The I/O Fund’s Top 15 Stocks for Q2 2026

Posted on April 21, 2026June 30, 2026 by io-fund

In 2018, the market was tumultuous from China trade wars, and the concept of an “AI data center” was not uttered by any stock analyst that I can recall. The AI blogs and Substacks you see today did not exist and the social media influencers that elaborate on the topic daily in 2026 were entirely focused on consumer tech and cloud (or had not yet begun investing in stocks).

This history is important as it substantiates who is early to a trend, yet it gets buried very quickly as most of what we read today is designed to be ephemeral. Being early to a trend is not simply a bragging right; it’s how the majority of the money is made in the stock market.

Jumping on a bandwagon yields lower returns as it means investing in what is already consensus. We avoid bandwagons, and instead, are often jumping off just as a trade gets too crowded. Below, I lay the groundwork for one of our boldest moves yet, which is to move to the sidelines with our Nvidia position. This move is driven by analysis that consistently questions: what is best for my Research Members right now? It is a question only afforded to the most independent research sites, of which there are very few.

While technologists and AI developers can devour information without penalty; investors cannot. Where investors are quite different is that every new data point and every hot take can lead to costly redirection. To contrast, our site is built not only to identify major trends and lesser-known tech stocks early, but to help Members move forward with calm confidence.

And in case it's gone unnoticed, the QQQs are flat this year. Many influencer-led tech ETFs are also flat to down – GRNY, IVES, and ARKK are all barely keeping pace with the broader tech index. In sharp contrast, we are up about 30% YTD, a meaningful outperformance during a bout of weakness in the markets and confusion around AI spending. Contributors include Bloom Energy, which we brought to our Research Members long before the stock became widely discussed — our initial entry near the 2025 lows is up over 1000% today. We also highlighted AAOI ahead of its 2026 surge, with the stock up nearly 300% YTD and over 650% since our lowest entry. We then doubled down on Lumentum in January with a 10% allocation, and the stock is up over 130% YTD.

Similar to previous reports, the report below is our team stepping back up to the plate and pointing in the direction we think the ball will land. It is over 70 pages long and took three weeks to write, combining deep thematic work, fundamental analysis, and portfolio-level judgment.

Although quite lengthy, this is about executing in the last inning when the game must be won. Whether you joined our site years ago or only since January, our official batting average is improving. Let's see if we can deliver for our Members again this quarter.

AI Accelerators: Shifting from Raw Compute to Unit Economics

AI accelerators are shifting their primary focus from raw compute to unit economics. Two years ago, Gartner had predicted 40% of existing AI data centers will be operationally constrained by power availability by 2027. That date is fast approaching, which means to continue selling GPUs or XPUs, leading AI semiconductor companies must actively work to solve for this constraint.

More recently, Morgan Stanley stated data centers are facing a “power shortfall totaling as much as 20%” for data centers through 2028. It’s expected there will be 13 GWs of shortage through 2028, when factoring in behind-the-meter solutions (more on that under the Energy section below).

While supplying power is outside of their domain, unit economics is something companies like Nvidia, AMD and Broadcom can help to improve. What this suggests is that the semiconductor supply chain will do everything within reach to lower the power requirements of AI systems from a design perspective.

To illustrate this approach, recently, the I/O Fund team covered how Arm is tackling lower power requirements in our write-up Arm Stock Could Win as Agentic AI Shifts the Bottleneck to CPUs Arm Stock Could Win as Agentic AI Shifts the Bottleneck to CPUs stating: “Arm is taking this a step further with a fully-liquid cooled, 200kW open-standard rack in partnership with Super Micro, packing 168 blades, or 336 CPUs, delivering a total of up to 45,696 cores. Arm EVP of Cloud AI Mohamed Awad stated that while it is a ‘200-kilowatt rack. We actually will consume about half that much power. We ran out of space. That’s why we couldn’t put more cores in there.’

This is one of the key advantages – it is not just about offering 2X the performance of x86 chips, but providing that performance boost while freeing up power for more compute or for more networking […] Arm says the new chip’s performance advantage over x86 could enable “up to $10B in capex savings per GW of AI data center capacity,” making it a compelling option for current and future agentic AI-optimized deployments to save money, save power and avoid Nvidia-lock in from its accelerator-agnostic nature.”

To connect the dots here, these stats should not be glossed over. As opposed to the compute-driven era we are firmly exiting, the way forward will be architectural designs that can lower power requirements. Instead of asking “how much compute can we build?” Big Tech is waiting in interconnection queues and waiting for the completion of nuclear power plants, asking: “How much compute can we actually power?”

Nvidia’s Systems are Becoming More Efficient:

There are two primary ways that Nvidia plans to assist in the push for better unit economics, such as cost per token and performance per watt. The first is to make each system they sell more efficient, and the second is to increase GPU density within the same power envelope.

In the March press releases from GTC, there is a subtle hint that Nvidia’s core KPI is not FLOPs anymore but rather tokens per watt.

Nvidia’s GB300 NVL72s offer 50X better performance per watt and 35X lower cost per token compared to the H200s. When comparing the Vera Rubin NVL72 to Blackwell, the new system delivers 4X better training performance and up to 10X better inference performance per watt.

In other words, if a data center has 100MW of power, then Vera Rubin allows 10X more inference in the same power envelope as Blackwell, which is critical for hyperscalers that are constrained by facility power.

More GPUs in the same Power Envelope:

As announced at GTC this year, Nvidia’s MGX racks will include rack-level energy storage capacitors to avoid the large load swings created by AI training and inference workloads. According to Nvidia, these spikes create stress on the grid and data center power infrastructure with these improvements resulting in lower peak current by up to 25% while Intelligent Power Smoothing will also help to reclaim stranded capacity:

“NVIDIA Vera Rubin NVL72 now introduces Intelligent Power Smoothing. It features 6x more rack-level energy storage (400 J per GPU) versus prior generations, and introduces a new closed-loop system that enables the GPUs to continuously monitor the state of charge of the capacitors to more efficiently flatten power profiles. This achieves much smaller AC power variation per minute, reduces peak current demands by up to 25%, and eliminates the need for massive battery packs to protect against large-scale power transients. At the facility level, provisioning racks at static Max-P strands power capacity that could otherwise be used to generate tokens. It assumes homogeneous workloads that always require peak power, when in reality AI factories run a mix of workloads with varying power needs.”

What Nvidia is describing here is that by flattening power spikes and by lowering peak current demand, Nvidia can put up to 30% more GPUs in the same facility power envelope. Max-P refers to static maximum power whereas Max-Q refers to allocating power more dynamically to accomplish better economics. In practice, the DSX Max-Q API is a software tool that Nvidia offers to achieve a token-per-watt goal rather than just raw performance.

Following GTC in March, Nvidia is effectively agreeing that power is the defining constraint of the AI buildout.

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The Importance of Cooling Technologies:

We’ve covered direct liquid cooling for a few years, beginning with Supermicro in 2023 and later with a cohort of cooling stocks in 2024. The simplest thesis as to why my Q2 report is emphasizing cooling technologies at this critical juncture for lowering power for data centers is the following:

“Cooling data center servers is responsible for 40% of the data center energy consumption. According to Dell, enclosed DLC solutions can save up to 23% of energy compared to traditional air-cooled racks. McKinsey places this number at 27% savings when there is 75% liquid cooled and 25% air cooled servers.:” – Liquid Cooling Leaders, June 2024 Liquid Cooling Leaders, June 2024

There are a few reasons why we dropped direct liquid cooling from our coverage over the past year or so but are picking it back up again as an important AI thematic trend. Although Blackwell offered both liquid cooled and air-cooled options in the B200s and the MGX NVL36s, many deployments remained with air-cooled because the current data facilities are built for air-cooled. This includes neoclouds, which also have a strong preference for the B200s and NVL36 with industry analysts stating the 40kW rack requirements were an easier upgrade from Hopper’s 20kW rack requirements, achieved by skipping a row: “Since it is only 40kW per rack, the MGX NVL36 can be air cooled […] This makes the MGX NVL36 very easy for existing datacenter operators to deploy without reworking their infrastructure.”

Rubin changes this as air-cooled is not an option as this generation reaches 180kW to 230kW per GPU. Nvidia is redesigning its Rubin racks to be “liquid cooled with high warm-water inlet temperatures,” which will help to lower facility power costs while freeing up more power for compute.

For Max-Q to be achievable (mentioned above), systems must be cooled to 45 degrees Celsius or 113 degrees Fahrenheit. According to Nvidia, this approach leads to “significant data center power savings,” resulting in up to 10% more GPUs being deployed. Here is what was stated:

“Operating at 45°C enables data centers in many climates to use ambient air and closed loop dry coolers for cooling, reducing the need for compressors, driving down PUE, and unlocking larger energy budgets for compute. Lower inlet temperatures of 35°C require data centers to divert massive amounts of facility power or water for cooling, while higher inlet temperatures maximize the amount of grid power converted directly into tokens. This yields significant data center power savings—enough to allocate up to 10% additional Vera Rubin NVL72 racks for more token generation in the same power budget.”

Rather than “cool” data centers, Nvidia is proposing to use warm water, which will require less power for chilling servers and allow more power to be used toward more compute. To achieve this, Nvidia uses facility water loops and coolant distribution units (CDUs) rather than direct-to-chip cooling to recycle the warm water across the facility.

All of the above marks an important change in tone for the Nvidia management team as it’s more about performance-per-watt and cost-per-token rather than raw performance or FLOPs. The first approach Nvidia is taking to decouple bigger racks from needing proportionate power is Intelligence Power Smoothing and warm-water cooling.

As investors, we should take our cue from the leading AI management team that the constraint in AI has officially shifted to Energy.

Nvidia’s Dominance Faces Its Biggest Test Yet

Recently, I’ve reiterated my $20 trillion market cap thesis, which translates to about 400% returns over the next four years, yet to assume Nvidia achieves this through hardware would be incorrect, in my opinion. The thesis hinges on software advancements and the recurring revenue that will inevitably come from Nvidia’s lead in robotics and simulation. Notably, I’ve held this opinion on the importance of Nvidia’s software business relative to hardware since 2023.

However, on the flip side, by saying software is central to the $20T thesis, I'm implying that Nvidia’s hardware moat becomes breached. Over 7 years ago, my original thesis on why Nvidia can become the world’s most valuable company when it was at a $100 billion market cap was centered on the moat the CUDA platform provides when I stated: “Developers will self-regulate the number of competitors for processing units due to a need for a universal platform that supports all frameworks.”

However, programming GPUs with the CUDA platform is primarily a training exercise as this is the phase where engineers are experimenting and need the developer ecosystem, including extensive tools like cuDNN, NCCL, debugging, custom kernel support, and CUDA’s massive libraries. The ecosystem has been built for over 20 years, has over 4 million developers contributing and every ML framework is first optimized for CUDA. The switching costs are extraordinarily high for engineers.

To contrast, inference is repetitive to where once a model is trained, the model is running millions of times per day. Serving platforms and inference frameworks like vLLM and TensorRT-LLM reduce dependency to develop on a specific software platform, like Nvidia’s CUDA. There is also more of a push toward open standards for the inference phase to reduce dependency on hardware specific code for serving paths, as tools like ONNX runtime, vLLM and the compiler Triton help to export models (or compile them) to be run agnostically on any AI accelerator.

In response to CUDA's moat weakening in the inference phase, Nvidia has pushed for their inference stack to remain proprietary by offering inference optimization software called TensorRT-LLM. TensorRT-LLM analyzes and optimizes LLMs to improve performance by running multiple operations on a single GPU kernel, selecting the optimal precision and optimizing memory usage for the key-value cache. Overall, Nvidia states this leads to 2-5X faster model performance for inference.

However, consider that Nvidia is needing this new attempt at vendor lock-in as the CUDA dynasty will not hold in the inference market. The open-source market is growing to become a serious contender to proprietary optimization software like TensorRT-LLM, as alternatives that are more community driven are available and accomplish something similar, such as vLLM and SGLang. Furthermore, large inference players like Cloudflare can build their own custom engines.

Expectations for the Erosion of Nvidia’s Market Share:

Below, I present what a few industry analysts are predicting. Although I believe these are aggressive, they help to illustrate what is in front of Nvidia as the hardware moat becomes breached.

Counterpoint Research believes that by 2028, custom silicon will cross the 15-million mark to surpass GPU shipments as the top 10 hyperscalers will have deployed 40 million AI server compute ASIC chips cumulatively during 2024-2028, stating: “What is also supporting this unprecedented demand is AI hyperscalers building significant rack-scale AI infrastructure based on their in-house stacks, such as Google TPU Pods and AWS Trainium UltraClusters, enabling them to operate as one supercomputer.”

TrendForce is the most aggressive forecast, stating GPU-based AI servers will account for 69.7% of shipments in 2026 with ASIC-based servers rising to 27.8%. This doesn’t account for GPU market share from AMD, which if you put that at 10%, would result in Nvidia’s market share being 59.7%.

With the information that I have today, these forecasts are too aggressive.

According to Broadcom, they’ll see $100B in AI chip revenue in 2027 and we’ve modeled another $50B in networking. If we allocate $60B to AMD and go with what we know of Nvidia’s stated trajectory to $1 trillion in revenue, then the split looks something more like this for 2027:

NVDA $500B
AVGO $150B to $200B (assuming mgmt team was being conservative we will use the $200B number)
AMD $60B
Total among top 3 silicon providers: $760B with NVDA at 66% market share

However, one data point that complicates things is MediaTek could see 150,000 CoWoS wafers in capacity in 2027, compared to 20,000 in 2026. Thus, the landscape is evolving in terms of the number of competitors.

Reference more CoWoS allocation notes under the AMD section.

The Linchpin: Rubin Delay Related to HBM4

The reason for closing our Nvidia is two-fold. As outlined above, custom silicon is expected to gain meaningful share in the coming years. Nvidia’s GPUs come at a significant premium, and Big Tech seeks to lower total cost of ownership. Additionally, inference prioritizes repetition and efficiency over general-purpose flexibility, where the CUDA moat matters less than it did during the training market.

At the same time, custom silicon is designed for specific workloads, allowing for lower power requirements, which is a critical advantage during a window when power will be greatly constrained.

To add to this, we are getting additional confirmation of an incoming Rubin delay. To be blunt, this is terrible timing for Nvidia as Big Tech was already diversifying with custom silicon. This makes a stronger case for having back-up orders with Broadcom, MediaTek and/or AMD.

HBM4 validation times have been cited as one key factor behind the delays for Nvidia’s upcoming Vera Rubin generation – we have seen in the past that these qualification tests can extend as long as 18 months, such as in Samsung’s case with HBM3e. Currently, reports suggest this HBM4-related delay could persist for one quarter.

Reports suggest this delay stems from Nvidia pushing suppliers to “request speeds of over 11 Gb/s per pin,” well above the JEDEC standard of 8Gb/s. More evidence for a delay is surfacing, with DigiTimes reporting on April 15 that SK Hynix is “considering reducing its planned 2026 shipments of high-bandwidth memory (HBM4) to Nvidia by about 20-30%.”

We also have another report stating SK Hynix is delaying its HBM4 production ramp until Q3, instead of its original Q2 target, with the delay said to better align with Nvidia’s schedule. Any potential delays or shipment cuts at SK Hynix also could be a key factor in a Rubin delay, as SK Hynix reportedly secured more than 70% of HBM orders for the upcoming chip; on the other hand, Micron and Samsung both have announced that HBM4 is in mass production for Vera Rubin, easing some of the supply constraints.

Memory: Pricing Power Takes on Market Doubts

The market is presenting two very different extremes with surging DRAM and NAND pricing causing memory stocks to skyrocket, until recently, when this subsector came to a screeching halt following Google’s TurboQuant announcement. The announcement got a lot of attention as Google stated they can deliver up to a 6x compression on LLM memory and vector search.

The Google TurboQuant announcement specifically addresses the KV cache, which essentially serves as a model’s long-term memory that is reused and extended throughout many steps or requests. KV cache capacity is a known pain point when working to balance long-context reasoning and memory capacity in inference workloads, as it can consume ~30% of GPU memory during deployment.

TurboQuant directly addresses this pain point by compressing the vectors (queries from users and keys in the KV cache) via real-time quantization, reducing the amount of bits needed to store ‘high-dimensional’ or complex data such as image features. This is increasingly important with AI coding, natural language processing, and multi-agent workflows, as the more a model is used, the more memory the KV cache takes up as it stores all of the prior responses.

Alphabet says TurboQuant can drive a 6X reduction in KV cache memory size, all while preserving model accuracy and accelerating speed up to 8X. However, there is some debate here as industry analysts have noted that “actual memory savings are around 2.7x, with speed improvements of about 4x.”

The market first interpreted the TurboQuant release as a memory ‘demand killer’, though it’s possible that the true reality may be that this is another ‘DeepSeek moment’ (as stated by Cloudflare’s CEO), where these new optimizations simply drive more AI infrastructure and thus more memory demand. It may all boil down to what Alphabet itself acknowledged – that TurboQuant “lowers memory costs.”

This could be another Jevon’s Paradox in the making, where the new efficiencies created on the KV cache side simply drive memory and AI infrastructure demand higher (not lower) by opening up new use cases and reducing memory costs.

Looking at this from the lens of AI inference, or inference at the edge or on local devices, the ability to reduce KV cache footprint, boost speed, preserve accuracy, lengthen context windows and allow for more concurrent requests may drive faster adoption of applications such as multi-agent systems, coding and natural language processing.

TurboQuant does not reduce the need for HBM in AI accelerators, as HBM will still be critical for parameter storage for training; it simply minimizes KV cache usage in inference. It also does not replace the NAND flash and SSD storage layer for training data, inference data retrieval and caching. Instead, what it likely will do is allow larger models to be run on the same accelerator footprint, and enable and broaden access to previously infeasible memory-intensive workloads (like multi-agent systems) to a wider range of users, from lowering memory usage and decreasing memory costs.

While the market grew concerned over TurboQuant, the other side of the picture – prices – may have been lost in the noise as the release was cited as a key contributor to a slight pullback in DRAM prices over the last few weeks. The 10,000-foot view instead shows DRAM prices had risen >20X over the last year, with robust price momentum for both DRAM and NAND throughout Q4 and Q1 that is now extending into Q2.

Key factors behind the rapid ascent in prices included major manufacturers shifting supply to prioritize AI-related HBM and LPDDR (server DRAM) demand, and new chips such as Nvidia’s Blackwell Ultra incorporating 50% more HBM capacity per chip versus Blackwell. This strong demand, increasing content of HBM attached to accelerators and DRAM content growth in AI servers is also why we saw Micron shutter its consumer DRAM unit to focus solely on AI. The NAND and enterprise SSD side faces extremely tight supply coupled with strong AI storage demand — Kioxia sold out of 2026 NAND capacity in January, and reports surfaced recently that controller supplier Phison’s CEO said that “every NAND manufacturer told us 2026 is sold out.”

Closer Look at the Memory Pricing Surge

It’s safe to say that looking back, the ascension and sheer pace of memory prices caught the entire industry off-guard as supply constraints worsened.

The vertical ascent in memory prices first became visible late last year within DDR4/5 chips for PCs, with prices surging from roughly $6.84 in September to $27.20 by December as supply and inventories rapidly tightened. This surge quickly extended well beyond PC/consumer DRAM, as server DRAM, NAND flash and enterprise SSDs also witnessed prices rise sharply into year end and early 2026.

For example, back in September, TrendForce had initially estimated conventional DRAM prices to rise 8-13% QoQ in Q4 driven by some supply constraints for DDR4/5 for PCs, and up 13-18% QoQ when including HBM. By November, reports were surfacing that quotes from Samsung were rising from $149 to $239 for 32GB DDR5, with other capacities all rising 30-50% since September, more than 3X the estimated quarterly increase.

By the end of Q4, conventional DRAM prices were pegged at +45-50% QoQ, far above initial estimates, with HBM-blended prices up 50-55% QoQ. The price hikes were only projected to worsen moving through Q1, with TrendForce estimating conventional DRAM prices up 90-95% QoQ (on top of Q4’s increase), driven by PC DDR4/5 up 105-110% QoQ and LPDDR5 server DRAM up 88-93% QoQ. Samsung had reportedly doubled its DRAM contract prices in Q1 versus Q4, with Q2 expected to see another 30% increase on top of that.

On the NAND side, prices followed a similar trajectory, with Q4 prices for enterprise SSDs estimated at 25-30% QoQ, with total NAND flash prices reported to be up 33-38% QoQ. For Q1, TrendForce had estimated at the start of February that the pace of NAND flash price hikes would quicken, rising 55-60% QoQ, with enterprise SSDs nearly matching that pace at 53-58% QoQ. By the end of March, barely eight weeks later, and NAND prices were estimated to be significantly higher, up 85-90% QoQ.

Initial price estimates for Q2 signal robust momentum continues, with conventional DRAM forecast to increase 58-63% QoQ, and NAND flash rising 70-75% QoQ. However, DRAM prices have recently pulled back around ~20-30%, with reports pointing to two main factors for the decline – distributors beginning to sell off stockpiled inventory and TurboQuant. Even with this correction, it should be noted that DDR4/5 prices remain >20X of their early 2025 prices.

For HDDs, pricing is more obscure. Major suppliers WDC and Seagate have already sold out of capacity for 2026 with price and volume conditions set in contracts, though 2027 pricing has not been set, and is the bigger catalyst on the horizon.

WDC executives noted that last quarter, prices were up “2%, 3% on an ASP per terabyte basis,” with the pricing environment stable and expected to remain stable moving forward, implying similar steady growth through the rest of this year. Some reports suggested HDD contract prices rose ~4% QoQ, still a far cry from the rapid ascent seen in SSDs.

Looking further ahead for HDDs, analysts from Morgan Stanley see 2027 pricing potentially being much stronger than currently expected. MS explained that they see “sustained hyperscaler demand strength, elongating customer visibility [and] firmer pricing into 2027,” with its initial channel checks suggesting hyperscalers are closer to paying $20 per terabyte for 2027 and 2028 capacity. This is significantly above current estimates for $13 to $15 per terabyte.

Even with capacities selling out and prices rapidly advancing above expectations, the market is still finding a way to doubt the runway for memory stocks. This likely stems from memory’s cyclical nature, previous history of rather violent swings from peak to trough, and an expectation that current prices will soon peak and quickly reverse.

However, the current environment has key ingredients for prices to remain strong. While it may be unlikely that we see prices rise >60% QoQ in each and every quarter this year, the persisting supply shortages coupled with the strength of AI-driven demand and timing of capacity expansion suggest that prices may not immediately reverse but rather remain elevated for longer – perhaps into 2027.

Current expectations predict this supply shortage will persist through late 2027, though key industry executives are beginning to pencil it in lasting even longer. Intel CEO Lip-Bu Tan believes there will be “no relief” until 2028, while SK Group Chairman Chey Tae-won stated at Nvidia’s GTC that the shortage could persist another four to five years as wafer supply may lag demand by more than 20% at times.

This is because capacity expansion efforts will take multiple quarters to materialize. For example, Micron detailed that initial output from its first Idaho fab is slated for mid-2027, while its Singapore fab and new Tongluo fab will add supply in late 2027 through 2028. Kioxia is planning to double its 2024 NAND capacity, but this will not be achieved until 2029, with equipment spending remaining below 2023 levels as NAND manufacturers remain cautious on spending to prevent oversupply.

Samsung and SK Hynix are said to be prioritizing boosting 1c DRAM for HBM and DDR memory for AI applications, with NAND on the back burner for the two; SK Hynix is reportedly projecting a capacity boost in 1H 2027 to double 1c DRAM output, while SK Hynix on the DRAM side, aiming to double its 1c DRAM output; Samsung is aiming to triple its 1c DRAM capacity by year-end 2026, supporting the ramp of HBM4.

AI Networking:

The stock market is like musical chairs, and you don't want to be the one left standing when the music stops. When it comes to networking companies gaining content on a platform or losing incremental share, nowhere does the supply chain shift faster than networking. This goes back to the differences between technologists and investors; an investor cannot afford to be the last one out whereas AI enthusiasts can devour information and debate without penalty.

The reason networking sees immense volatility is straightforward: much of the market is tied to a single customer, Nvidia; and Nvidia is rolling out new architectural iterations at an unusually fast pace these days.

On that note, we wanted to give our Members’ a heads-up last quarter that the copper-to-optics boundary was shifting, stating in the Q1 2026 AI Top 15 Report that:

“While copper-based links remain essential for short-reach, low-latency connections—particularly within NVLink scale-up domains—the expansion of Ethernet fabrics, higher port counts, and the adoption of co-packaged optics are driving an inevitable shift toward optical content.

Blackwell and Blackwell Ultra are fundamentally focused on solving scale-up problems, where the primary challenge is binding large numbers of GPUs into a single coherent node using ultra-dense, low-latency NVLink fabrics.

Rubin, by contrast, is primarily focused on assisting higher bandwidth requirements, as the focus is now on sustaining inference and training workloads at scale without bottlenecks forming beyond NVLink. The limiting factor is how efficiently bandwidth can be delivered and distributed across racks and fabrics, resulting in higher port counts, faster link speeds (800G now and moving toward 1.6T).

[…] The increasing amount of computing nodes (especially as Nvidia pushes towards the NVL576 with Rubin Ultra) along with increasing amount of interconnects means that bandwidth must also increase, from 400G to 800G and now to 1.6T, to ensure that low-latency, high-throughput communication remains across the entire platform.

As a result, it’s expected that optics move closer to the switch, as copper and AEC content becomes constrained by reach and signal integrity. The result is a networking stack where silicon photonics capture incremental value, even though copper remains relevant and intact at the shortest distances. “

To continue on the theme for this report, networking is no longer optimized around compute. Instead, the road map for AI systems is forced to address fixed power envelopes while also preparing for larger clusters. Not surprisingly, the motivation to move to silicon photonics and co-packaged optics is also about reducing power consumption, stating CPO could “slash power consumption by 3.5X compared to traditional pluggable transceivers.” The press release goes onto say that by eliminating external DSPs and reducing the signal path from inches to millimeters, CPOs “dramatically boost power efficiency.”

There are additional reasons, such as reducing component count and enhancing performance as adding DSPs can result in latency, as well. This becomes even more evident as data rates become faster with DSPs consuming half the power draw of a 1.6 Tbps transceiver.

In a recent press release, Broadcom stated co-packaged optics can offer 65% power savings compared to re-timed pluggable optics. These may seem like big numbers but remember that compute is the bulk of the power draw, thus the overall impact is likely in the single digits.

Although both of these companies have voracious appetites to control as much of the scale-up networking stack as possible, there are key areas where smaller vendors can participate, such as supplying ASIC switches, optical transceivers including lasers like EML, VSCEL, CW, Silicon Photonics chips and interconnects.

To illustrate the opportunities for smaller vendors, Lumentum has been able to capitalize on tight EML supply and pricing power. In fact, EML shortages are so severe, that hyperscalers are accelerating the SiPho timeline by adopting alternatives like a combination of CW lasers and silicon photonics to forego waiting for more indium phosphide (InP) supply.

The CW laser-SiPho combination combines a continuous-wave (CW) laser with a silicon photonics chip to handle modulation, which opens up the supplier base. Here is what a December TrendForce press release stated:

“CW lasers offer a steady optical signal and are paired with silicon photonics chips produced at semiconductor foundries used as external modulators. Their simpler design stems from the absence of integrated modulation, which broadens supplier options. Consequently, CW lasers combined with silicon photonics have become the main alternative route for CSPs facing EML shortages.

However, CW production faces increasing constraints due to several factors: long equipment lead times restrict expansion, and strict reliability standards necessitate labor-intensive die-cutting and aging tests. Consequently, many vendors outsource these steps, which adds to downstream bottlenecks. This situation is causing the CW ecosystem to approach a capacity crunch, leading suppliers to hasten their expansion efforts.”

Yet, even if EML demand can source elsewhere to alleviate the bottleneck, a company like Lumentum remains in pole position to supply external InP-based CW lasers along with other suppliers.

We also recently covered a long-haul networking supplier on the Discovery tier that specializes in long-haul networks, an area that Nvidia and Broadcom are unlikely to compete with vendors as it requires expertise in telecom networks and the ability to distribute AI traffic between data centers.

Another growth opportunity is VSCEL lasers, which are ideal for high-volume and short-reach interconnects as they are low power and low cost. Broadcom recently emphasized VSCEL lasers for their ability to help AI clusters scale beyond copper while still providing short-reach efficiency. This is called near-packaged optics (NPO) and will bridge the limitation of copper today with the 1+ year deployment of co-packaged optics.

Here is what Broadcom stated – note this is a longer quote but nicely summarizes how the shift toward optics is likely to play out:

“The insatiable demand for compute power in AI and high-performance computing (HPC) is rapidly approaching a fundamental physical barrier: the limits of copper connectivity. As next-generation XPUs demand bandwidths soaring toward 28.8 Tbps, traditional copper interconnects are struggling to keep pace.

With SerDes rates reaching 100 Gbps per lane, the effective reach of Direct Attached Copper (DAC) has shrunk to a mere 5 meters. For operators, this restricted electrical signal is a roadblock to building the massive, disaggregated AI clusters required for the next era of innovation.

While the future of data center connectivity is undeniably optical, the path forward requires a pragmatic approach. Co-Packaged Optics (CPO) remains the "North Star" for energy-efficient, high-bandwidth scaling, but the industry needs a high-performance solution that can be deployed today.

Vertical Cavity Surface Emitting Laser (VCSEL)-based Near-Package Optics (NPO) serves as that essential bridge. By leveraging readily available 100 Gbps VCSEL technology—with 200 Gbps solutions already in development—NPO offers a practical, high-performance alternative to traditional pluggable optics.”

Note: We will be publishing a thematic piece on the CPO opportunity later this month. We plan to continue tracking this space closely as it evolves and aim to offer best-in-class execution, particularly given that many of our top winners over the past 12 to 18 months have come from AI networking.

AI Monetization is Heating Up

If you and I were in an elevator and I had only a few seconds to explain my view on the AI market, I’d say this: the biggest opportunity for AI stock returns still lies ahead, not behind us.

A few months back, I wrote in a free newsletter that the greatest risk to an investor is not an AI bubble or the many other headlines that surface and weaken AI stocks, but rather the biggest risk in the current market is that an investor misses out on what be one of the strongest investing opportunities of our lifetime: what I’ve dubbed the AI Monetization Supercycle catalyzed by the inference phase.

Recently, Reuters reported that OpenAI is seeing more than $25 billion in annualized revenue (although at what margin is still to be seen). OpenAI also recently stated enterprise now makes up 40% of revenue, and adoption on its consumer remains strong with 900 million weekly active users.

Anthropic also revealed that its revenue run rate has now surpassed $30 billion in early April, more than doubling from February’s $14 billion and up $21 billion since the end of 2025. This helps investors with timing as it illustrates we are moving away from the experimental R&D phase. Notably, this is the fastest ramp in revenue we’ve seen in the tech industry.

Tokens are the ‘currency’ of this monetization wave, and there’s ample evidence that the market is continuing to underestimate the sheer volume growth ahead in tokens (and thus revenue) as inference-based applications expand and new use cases pop up week after week. Dell’s COO Jeff Clarke provided a great visual on the growth point, explaining that his company had originally modeled inference driving 1 quadrillion tokens by 2028, but now that view has already risen 57X:

“The demand for inference, long thinking, auto aggressive reasoning models is now requiring more computational intensity. At minimum, at a minimum, 100x, two orders of magnitude greater than we thought less than a year ago. More than two orders of magnitude more than we thought just a year ago. And while that shows up in, in the form of tokens, the measure and what do tokens need, tokens need computational capacity and capability to provide them. We thought as we model this, that inference would drive by 2028, 1 quadrillion, that's 15 zeros, 1 quadrillion tokens. Now it's 57 quadrillion, and I'm sure we're wrong.” 

To wrap your head around just how big 57 quadrillion, if you spent $1 million dollars each and every day, it would take more than 156 million years to reach that number.

What’s more impressive here is that the token growth is already rapidly accelerating and well on the way to reach that 57 quadrillion estimate. Alphabet revealed in Q4’s earnings in early February that its first party models including Gemini were processing more than 10 billion tokens per minute via direct API use, up more than 40% QoQ from 7 billion per minute in Q3. To apply this to Dell’s framework, that would be more than 5 quadrillion tokens annualized.

According to a note written by OpenAI’s CFO in early April, their APIs are processing 15 billion tokens per minute, up 2.5X from 6 billion tokens per minute just six months ago in October. This would represent nearly 7.9 quadrillion tokens annualized.

Combined, Alphabet and OpenAI alone are processing nearly 13 quadrillion tokens annualized, while growing >40% QoQ and 5X YoY. When taking into account Anthropic, AWS, Azure, OCI and all of the other R&D labs running models in the cloud, we may well be at the 57 quadrillion pace at some point this year.

Perhaps more important than revenue is the capability of models with OpenAI’s GPT 5.4 “Thinking” model scoring 83% on the GDPVal benchmark, placing it at or above human experts on economically valuable tasks. In Morgan Stanley’s “Intelligence Factory” model, these breakthroughs “lead to an accelerating learning curve, with successive models rapidly outperforming their predecessors”

In other words, because models are outperforming their predecessors, it makes for a case for more AI spend (not less), supported by the unprecedented revenue trajectories we are seeing from R&D labs now, but likely Big Tech soon too.

In their last earnings report, Microsoft stated, “We are only at the beginning phases of AI diffusion and already Microsoft has built an AI business that is larger than some of our biggest franchises.”

Alphabet stated they’ve sold more than 8 million paid Gemini Enterprise seats to more than 2,800 companies with customer interactions growing 65% year-over-year – all within four months. The management team made another comment about the impact AI is having on independent software vendors, stating: “Revenue from AI solutions built by our partners increased nearly 300% year-over-year, and commitments from our top 15 software partners grew more than 16x year-over-year.”

Initial Signs the Agentic AI Market is Taking Off

Model context protocol (MCP) is a standard that lets AI models connect to external tools, data and systems. The standard allows AI to have access to tools and to be able to take actions, which marks an important shift to agentic AI. It also will lead to skyrocketing inference demand as the protocol allows AI agents to query databases, make API calls and execute, leading to significantly higher token usage.

Anthropic released MCP as an open standard in late 2024, with OpenAI adopting it in April of 2025, Microsoft adopted MCP in July of 2025, and AWS in November of 2025. Today, MCP-compatible tooling was donated to the Linux Foundation and is the default protocol for agentic AI with 97 million downloads. MCP is often compared to TCP/IP, or the internet protocol that is owned by nobody yet enabled extensive development across the broader web. Furthermore, without a standardized protocol, developers would have to build observability at an unsustainable level for every tool integration.

MCP is what powers Claude Code’s workflows, allowing the LLM to use internal databases and external APIs. AI is transitioning toward “autonomous execution engines” by going beyond the terminal command on a computer to now accessing external tools, such as querying a database or sending Slack messages. Each MCP connection results in a bigger and better workflow, adding to the complexity that AI agents can handle autonomously.

MCP adoption is essentially a leading indicator for the enterprise agentic AI market, as it’s the protocol that deploys AI agents that are capable of production at the system-level. The acceleration in SDKs from 2 million monthly downloads to 97 million across about 18 months is signaling the inference market is beginning to take off.

Although I can’t promise timing will be exactly in 2026, a reasonable assumption is 2H 2026-2028 time frame. Gartner is more bullish on timing than even myself, stating 40% of enterprise applications will integrate task-specific agents by 2026, up from less than 5% in mid-2025. According to Deloitte, 93% of IT leaders plan to introduce autonomous agents in the next two years, while nearly half have already implemented them.

Going back to my introduction on execution, and pointing to where I plan to hit the ball, the inference opportunity resembles more of a zero-sum game. We can see evidence of the market agreeing as the software trade has been hit hard lately. The I/O Fund team is cautiously optimistic for a time when software dominates our portfolio again; but that time is not right now.

AI Energy: Last but Certainly Not Least

Although I originally thought compute would mark the largest supply-demand imbalance in my career, remarkably, there is another imbalance that carries far more importance. Which brings me to our last thematic trend for Q2: AI Energy.

Two years ago, the I/O Fund began setting the stage to remain competitive on portfolio returns by introducing energy to our Research Members when we stated: “Big Tech is spending tens of billions quarterly on AI accelerators, which has led to an exponential increase in power consumption. Over the past few months, multiple forecasts and data points reveal soaring data center electricity demand, and surging power consumption. The rise of generative AI and surging GPU shipments is causing data centers to scale from tens of thousands to 100,000-plus accelerators, shifting the emphasis to power as a mission-critical problem to solve.”

At the time of publishing, there was not even a whisper on the Street about the incoming fundamental bottleneck to AI data center expansion. While those who only follow our free analysis think we’ve been stuck on the Nvidia thesis for years, the truth is Nvidia hasn’t been our leading allocation for quite a while.

As you know by now, Bloom Energy was one of our biggest winners last year and I reiterated it was a Top Stock Pick for 2026. But it would be too narrow to focus on Bloom as the only destination for our energy allocation. We have many others we want to own when the timing is right.

Consider this question from my point of view, which is, will there be a time when energy dominates our AI allocation, even above and beyond AI accelerators or networking? Yes, that time is approaching. We want to be fastidious in our analysis now given the I/O Fund tends to be about 2 years earlier than the Street – and well, we are coming up on our first coverage being 2 years ago, indicating the time for energy to lead could be nearer than you might think.

Briefly Revisiting the AI Energy Thesis

Up to this point, we’ve hammered on the increase in power requirements across Nvidia’s GPU systems. To keep the math simple, it looks like this:

Blackwell doubled the power consumption of the previous Hopper generation from 70 kW to 120 KW-140 kW.
Vera Rubin will increase 50% from 180 kW to 230 kW
Rubin Ultra racks with 576 GPUs will increase this by roughly 3X to 600 kW by late 2027. That’ll represent 5X in a two-year design timeframe.

Note, these figures do not include networking, interconnects, cooling and other hardware, which will further boost power draw per rack.

The numbers above reveal Nvidia’s aggressive product road map is set to release new GPUs every 1-2 years, yet grid infrastructure operates on a 5-10 year timeline. For example, in its largest configuration, the Vera Rubin NVL576, dubbed the ‘Kyber’ rack, could draw as much as 600kW or 5x that of the GB200 NVL72 in just a two-year design timeframe.

Therein lies the compounding problem that brought us to Bloom Energy, which is that current data centers are fitted for 50kW racks and need to be retrofitted for 600kW racks. This will move to 1 MW racks as AI servers are expected to use over 1000 kW of power in the Feynman architecture due out in 2028, which represents 8X the power requirements of Blackwell in about 4 years' time.

In the Q1 2026 Top 15 AI Stocks Report, I emphasized the timing issue the AI data center buildout faces specifically between 2026-2029:

“For example, across the board, developers are expecting to have power delivered by late 2026 to early 2027 on average, with most regions seeing expectations as early as late 2025. This is likely driven by consistent strong demand for AI infrastructure services, as new capacity will allow hyperscalers to meet more demand and drive more revenue.

Yet, utilities do not expect to be able to meet these delivery timelines in most of these primary and secondary markets, with many projecting late 2027 through 2028, with major hub Northern Virginia seeing one of the longest timelines at nearly 2029.”

Since I wrote that in mid-January, the problem has only been exacerbated. The capex raise we saw in late January through early February of nearly 40% to $600 billion is bullish for key suppliers but also puts into question how to power an increase in compute that is into the hundreds of billions year-over-year.

For example, following capex raises, this estimate from Congress.Gov on January 23rd is likely outdated, which states that U.S. data center energy use comprised 4.4% of the United States annual electricity consumption yet is expected to consume 12% by 2028 for a 3X increase.

Evidence Mounts on the Incoming Energy Shortage

Evidence of an energy shortage is growing each quarter. For example, we covered in a Discovery tier analysis that PJM clearing prices have surged to the tune of 11X over the past two years. This began in the 2025/26 auction, where clearing prices jumped 833% from $28.92/MW-day to $269.17/MW-day, reaching the annual cap. The 2026/27 auction saw prices once again hit the FERC-approved cap at $329.17/MW-day, a 22% YoY increase.

Skyrocketing power prices and elevated risk of grid shortfalls from a fifth consecutive year of declining supply puts major emphasis on adding new capacity to the grid. What the Street (and the public) have not realized yet is the extent of the incoming capacity that is being claimed by data centers. PJM reported in August that it's long-term projected load growth from 2024 through 2030 would be 32GW, with 30GW of that coming from data centers, assuming many data center projects materialize on time.

However, the problem here is that PJM’s forecasting has recently underestimated peak demand growth, even with significant upward revisions over the last few years. For example, realized peak demand is already approaching 160 GW, nearly two years ahead of current forecasts, and if data center builds progress at current (or accelerated) paces, peak load may continue to outpace forecasts through 2030.

This helps explain why the market is not unilaterally rewarding Nvidia for capex raises in the same manner as during the Hopper architecture. Not only will a higher percentage of capex be allocated to energy; but it’s also a puzzle as to how this will be perfectly resolved. We had noted in a previous analysis the risk is that GPUs sit idle:

“If a company like Microsoft buys tens of billions of Nvidia’s Blackwell GPUs, the longer the massive investment in GPUs waits for power, the more delayed that revenue and profits become. In turn, this plays into market share as competitors who can energize GPUs faster will have a critical head start over those that are waiting for power. This is simple in concept, yet the lack of power having vast consequences cannot be overstated if you combine the sheer size of investments being made in AI alongside fierce, heightened competition.

AI is a spending race, but this means it is at the core, a power race. It does not matter if a hyperscaler spends tens of billions more on capex if it cannot secure the power to stand up new data center infrastructure to then deploy those GPUs immediately. The AI market is officially moving from being compute constrained to being power constrained, and this shift is important for I/O Fund members to prepare for.” –Why Power is Critical for Data CentersWhy Power is Critical for Data Centers

Notably, most growth investors do not have experience generating returns in the energy sector. It has long been one of the most difficult industries to find alpha, given its lumpy cycles, commodity sensitivity, and heavy exposure to regulation.

That is where the I/O Fund’s flexibility becomes a meaningful advantage. Our process is designed to be early to stocksearly to stocks (as opposed to a process that is designed to establish expertise in only one domain). This has allowed us to find winners year after year in every subsector of technology. You can fully expect us to use our flexible yet effective process in the energy sector over the coming years.

Large-Scale Utility:

Large-scale utility is naturally the first subsector to think of to address the energy crisis. Utilities benefit when there is this much demand because one thing utilities do well is deliver reliably.

As discussed, the PJM clearing prices saw prices surge 11X over the past two years when you combine the 2025/2026 prices jump 833% to $269.17/MW-day and then again 22% in the 2026/2027 auction prices to $333.44/MW-day. When you consider zones that are further constrained, such as BGE and Dominion, the prices increased even further to $465.35/MW-day and $444.26/MW-day, respectively, in the 2026/2027 auction.

This represents a cap for the $333.44 MW-day as the auction pricing would have hit $530/MW-day without the cap.

When we look at large-scale utility stocks such as Talen, Constellation Energy or Vistra, the high auction prices are leading to higher prices on their existing assets. Although that may seem intuitive, the key here is they don’t have to spend more on capex to report higher profits – which is a rarity right now.

Utilities like Constellation Energy, Vistra and Talen earn capacity revenue in addition to energy revenue. The retainer payment correlates to the following capacities:

Constellation cleared 17,950 MW in the latest auction for roughly $2.2 billion in capacity revenue for 27/28.
Vista cleared 10,566 MW in the latest auction for roughly $1.3 billion in capacity revenue for the 27/28 year
Talen cleared 8,745 MW in the latest auction for about $1.1 billion.

According to a recent report from Morningstar, energy prices increased from $33.74 MWh to $50.73 MWh in 2025, for an increase of 50.4%. If we break the report down further, we see that capacity costs are skyrocketing.

Energy is 59.6 percent of the cost of wholesale power and rose 51.2%
Capacity is 15.8 percent of the cost of wholesale power and rose 262.3%
Transmission is 22.4 percent of the cost of wholesale power and rose 4.5%

Capacity is where the auction pricing surge is showing up as energy companies are paid more just for having capacity exist. When energy pricing goes up, it’s because energy costs more. However, capacity pricing is surging while Utility companies do very little to justify this increase as there were no new plants built or new upgrades. Conversely, Utilities benefit from not adding new plants as it creates scarcity pricing.

As you can imagine, residential and commercial customers in data center regions aren’t too happy about having to absorb capacity pricing, which is allocated more broadly rather than tied to usage. For example, according to a recent report from IEEFA, the residential bill in Maryland is expected to go up $18/month and up $16/month in Ohio, as " ratepayers across the region will collectively be paying an additional $1.4 billion in capacity market costs, again driven largely by data center demand.”

This is important to consider as investors typically want to see uncapped growth in a stock, yet growing concerns from consumers could lead to another capped PJM auction come June 2026.

Talen is more of a pureplay for PJM auction pricing compared to Constellation which includes the recent Calpine acquisition, a retail business and is exposed to many markets outside of PJM like gas-heavy ERCOT and CAISO. Although Talen is not entirely PJM, it’s heavily centered in this market, which helps to strip out the revenue trajectory seen below. The main takeaway is the bulk of the growth is accounted for in the strong 2026 year, yet there is a leveling out in future years as it implies capped auction pricing.

However, profits are expected to outpace revenue growth, which means despite Utilities not fitting the growth characteristics we typically seek at the I/O Fund, there could be times their defensibility is attractive.

Behind-the-Meter:

There exists a significant disconnect between when hyperscale and colocation developers expect to have site power, and when large-scale utilities expect to be able to deliver. This means even if you want to build a new facility for 600kW racks, getting power to it is a multi-year ordeal.

Due to time constraints, connecting new data centers to the grid is not the most feasible option for hyperscalers looking to deploy gigawatts of capacity quickly, and instead, alternative power sources in the near term will be in higher demand. This is supported by research from TD Cowen regarding grid connection timelines for new data centers, which span anywhere from 36 months to 48 months in these markets. In 2024, Bloomberg reported that utility Dominion Energy said >100MW data centers in Virginia were facing up to seven year wait times for new connection hookups.

This has led to firms like McKinsey predicting 25% to 33% of net new generation will come from behind-the-meter solutions by 2030. This is significant considering the market was effectively zero going into the AI boom.

We've covered the advantages of behind-the-meter and on-site power generation for about two years. Briefly, it refers to bypassing the grid entirely by generating power on-site or nearby with solutions like natural gas turbines, small modulator nuclear reactors, fuel cells and solar/batteries. These solutions don’t require the grid and can be deployed in 1-2 years time or as quickly as 3 months in Bloom Energy’s case.

In our September analysis, we began to answer the question of how many GWs correlate to capex spending. For 2025, we had projected Big Tech could bring on 7-9 GWs with 2025 capex, and then 9-12 GWs with 2026 projected capex, for a total of 16-21 GWs across the two years. We raised this another 4GWs to include Oracle for a total of 20-25GWs for 2025 and 2026, yet this still does not include xAI, CoreWeave or Nebius.

Given the capex increases we saw in January, that 2026 number has nearly doubled, even without including the neoclouds, with our September framework projecting Big Tech and Oracle could bring on 16-20GW this year alone. Cumulatively, that could bring total capacity additions in 2025 and 2026 to 23-29GW.

Put another way, any raise in capex spending over the next two years puts greater emphasis on behind-the-meter solutions.

The Case for the Miners

The term “don’t throw the baby out with the bath water” could apply to Bitcoin Miners. Despite weak price action over the past few months, it’s hard to imagine a way forward without utilizing these brownfield sites.

Applied Digital pointed out that less than two percent of data centers have racks with greater than 50kW. Where retrofitting is attractive is not necessarily the costs associated with construction but rather that the turnaround time for using an existing facility can be shortened from 4-7 years to 18 months to 30 months.

Bitcoin mining is not behind-the-meter in a strict sense, but it is effectively behind-the-meter because miners secure direct, wholesale power through upfront contracts that are not renegotiated. They are also considered on-site power as there is minimal transmission dependency due to co-locating near a mix of power sources (near gas plants, augmented by wind, solar, water/hydro). In most cases, even if a utility meter exists, the power system is purpose-built for that site and is not shared retail infrastructure. This also helps equal the playing field as the biggest drawback for Bitcoin Miners is they need extensive retrofitting.

You’ve heard me use the words “time to power” before to describe Bloom Energy’s investment thesis. Bitcoin Miners are similar – they offer time to power. Not only do Bitcoin Miners offer speed, but they also offer below-market rates to hyperscalers.

Regarding the weak balance sheets, for the very best power sites, this will transform quickly as these companies are transitioning from volatility that is characteristic of Bitcoin to AI contracts that provide fixed, recurring revenue with 80% to 90% operating margins. What will matter is if the market is willing to re-rate these stocks based on Big Tech being the collateral backing them as we are seeing about $3 billion or more in convertible notes and long-term debt in some of these names with very little revenue (yet).

The debt plays a big part as to why Bitcoin Miners go in and out of fashion, but underneath the debt is execution risk. We will often see large revenue targets offered by the management teams, yet the market is essentially saying – we need more evidence you can deliver what you say you will.

In terms of how we plan to play this, not much has changed in terms of the risk profile of Miners and our overall investment strategy:

“Right now, we prefer to stay as close to the hyperscaler deals as possible when evaluating Bitcoin Miners. The reason for this is that it solves the pain point of having a company with deep pockets back-stop the leases, which in turn, improves creditworthiness and credit terms. As many of you are aware, our ethos is to participate in the upside while protecting to the downside. We want the best of both worlds, and in a highly speculative momentum play like Bitcoin Miners pivoting to AI data center infrastructure, the primary goal is to reduce risk.” -September 2025 Discovery Analysis on Bitcoin MinerSeptember 2025 Discovery Analysis on Bitcoin Miner

Top 15 AI Stocks List

Section 1: AI Accelerator Stocks

Broadcom: Strong Contender for First Place

Broadcom guided to $22 billion in FQ2 revenue up 47% YoY and adjusted EBITDA at 68% of revenue. Within that, management guided semiconductor revenue to $14.8 billion, up 76% YoY, and AI revenue to $10.7 billion, up 140% YoY, indicating an acceleration from Q1.

The most explosive comment was this: “Today, in fact, we have line of sight to achieve AI revenue from chips, just chips in excess of $100 billion in 2027. We have also secured the supply chain required to achieve this.”

Management characterized this demand as being driven by a small number of hyperscalers and frontier model builders, with both training and inference contributing as those customers will soon productize their LLM platforms. Within discussing the impressive customer list, the CEO of Broadcom hinted toward 2027 being significantly higher than $100 billion – plus another analyst did math that would show a sharp inflection in 2028 due to OpenAI’s incoming GWs.

In our last Quarterly write-up, it was stated that Morgan Stanley now expects 5 million TPUs to be shipped in 2027, a 67% rise from its prior estimate for 3 million; for 2028, the firm estimates shipments as high as 7 million, a 120% increase from its prior estimate. This would project YoY growth of 40% from 2027 to 2028, a substantial increase from 6% previously, and will represent more than 2X growth in two years.

More recently, Hong Kong-based GF Securities stated that they now expect total TPU shipments to be 4.5 million/7.9 million units in 2026E/2027E, up from previous estimates of 4.5 million/6 million. The upward revision is primarily driven by external sales. For Broadcom, they expect its TPUs to be 4.1 million/5.8 million for 2026E/2027E.

We had stated the estimates provided in the Thematic section were a bit aggressive, yet rather it lands at 6 million or higher for Broadcom in FY2027, the direction is firmly up. Even with MediaTek potentially taking some TPU business on the inference side, Broadcom is in pole position across many hyperscaler customers.

Revenue:

Broadcom’s FQ1 ending January 2026 revenue grew by 29.5% YoY and 7.2% QoQ to $19.3 billion, beating estimates by 0.9%. Revenue growth accelerated by 1.3 percentage points from 28.2% growth in the previous quarter.

Management provided a strong FQ2 guide of $22 billion, implying a YoY growth of 46.6% and 13.9% QoQ, beating estimates by 7.8%.

The expected strong growth is primarily driven by AI revenue, which is expected to grow 140% YoY and 27% QoQ to $10.7 billion. Analysts expect strong revenue growth to continue, with FQ3 revenue expected to grow 81.8% YoY $29 billion and 87.5% YoY to $33.8 billion in FQ4.

AI Revenue:

AI revenue was at $8.4 billion this quarter and is guided to $10.7 billion next quarter for a run rate of about $43 billion. On the surface, the guide doesn’t look like much and would imply a deceleration given AI is growing at a rate of 140% YoY and 27% QoQ – whereas this is effectively saying Broadcom will double in 7-8 quarters.

However, the easy-to-miss details on the guide is that the $100 billion is only for silicon and does not include networking. The words “significantly in excess” were also added later to the guide in the following statement during the Q&A portion.

According to the earnings call, networking is about 33% to 40% of AI revenue today: “AI networking revenue grew 60% year-on-year and represented 1/3 of total AI revenue. In Q2, we project AI networking to accelerate a lot more and grow to 40% of total AI revenue.”

If we assume this mix continues on the low end for about 30% mix in AI networking of total AI revenue, then it’s reasonable to assume Broadcom’s AI revenue will be $143 billion with networking of $43 billion (or 30% of $143B). This represents a QoQ growth of 30% for 7-8 quarters – which is an excellent baseline to set.

Earnings:

FQ1 GAAP EPS grew by 31.6% YoY to $1.50. Adjusted EPS grew by 28.1% YoY to $2.05, beating estimates by 1.3%, primarily driven by operating leverage.

Margins:

The company’s adjusted EBITDA margins beat management guidance in FQ1, primarily driven by operating leverage.

Gross profit margin improved by 10 basis points YoY and QoQ to 68.1%. Adjusted gross margin came at 77%, down 210 basis points YoY and 90 basis points QoQ and marginally beat the guidance by 10 basis points.

Operating margin improved by 230 basis points YoY and 260 basis points QoQ to 44.3% primarily driven by operating leverage. The adjusted operating margin was 66.4%, compared to 65.9% in the same period last year and 66.2% in the previous quarter.

FQ1 net income grew by 33.5% YoY to $7.35 billion with a net profit margin of 38.1% compared to 36.9% in the same period last year.

FQ1 adjusted EBITDA grew by 30.2% YoY to $13.1 billion with an adjusted EBITDA margin of 68% and was better than the management guidance of 67%.

Cash:

Broadcom’s cash flows are improving, driven by higher profits.

FQ1 operating cash flows grew by 35.1% YoY to $8.26 billion with an operating cash flow margin of 42.8% compared to 41% in the same period last year.

FQ1 free cash flows grew by 33.2% YoY to $8.01 billion with a free cash flow margin of 41.5% compared to 40.3% in the same period last year.

Cash was $14.2 billion at the end of FQ1 with debt of $66.1 billion compared to cash of $16.2 billion and debt of $65.1 billion at the end of FQ4. The company repurchased shares worth $7.85 billion and paid dividends of $3.1 billion in the recent quarter.

Valuation:

Broadcom trades at a forward P/S ratio of 16.9. The company traded at a minimum forward P/S ratio of 6.7 and the maximum of 28.8 in recent years. Broadcom is currently trading around the mid-range. On the bottom line, it is trading at a forward P/E ratio of 32.6. The company traded at a minimum forward P/E ratio of 17.3 and a maximum of 57.2. Broadcom is trading slightly lower than the mid-range on the forward P/E ratio.

Notable Risks:

Broadcom’s debt load has increased following past acquisitions, which adds balance-sheet risk. That said, the company has a strong track record of deleveraging and generates substantial cash flow, which helps offset this concern.

Google is deliberately diversifying away from depending solely on Broadcom, giving itself more leverage on pricing and supply chain resilience. MediaTek is a clear winner in this shift, but Broadcom retains a meaningful role in the core TPU architecture for now, and Broadcom is also growing in importance with other hyperscalers such as Meta.

Arm Stock Could Win as Agentic AI Shifts the Bottleneck to CPUs

Arm unveiled an AGI CPU last month to address one of AI’s biggest bottlenecks, which is orchestration. During the chatbot craze of 2023-2025, GPUs did most of the heavy lifting while CPUs had become an afterthought. Yet with agentic workloads, which is perhaps the single largest catalyst on the horizon for the AI trade in 2026 and beyond, the importance of CPUs is set to increase.

In agentic workflows, the GPU still handles inference, but between each inference call, the CPU is doing the orchestration – which are best described as handling tool calls, API requests and memory tasks. AI agents are surfacing this new constraint, which is how to prevent latency and underutilized GPUs following the exponential growth of orchestration needs.

For investors, what matters is that CPUs account for 50% to 90% of total latency in workflows, which means the CPU-to-GPU ratio in AI clusters will need to increase. Earlier this year, both AMD and Intel saw analyst upgrades based on the outstripped supply of CPUs leading to higher average sales prices of roughly 10% to 15%. Reuters also reported that Intel’s unfulfilled orders are reaching longer than six months while AMD delivery times are believed to be eight to 10 weeks.

Regarding how Arm fits in, the company’s expertise in lowering power requirements could matter more than the market expects. After years of supplying the architecture IP behind other companies’ CPUs, Arm is preparing to directly compete with its customers and x86 CPU competitors by transitioning to a chip designer themselves. This comes during a time when CPU cores are expected to go up 4X from 30 million CPU cores per gigawatt to 120 million CPU cores per GW.

Revenue:

Q3 FY2026 ending December revenue was up 26.1% YoY and 9.4% QoQ to $1.242 billion, representing a record quarter for revenue and exceeding $1 billion for the fourth consecutive quarter.

Key Advantages of Arm’s ‘AGI CPU’ for Agentic AI Workloads

Arm also marked its long-awaited foray into physical chip development with its ‘AGI CPU’, launched at its Arm Everywhere event last month. The company’s pivot into physical CPU and rack development is one the AI industry will watch with great anticipation given Arm’s history of owning significant IP in the mobile space combined with the company setting out to solve agentic AI’s orchestration challenges.

Leveraging Arm’s history of delivering high performance with low power requirements for mobile devices, the new AGI CPU is designed to offer a similar balance between high performance and low power consumption.

The AGI CPU was co-developed with key partner Meta, the chip’s first customer, who revealed they turned to Arm almost two-and-a-half years ago to see if there was a CPU option that fit Meta’s needs: “put in a lot more cores per watt, but we do not want to compromise on the performance piece.” Meta had only been finding options satisfying one of the two criteria: meeting the performance but with too much power, or meeting the power but with too little performance.

Margins:

Arm has a profitable business model that constitutes licensing revenue and royalty revenue. The company reported a strong gross margin of 97.6% in Q3 FY2026 ending December.

Arm reported a GAAP operating margin of 14.9% and an adjusted operating margin of 40.7% in the recent quarter. The difference between adjusted operating margin and GAAP operating margin is that the company is a recent IPO and has high stock-based compensation of $285 million or 23% of revenue.

Cash:

The company’s cash flows have been lumpy due to high working capital and high capex to support the long-term growth. However, with the expected strong future profit growth, the cash flows should improve. The company also has a strong balance sheet with cash & short-term investments of $3.54 billion and no debt.

Valuation:

Arm is currently trading at a P/S ratio of 37.1 and a forward P/S ratio of 29.1. The company is trading significantly higher than its other semiconductor peers like Broadcom’s forward P/S ratio of 16.9 and Nvidia’s forward P/S ratio of 12.4.

The company’s revenue growth is expected to accelerate in the next five years compared to the previous period. The company’s revenue CAGR has been 19.3% from FY2021 to FY2026E. Analysts expect revenue to grow at a CAGR of 34% from FY2026E to FY2031E and will be even higher at 38.5% if we use the $25 billion management guidance. However, when looking at the AI segment of many semiconductor peers, the growth rate does not stand out, per se, to justify the high valuation. Rather, the consistency of licensing and royalties' revenue does stand out, and this recurring revenue will create a nice baseline when you combine higher growth from their merchant CPUs.

Notable Risks:

The company’s cash flows have been lumpy due to high working capital and high capex to support the long-term growth.

AMD: Underestimated and Largely Misunderstood

About 18 months ago, I spelled out AMD could outpace Nvidia’s returns by 2030 stating in a Real Vision video interview that the company’s opportunity is closely tied to the inference market.

The overall thesis is that the data center GPU market desperately needs a second-place contender. Investors may appreciate Nvidia’s pricing power, but hyperscalers and companies like OpenAI do not; they’d like to see more competition and optionality including lower prices. That is why we are seeing Meta work alongside AMD to bring Helios to market and a recent 6GW deal from OpenAI.

One key area where Helios stands out is memory — the platform offers roughly 50% more total memory capacity compared to Nvidia’s Vera Rubin rack architecture. AMD will offer 1.4 PB/s of memory bandwidth, slightly below Rubin’s 1.6 PB/s as Nvidia is said to be requiring pin speeds of 11 Gb/s, above the standard 8 Gb/s, driving the higher bandwidth despite lower HBM content. The HBM content and nearly comparable bandwidth will likely make AMD a compelling solution for inference workloads considering its price-advantage over Nvidia.

Buried in the most recent earnings call was a rather strong statement for this otherwise-conservative management team that AMD is “well positioned” to grow data center revenue by more than 60% annually over a 3-5 year time frame:

“With the launch of MI400 series and Helios representing a major inflection point for the business, as we deliver leadership performance and TCO at the chip compute tray and rack level. Based on the strength of our EPYC and Instinct road maps, we are well positioned to grow data center segment revenue by more than 60% annually over the next 3 to 5 years, and scale our AI business to tens of billions in annual revenue in 2027.”

Given the strength of the comment, an analyst asked about the comment on the call and if the 60% applies to 2026 with management replying this is certainly possible:

“We're not obviously guiding specifically by segment, but the long-term target of, let's call it, greater than 60% is certainly possible in 2026.”

Per my last earnings writeup: “AMD Q3: The Catalyst is Expected in H2 2026," which stated, “AMD is a stock where I’ve been intentional about managing expectations. The upside is compelling — as the second place in data center GPUs is wide open. Yet for those who have followed our coverage, the timing has always been key: meaningful execution in AI accelerators is not expected to materialize until the second half of 2026. In other words, the long-term opportunity is substantial, but patience remains part of the thesis.”

Revenue:

AMD’s Q4 revenue grew by 34.1% YoY and 11.1% QoQ to $10.27 billion, beating estimates by 6.2%. However, the company’s revenue this quarter included approximately $390 million from MI308 sales to China and excluding this revenue since it was not included in the guidance would yield only a 2.2% beat, the smallest in the last four quarters.

Management guided Q1 revenue of $9.8 billion at the midpoint, implying a YoY growth of 31.8% YoY and down (4.6%) QoQ and the guidance includes about $100 million of MI308 chip sales to China.

AI Revenue:

The company’s Data Center segment revenue grew by 39% YoY and 24% QoQ to a record $5.4 billion, led by accelerating Instinct MI350 Series GPU deployments and server share gains. However, it included MI308 chips sales to China, otherwise, would be only 29% YoY and 15% QoQ growth. MI450 ramp is expected in the second half of the year, particularly in Q4. The company remains on track to launch its MI500 chips in 2027.

Earnings:

The company’s Q4 adjusted EPS grew by 40.4% YoY to $1.53 primarily driven by operating leverage, beating estimates by 16%.

Analysts expect Q1 adjusted EPS to grow 32.7% YoY to $1.27 and 195.7% YoY to $1.42 in Q2 2026.

Margins:

The company’s profits are growing. However, near term margins are negatively impacted by higher operating expenses to support strong future AI opportunities. Management expects margins to improve by the end of Q4 due to favorable product mix, particularly the ramp of MI450 chips.

Q4 gross profits grew by 44% YoY and 17% QoQ to $5.58 billion. Adjusted gross profits grew by 41% YoY and 17% QoQ to $5.86 billion. Excluding the inventory reserve release and MI308 revenue from China, gross margin would have been 55%, up 100 basis points YoY and QoQ. Management has guided 55% adjusted gross margin in Q1.

Operating margin improved by 600 basis points YoY and 300 basis points QoQ to 17%. Adjusted operating margin improved by 200 basis points YoY and 400 basis points QoQ to 28%. Management has guided an adjusted operating margin of 24% in Q1. The company’s near-term margins are negatively impacted by higher operating expenses to support strong future AI opportunities.

Cash:

Q4 operating cash flow grew by 77% YoY to $2.3 billion with an operating cash flow margin of 22%, up 500 basis points YoY and 300 basis points QoQ.

Q4 free cash flow grew by 91% YoY to $2.1 billion with a free cash flow margin of 20%, up 600 basis points YoY and 300 basis points QoQ.

The company has cash and short-term investments of $10.5 billion, up from $7.24 billion in Q3. While debt remained the same at $3.22 billion.

Valuation:

AMD is trading at a forward P/S ratio of 8.6. The company has traded at a minimum of 3.7 and a maximum of 13.3 in recent years. AMD is currently trading at mid-range. On the bottom-line, it is trading at a forward P/E ratio of 36.6. The company has traded at a minimum of 19.7 and a maximum of 66.4 in recent years. AMD is trading slightly lower than the mid-range on a forward P/E ratio.

Notable Risks:

AMD faces constraints around packaging capacity, particularly around CoWoS, where industry constraints can limit how quickly advanced AI accelerators are brought to market. There is also execution risk, as AMD must take on Nvidia. In addition, AMD’s AI mix may carry lower margins than investors prefer, especially as the company competes aggressively on price and invests to gain share.

Lastly, Arm-based CPUs present a competitive risk in the server market, as hyperscalers continue exploring alternative architectures that could pressure x86 share over time.

Nvidia: Seeking to Defend its Throne

Inventories increased more than 8% QoQ to $21.4 billion, but more importantly, Nvidia’s supply related commitments surged. We highlighted this last quarter as a key sign that the strong data center QoQ revenue inflection would continue.

In Q4, Nvidia’s supply-related commitments surged nearly 90% sequentially to $95.2 billion, a major step-up from the prior ~$28-30 billion range through late FY25 and the first half of FY26. Nvidia says it is strategically securing inventory and capacity to meet demand beyond the next several quarters, which we believe serves as a key sign that the current accelerated QoQ data center growth of ~$10 billion will likely persist as Blackwell Ultra continues ramping and as Vera Rubin ramps.

While initially, this could be taken as evidence that Blackwell’s ramp is persisting; the more likely outcome now is that it signals a Rubin delay. If this is true, the risk is that it sits on the balance sheet until Rubin ships. However, the more likely scenario is that most of these commitments could be converted to Blackwell and Blackwell Ultra orders.

TrendForce data supports this theory, stating that industry watchers expect Rubin to account for 22 percent of Nvidia’s high-end GPUs, down from 29 percent. As stated in our Thematic section, the reason stated is: “time required to validate the newer HBM4 memory used by the chips, challenges with the migration to Nvidia's faster ConnectX-9 NICs, the system's higher overall power consumption, and the more advanced liquid cooling requirements as contributing to the delays.”

In the same article, the stated assumption is that Blackwell mix rises to 71% while Hopper is down to 7% from original expectations of 10% due to China tensions.

According to additional checks, this is aligned with Keybanc, stating 2026 supply is expected to support "5.5M-6M Blackwell GPUs, 1.5M Rubin, and 1M Hopper GPUs.” KeyBanc’s estimates imply higher Hopper revenue – which is what could sting slightly – as these numbers would make up roughly 69% to 71% of Nvidia’s 2026 GPU output, while Rubin accounts for about 18% to 19% and Hopper about 12%. Keybanc also cut VR rack estimates by 50% to 6K, down from 12-14K.

Overall Revenue Growth:

Nvidia’s Q4 revenue accelerated to 73.2% YoY from 62.5% YoY in Q3, while QoQ growth moderated slightly to 20% QoQ from 22% in Q3, due to Nvidia’s increasing revenue base. Revenue for the quarter was $68.13 billion, beating estimates by 2.9%.

For Q1, Nvidia guided revenue growth to accelerate further to 77% YoY, forecasting revenue to be $78 billion, +/- 2%, coming in well ahead of consensus for $72.03 billion.

Sequential growth would again moderate to 14.5% QoQ at the midpoint of guidance, though again this is partly due to the law of large numbers as dollar growth is projected to be nearly $10 billion QoQ, versus $11.1 billion in Q4.

AI Segment Growth:

Data Center revenue in the quarter was $62.31 billion, with YoY growth accelerating nine points to 75% YoY although QoQ growth moderated 3 points to 22% QoQ, due to the larger revenue base. This compares to 25% QoQ growth last quarter, marking two strong back-to-back quarters from Blackwell Ultra shipping in volume.

Within Data Center, Compute revenue rose 58% YoY and 19% QoQ to $51.33 billion, slowing from 27% QoQ in Q3 though YoY growth accelerated 2 points.

Networking revenue was once again quite an outlier in Q4’s report, with growth accelerating sharply on both a YoY and QoQ basis in the quarter. Networking revenue was $10.98 billion in Q4, up 34% QoQ and 263% YoY – this represents more than a 100 point acceleration from 162% YoY growth in Q3, while QoQ growth accelerated 21 points. Nvidia said the strong growth stemmed from the introduction and ramp of NVLink compute fabric for both GB200 and GB300 systems, as well as growth in Ethernet, InfiniBand and Spectrum-X.

On the call, it was stated that Nvidia is likely the largest Ethernet company in the world.

Earnings:

GAAP EPS saw a rather large beat in Q4, coming in at $1.76, up 98% YoY and beating estimates for $1.47 by more than 19%.

Adjusted EPS was $1.62, up 82% YoY and beating estimates by just over 5%. Growth accelerated from 60.5% in Q3 and marked Nvidia’s fastest adjusted EPS growth in the last five quarters.

Margins:

Nvidia’s gross margins moved higher in Q4 to the 75% range, with GAAP operating margin following this expansion and moving back to the 65% level. To note, starting in Q1, Nvidia’s adjusted margin figures will include SBC.

Q4 GAAP gross margin was 75%, slightly ahead of management’s guidance for 74.8% and expanding by 2 points YoY and 1.6 points QoQ, with the sequential expansion driven by Blackwell and better product mix.

Q4 GAAP operating margin was 65%, also slightly ahead of guidance for 64.5%, and expanding 3.9 points YoY and 1.8 points QoQ, showing a hint of operating leverage. For Q1, Nvidia guided for operating margins to be flat at 65% and since the adjusted margin figures will include SBC, it will be lower sequentially at 65.4%.

Q4 GAAP net margin was 63.1%, expanding 6.9 points YoY and 7.1 points QoQ, while adjusted net margin was 57.2%, up 1.1 points YoY and 1.5 points QoQ.

Cash:

Cash flows were robust in Q4, with cash flow margins improving significantly on both a YoY and QoQ basis. Operating cash flow was $36.2 billion in Q4 for a 53.1% margin, up 10.9 points YoY and 11.4 points QoQ.

Free cash flow was $34.9 billion for a 51.2% margin, up 11.7 points YoY and 12.4 points QoQ. Cash and equivalents totaled $62.6 billion, while debt was $8.47 billion.

Valuation:

Nvidia trades at a forward P/S ratio of 12.4. The company has traded at a minimum forward P/S ratio of 10.8 and a maximum of 28.3 in recent years. Nvidia is currently trading significantly lower than mid-range. On the bottom line, it trades at a forward P/E ratio of 22.7. Nvidia has traded at a minimum forward P/E ratio of 19.9 and a maximum of 50.6 in recent years. Nvidia is currently trading significantly lower than mid-range.

Notable Risks:

Net-net on the Rubin delay: Given Blackwell backfill, revenue may not be heavily impacted yet the optics around the delay could lead to more diversification into custom programs and AMD GPUs. Rubin systems go for a higher average sales price, yet the bigger issue isn’t losing the markup in the near-term but rather: 1) is the delay truly only one quarter (we’ve been here before and the delay was longer) and 2) Nvidia’s product road map is not seen as invincible. If you recall, I stated the product road map is the second line of defense should the CUDA moat be breached.

Our catalysts to the $20 trillion thesis remain – which is a strong product road map, analyst estimates being far too low in the 2028-2030 window, but even more importantly, my prediction is that Nvidia exits the decade as one of the largest AI software companies. We saw how quickly the company took over Broadcom as the largest Ethernet companies; something similar is what my $20 trillion thesis hinges on, but in robotics and automation.

TSMC: The Importance of CoWoS Capacity

The main challenge for AMD and its data center growth boils down to capacity at TSMC on the CoWoS side. Not only does CoWoS capacity remain tight, but Nvidia is locking in a majority of TSMC’s capacity, leaving AMD, Broadcom, Google, and others to fight for its scraps. For example, analysts from KeyBanc estimate that Nvidia has secured ~650K wafers in 2026, up 76% YoY, whereas AMD’s 2026 allocation is estimated to be 80K, up barely 14% YoY.

Other reports suggest Nvidia’s allocation is around ~595K and AMD at 105K in total, with 80K at TSMC and the rest at other OSATs; regardless of the exact split, the fact is that AMD’s CoWoS allocations are a fraction of Nvidia’s this year.

To put this in perspective with percentages, TSMC is expected to ramp CoWoS capacity from ~75-80K per month at the end of 2025 to ~130K per month by the end of 2026, so it’s likely that its current capacity is closing in on the ~100K per month level. Thus, Nvidia would be locking up more than 50% of current supply at 650K, with AMD getting less than 7%.

This headwind may ease come 2027, with AMD’s allocation projected to rise as much as 70% YoY, per KeyBanc, taking its CoWoS wafers to ~136K, supporting higher GPU volumes and thus revenues. On the other hand, KeyBanc estimates Nvidia’s allocation to rise to 840K in 2027, still more than 6X AMD’s.

Revenue:

Q1 revenue grew by 40.6% YoY and 6.4% QoQ to $35.9 billion, beating the mid-point guidance by 2%, primarily driven by strong AI demand.

Management guided Q2 revenue of $39 billion to $40.2 billion, implying a YoY growth of 31.7% and 10.3% QoQ.

AI Revenue:

HPC revenue increased 20% QoQ in NT$ to account for 61% of the Q1 revenue.

Management mentioned that AI-related demand is robust and increased the company’s full year total revenue guidance to above 30% growth in U.S. dollar terms from the earlier close to 30% provided during Q4 earnings.

Margins:

TSMC’s ability to generate exceptionally strong profits showcases that the company is one of the best-managed companies in the world. Despite the rising inflation, tariff concerns, technological advancement, trade wars, overseas fab expansion, and geopolitical tensions, TSMC has overcome these challenges by continuing to generate superior profits. Margins continue to expand due to cost controls, higher capacity utilization rates, economies of scale, and better price negotiation with customers and suppliers.

Q1 gross margin was 66.2%, up 7.4 percentage points YoY and 3.9 percentage points QoQ primarily due to cost improvement efforts and better capacity utilization rate.

Q1 operating margin improved by 9.6 percentage points YoY and 4.1 percentage points QoQ to 58.1% primarily due to operating leverage.

Q1 net profit margin improved by 7.4 percentage points YoY and 2.2 percentage points QoQ to 50.5%.

Earnings:

Q1 GAAP EPS grew by 64.6% YoY to $3.49, beating estimates by 3.2%.

Cash:

Q1 operating cash flow was $22.1 billion or 61.6% of revenue compared to $19 billion or 74.5% of revenue in the same period last year.

Q1 free cash flow was $11 billion or 30.7% of revenue compared to $9.0 billion or 35.1% of revenue in the same period last year.

The company had cash & marketable securities of $105.5 billion and debt of $31.7 billion.

Valuation:

TSMC trades at a forward P/S ratio of 11.5. The company has traded at a minimum forward P/S ratio of 5.9 and a maximum of 13.4 in recent years. TSMC is currently trading slightly higher than mid-range. On the bottom line, it trades at a forward P/E ratio of 23.2. TSMC has traded at a minimum of 13.5 and a maximum of 29.6. TSMC is currently trading around the mid-range on the bottom line.

Notable Risks:

Geopolitical concerns.

Memory Stocks:

Micron: Doors. Blown. Off.

As someone who looks at hundreds of earnings reports a year, there are times an earnings report shatters expectations like an Olympian breaking a record or an athlete leaving no doubt who is the best in the game. Micron did this by dropping an earnings report so strong on fundamentals that I cannot recollect seeing one quite like this.

Micron blew the doors off with revenue growth of 196.3% YoY and up 75% QoQ for a beat of 22.3% on a massive revenue base of about $24 billion a quarter. The forward fiscal Q3 growth is eye-watering at 260.2% YoY and 40.4% QoQ. This is nearly 100 points higher than what analysts had slated for fiscal Q3 with consensus at 150.2% growth YoY.

The $10.2 billion sequential increase is nearly unprecedented outside of Nvidia’s most recent quarter posting $11 billion QoQ growth – yet, let’s not forget that Nvidia is the world’s most valuable company.

Here is what management stated about this record-breaking quarter:

“Quarterly revenue nearly tripled versus one year ago, and revenue for DRAM, NAND, HBM (high-bandwidth memory) and each business unit reached new highs. Our fiscal Q3 single quarter revenue guidance exceeds the full year revenue for every year in our company’s history through fiscal 2024. For fiscal Q3, we anticipate exceptional records across revenue, gross margin, EPS and free cash flow.”

To also help illustrate just how impressive this earnings report was, consider that Micron was not supposed to see $33 billion in a single quarter until FQ1 2028 (November of 2027) yet following a second quarter of $10B sequential growth, will now see this revenue in the quarter ending in May of 2026.

As incredible as the revenue growth is; the margins are arguably even more incredible at an 81% gross margin and 76% operating margin guide for the next quarter.

So, why would the market sell the report after hours? Well, to be prudent, Micron was reporting a steep, negative gross margin of (9%) in FY2023 with one quarter as low as (32.7%) in FY23. Thus, the question of whether we are seeing a cyclical top or a structural shift in memory is a very valuable question to answer, and the importance of this broader question is only further reinforced by the results we saw this past quarter.

The difference between the AI cycle and the cyclical peaks in the past is that Micron is combining record fundamentals with improving visibility through multi-year customer agreements and a strengthening product roadmap (HBM4/HBM4E, 1γ DRAM, Gen6 SSDs).

Management repeatedly stated the market is supply constrained beyond 2026, with new fabs coming online in 2028. Meanwhile, longer context windows, reasoning, and agentic workloads will keep HBM and DRAM demand elevated. NAND is proving it's no longer an afterthought with historic pricing surges that are causing heavyweight customers to seek more stability with SCA agreements.

While I do believe SCAs could be the reason for softer price action, it’s my conclusion at this time that memory remains an important strategic asset that results in Micron being in the driver’s seat during a sustained upward trend, albeit with the occasional lumpiness inherent to supply chains. In that sense, I foresee Micron becoming more secular than the market has historically treated it.

Revenue:

Micron’s Q2 FY2026 ending February revenue grew by an impressive 196.3% YoY and 74.9% QoQ to a record $23.9 billion, beating estimates by a solid 22.3%. Revenue growth accelerated by nearly 140 percentage points from 56.7% YoY and 20.6% QoQ growth in the previous quarter. The $10.2 billion sequential increase was the largest in the company’s history and was primarily driven by strong AI memory demand.

Management also provided a strong FQ3 revenue guidance of $33.5 billion, implying a YoY growth of 260.2% and 40.4% QoQ. The revenue guidance beat consensus estimates by a stellar 44%.

AI Revenue:

Combined CMBU and CDBU FQ2 revenue QoQ growth was 75% and calculating using the similar mix in FQ2 implies 40% QoQ guide in FQ3.

Micron’s Cloud Memory Business Unit (CMBU) FQ2 revenue grew by 163% YoY and 47% QoQ to a record $7.75 billion. Revenue growth accelerated by 63 percentage points from 100% YoY growth and 16% QoQ growth in the previous quarter. The strong sequential growth was primarily driven by an increase in prices and favorable mix.

Core Data Center Business Unit (CDBU) FQ2 revenue grew by 211% YoY and 139% QoQ to a record $5.69 billion. Revenue growth accelerated sharply from 4% YoY and 51% QoQ growth in the previous quarter. The strong sequential growth was primarily driven by higher pricing and growth in bit shipments.

Earnings:

Micron’s FQ2 GAAP EPS grew by 756% YoY to $12.07, beating estimates by 36.3%. Adjusted EPS grew by 682.1% YoY to $12.20, beating estimates by 36%, primarily driven by higher memory prices, cost controls, favorable revenue mix, and operating leverage.

Management also provided a strong guide for the next quarter. GAAP EPS guide is $18.90, implying a YoY growth of 1025%. While the adjusted EPS guide is $19.15, implying a YoY growth of 902.6% YoY, beating estimates by 77.8

Margins:

Micron’s margins are gravity-defying.

FQ2 gross profits grew by 499.2% YoY to $17.76 billion. Gross profit margin was 74.4%, an improvement of 37.6 percentage points YoY and up 18.4 percentage points sequentially. It beat the management guidance of 67%. The adjusted gross margin improved by 37 percentage points YoY and 18.1 percentage points sequentially to 74.9%. The strong gross margin was driven primarily by higher pricing, favorable mix, and cost controls.

Management has guided further improvement of gross margin to 81% in the next quarter.

FQ2 operating profits grew by 810% YoY to $16.14 billion. Operating margin came at 67.6%, an improvement of 45.6 percentage points YoY and 22.6 percentage points sequentially. It beat the management guidance of 58.7%.

The adjusted operating margin improved by 44.1 percentage points YoY and 22 percentage points sequentially to 69% driven by operating leverage. Management has guided further improvement of operating margin to 76.2% and adjusted operating margin to 76.8% in the next quarter.

FQ2 net income was $13.79 billion or 57.8% of revenue compared to $1.58 billion or 19.7% of revenue in the same period last year. Adjusted net income was $14.02 billion or 58.8% of revenue compared to $1.78 billion or 22.1% of revenue in the same period last year.

Cash:

Micron’s strong profits are leading to higher cash flows.

FQ2 operating cash flows grew by 202% YoY to $11.9 billion with an operating cash flow margin of 49.9% compared to 49% in the same period last year.

FQ2 adjusted free cash flows grew by 705% YoY to $6.9 billion with an adjusted free cash flow margin of 28.9% compared to 10.6% in the same period last year.

Capex grew by 61.3% YoY to $5.0 billion. For FQ3, management has guided a capex of $7.0 billion and expects adjusted free cash flows to roughly double sequentially.

Cash and investments were $16.6 billion and debt of $10.14 billion compared to $12.02 billion and $11.76 billion in the previous quarter. Micron repurchased shares worth $350 million and also reduced debt by $1.6 billion in the recent quarter.

Valuation:

Micron trades at a forward P/S ratio of 4.3. The company has traded at a minimum forward P/S ratio of 1.2 and a maximum of 6.8 in recent years. Micron is currently trading slightly above the mid-range. On the bottom-line, the company is trading at a reasonable forward P/E ratio of 7.2 due to the strong margin expansion and expected adjusted EPS growth of 597% to $57.8 for FY2026.

Notable Risks:

Memory can be stubbornly cyclical, and the market appears to be discounting the familiar pattern Micron has faced in past cycles where peak shipments were followed by a sharp reversal ahead of pricing and demand normalizing.

Management commentary supports Micron being in a sustained uptrend as 2026 is supply-constrained and greatly limited by DRAM and NAND supply. However, despite the outsized demand and strong product road map, Micron will likely see peak sales before Nvidia’s Vera Rubin sees peak sales given HBM and data center DRAM sits earlier in the supply chain. Therefore, there can be air pockets tied to Nvidia’s GPUs shipping in volume even when the overall trend remains intact.

Micron is also exposed to PC/consumer and traditional server revenue.

SanDisk: A Thing in Motion …

SanDisk’s second quarter report was a blowout on all accords, with the company reporting an impressive 31% QoQ growth for revenue to $3.03 billion and a tremendous 408% QoQ growth to $6.20 in adjusted EPS, capitalizing on strong demand and strong pricing from undersupply dynamics.

However, the guide was even more impressive, with SanDisk forecasting $4.4 to $4.8 billion in revenue, up 52% QoQ at midpoint, and adjusted EPS more than doubling QoQ to $12 to $14, roughly 200% above consensus at midpoint.

To put in perspective just how large of a beat this was, SanDisk was not expected to see this level of revenue or EPS at the end of 2027 – consensus for the Dec 2027 quarter was $4.19 billion and $9.29 in EPS heading into this report.

There were a handful of important comments from management in the call regarding the NAND market, that it will be even more undersupplied in fiscal Q3, while data center growth forecasts raised yet again.

SanDisk noted that it was unable to fulfill customer demand in Q2, yet management added that it anticipates “the market to be more undersupplied [in Q3] than it was in the second quarter” with bit growth down mid-single digits QoQ compared to a mid-single digit increase QoQ in Q2.

Management also added that they expect “customer demand well above supply beyond calendar year 2026, which requires careful allocation planning and alignment with our customers.”

This is rather important as analysts were currently expecting NAND pricing to peak in the calendar Q1 quarter on a QoQ basis, yet ASP growth may end up higher for longer considering the supply-demand imbalance is widening.

For example, analysts were projecting NAND ASPs to accelerate to the low-20s to low-30s QoQ in calendar Q1 and then slow to the mid-teens in calendar Q2, yet a widening imbalance could potentially push prices up to 40% QoQ and 20% QoQ, respectively.

This accelerating forecast for data center exabyte growth ties into NAND’s increasing role in AI infrastructure, as we had recently outlined with KV cache requirements and Nvidia’s new inference memory platform. On this exact topic of Nvidia’s KV cache discussion and TB of content per GPU, management explained that “none of that demand is in the numbers we're talking about, demand numbers at this point,” but “our initial looks at it when we look at, let's say, '27 demand, we think that's roughly maybe 75 to 100 additional exabytes. And then a year after that, you can double that. So it is a significant amount of demand.”

For context, 75-100 EB of demand in 2026 would account for roughly 6-8% of the entire flash market, while doubling that to 150-200EB in 2027 would correspond to 10-13% of the market – a significant new demand driver.

As a result of the increasing role of NAND and enterprise SSDs in AI inference applications, and expectations for a “meaningful increase in NAND content per deployment,” management expects data center revenue to “grow meaningfully in both the near and long term.”

However, there is another near and medium-term risk to the SSD story related to the KV cache-optimized tier Nvidia recently proposed with its ICMS platform – Google’s TurboQuant.

As we had discussed in our first SanDisk analysis, SanDisk: Shares Up 559% In 2025 On NAND Flash, Enterprise SSD Tailwinds, the KV cache essentially serves as a model’s long-term memory that is reused and extended throughout many steps or requests. KV cache capacity is a known pain point when working to balance long-context reasoning and memory capacity in inference workloads, as it can consume ~30% of GPU memory during deployment. While TurboQuant directly addresses this pain point by compressing the vectors to reduce KV cache memory size by up to 6X, it likely will not fundamentally alter the architectural needs for NAND and SSDs for storing, caching and retrieving training and inference data. Instead, it will likely help drive KV cache usage lower and enable longer context windows, more concurrent requests and open the door for previously-infeasible memory-constrained workloads to arise.

Revenue:

SanDisk reported $3.03 billion in revenue in Q2, beating estimates by ~12.5%, with SanDisk attributing the growth to higher prices across its three segments with prices strengthening through the quarter.

Revenue growth accelerated more than 38 points to 61.2% YoY, while sequential growth accelerated nearly 10 points from 21.4% QoQ in Q1 to 31.1% QoQ in Q2.

Q3’s guide was a blowout versus consensus, with SanDisk forecasting $4.4 to $4.8 billion in revenue, more than 58% ahead of consensus for just $2.91 billion. This also points to a significant 110 point acceleration to 171.3% YoY at midpoint and 21 points to 52% QoQ.

Estimates for fiscal Q4 points to 219.6% YoY growth to $6.1 billion. For the full year, current consensus points to 116.1% YoY growth to $15.89 billion.

AI Revenue:

SanDisk’s data center revenue growth was robust in Q2 with the company reporting growth of 76% YoY and 64% QoQ to $440 million, accelerating 86 and 38 points respectively. Data center still accounts for a smaller portion of overall revenue at almost 15% in the quarter, though this is up from 12% last quarter.

Management said they are seeing strong adoption of data center products from cloud hyperscalers, enterprise and edge data centers, and system integrators. SanDisk completed qualification of its PCIe Gen5 high-performance TLC SSDs at a second hyperscaler in the quarter, while two major hyperscalers are advancing with qualifications for its BiCS8 QLC ‘Stargate’ products, set to begin shipping in the next several quarters, providing another tailwind for growth.

Earnings:

SanDisk reported a large beat on EPS in Q2, though arguably the Q3 guide could be one of the largest beats in tech, with management forecast Q3 adjusted EPS 200% above consensus estimates.

GAAP EPS was $5.15 in Q2, up 587% QoQ and 615% YoY, and nearly $2 ahead of consensus estimates for $3.20. Adjusted EPS was $6.20, beating the $3.78 estimate by 64% and representing 408% QoQ and 404% YoY growth.

For Q3, management guided for $12 to $14 in adjusted EPS, up 110% QoQ, and coming in 200% above consensus estimates for $4.33 at midpoint.

Margins:

SanDisk saw strong gross margin expansion in Q2 stemming from higher prices, while unit cost reductions served as an operating margin tailwind.

Q2 GAAP gross margin was 50.9%, up 21.1 points QoQ and 18.6 points YoY, while adjusted gross margin was very similar at 51.1%, up 21.2 points QoQ and 18.6 points YoY.

GAAP operating margin was 35.2%, up 27.6 points QoQ and 24.8 points YoY, while adjusted operating margin was 37.5%, up 26.9 points QoQ and 25.1 points YoY.

GAAP net margin was 26.5%, up 21.6 points QoQ and 21 points YoY, and adjusted net margin was 32%, up 24.2 points QoQ and 20.5 points YoY.

For Q3, SanDisk projected margins to expand further, guiding GAAP gross margin to be 64.9% to 66.9%, up 15 points QoQ and 43.4 points YoY at midpoint, while GAAP operating margin was implied to be 54.7% at midpoint, up 19.5 points QoQ.

Adjusted gross margin was guided to be 65% to 67%, with adjusted operating margin guided to be 56% at midpoint.

Cash:

Operating cash flow of $1.02 billion, up ~973% YoY, for a 33.7% margin, up 12.6 points QoQ and 28.6 points YoY; FCF of $980 million and adj FCF of $843 million for a 27.9% margin, up 8.5 points QoQ and 23 points YoY; Cash of $1.539 billion and debt of $603 million

Valuation:

SanDisk’s valuation is somewhat hard to pin down given the company’s limited history on the public markets after its February 2025 spinoff, and its 2,720% rally in the past one year. On the top line, SanDisk is trading at 8.4 forward P/S ratio, having traded as low as 0.6 last August and with an average multiple of 2.1 for its limited public history.

On the bottom line, SanDisk is trading at a 21.5 forward P/E ratio, having traded as low as 1.0 last August with an average of around 9.7.

Notable Risks:

For a stock with this level of top-line and bottom-line growth, the risk is deceleration. While adjusted EPS is expected to surge 1307% in FY2026 and 142.6% in FY2027, expectations call for a 12.8% decline in FY2028.

Quick Note on HDD Stocks:

We’ve covered HDD stocks recently on our Discovery tier.

Hard disk drives (HDDs) offer the lowest-cost per terabyte, which makes HDDs ideal for “big data” storage, backups and large AI datasets. Compare this to solid state drives (SSDs) which store data on flash memory chips and are far faster and lower-latency. SSDs cost more per terabyte, thus leveraging a mix of HDDs and SDDs is a popular choice.

As it stands today, SDDs have illustrated significant pricing power compared to HDDs. Therefore, because HDDs are considered more commoditized in the current market dynamics compared to SDDs, these stocks are being overlooked.

As inference requires more exabytes to be stored, HDDs offer an advantage in that storage tier. In fact, a leading HDD management team sees a CAGR of 25%+ over the next 5 years with HDD representing “80% of the storage media that deployed within a hyperscale environment.” Multimodal datasets are among the largest drivers of incremental storage demand. Video is another data hog and even modest growth here from multimodal AI can create what’s called “data exhaust.”

There are two things to note when looking at HDD stocks. The first is these are bottom-line stories in the current market with growth of 67%+ and even 270%+ last quarter on EPS. The second is that while pricing is fixed for 2026, it comes up for re-negotiation in 2027.

Subscribe to Discovery to unlock the full Top 15 AI Stocks report and get additional insights into the next phase of the AI trade. To subscribe to Discovery with 40% off, click here to email us or email premium@io-fund.com and mention code DISCOVERY40Discovery with 40% off, click here to email usclick here to email us or email premium@io-fund.com and mention code DISCOVERY40

AI Networking Stocks

We covered quite a bit of the shifts in AI networking in our last quarterly report, found here.

Lumentum: Capacity Constrained (and Loving It)

Lumentum is a leading allocation as of January and is up 127% YTD. The company (and cleary the stock too) is benefiting from outsized demand for its EML lasers, reaching a quarterly company record in EML laser shipments. While EMLs are largely spoken for with InP wafer fab capacity fully allocated with long-term agreements, the company is expanding its capacity with additional supply expected to come online in the second half of this calendar year.

The transition to 1.6T is moving faster than management originally anticipated, which contributed to the beat/raise with management stating: “We achieved another quarterly company record in EML laser shipments led by 100 gig line speeds and bolstered by a ramp in 200 gig devices. Simultaneously, we expanded our footprint in next-generation architectures shipping CW lasers for 800 gig manufacturers and increased volumes of ultra-high-power laser shipments for CPO applications.”

There are additional growth levers for Lumentum as we look further out, driven by optical circuit switches and co-packaged optics. Optical circuit switches are beginning to move the needle now with a $400 million backlog, although currently at around $10 million in revenue. In 2027, co-packaged optics (CPOs) will represent another important market for Lumentum alongside UHP chips and ELS modules will help expand the company’s serviceable addressable market.

Management emphasized that indium phosphide wafer fab capacity is fully allocated, with the company indicating they have already delivered half of their expansion target over one quarter alone due to strong customer demand necessitating they pull forward delivery. Thus, the natural question for an investor is whether Lumentum can add more capacity. The company stated they foresee more capacity coming in the second half of the calendar year:

“We are scaling rapidly through precision tool optimization and yield gains. This execution will help to ensure that additional capacity comes online as planned over the next two quarters and beyond. While not able to size it, we now have line of sight to a significant block of additional capacity starting in the second half of 2026 both recurrent activities in Sagamihara and better utilization of our Caswell, United Kingdom and Takao, Japan fabs.”

Although minimal right now, 200G is ramping faster than expected, representing 5% of unit volume yet represents 10% of laser chip revenue. According to management, demand for 200G EMLs is about a quarter faster than they originally anticipated with the goal of ending the year with 25% of unit volume from this new product mix – with these seeing higher average sales prices than the 100-gig.

Management stated the following: “Our 200-gig line speed, as we said, is actually doing a little bit better than we expected. I think on the last call, we had said that the 5% revenue of — 5% of mix would be this quarter. It was a quarter earlier than we had expected, and that's primarily because 1.6T is coming on, I think, faster than we initially anticipated, and that is heavily being driven by 200-gig EMLs.”

This was discussed further in the call with management stating 1.6T was stronger than it was 90 days ago.

Revenue:

Lumentum delivered Q2 revenue at the upper end of its guided range, yet its guidance stands out as it not only points to YoY growth accelerating almost 24 points to 89.3% YoY, but it also was a larger magnitude beat in dollar terms versus last quarter.

Q2 revenue was $665.5 million, a modest 2% beat to estimates and in the upper end of Lumentum’s guidance for $630-$670 million. Revenue growth accelerated 7.1 points to 65.5% YoY, while sequential growth was robust at 24.7% QoQ, its fastest growth in eight years and accelerating 13.7 points.

For Q3, Lumentum guided for revenue between $780 million and $830 million, accelerating 23.8 points to 89.3% YoY at midpoint. Sequential growth will remain strong with guidance pointing to growth of 21% QoQ at midpoint.

What’s impressive here is that Lumentum’s guidance beat consensus by a larger margin than it did last quarter – at the $805 million midpoint, this would be nearly $99 million ahead of the $706.4 million estimate, whereas Q2’s guide for $650 million at midpoint beat by ~$88 million.

Following the report, we had stated: “Considering the scope of this raise for Q3, it’s likely that estimates for Q4, which currently are pegged at just $770.4 million, are revised much higher in the coming days/weeks. As a result, it’s likely that consensus estimates for FY26, currently at $2.64 billion, move ~8-10% higher.”

At time of writing in April, FQ4 estimates were revised up 19.1% since the earnings report for 90.9% YoY growth to $917.8 million. FY2026 revenue estimates are $2.92 billion, up 77.8% YoY and have been revised up by 10.6%.

AI Revenue:

Components revenue was $443.7 million in Q2, up 68.3% YoY and 17% QoQ. YoY growth accelerated 3.4 points while QoQ growth decelerated 1.4 points from last quarter. Components accounted for 66.7% of revenue in Q2, down from 71% in Q2.

Driving this growth were EML shipments, with Lumentum saying both 100G and 200G EMLs reached new company records. Systems revenue rose 43.5% QoQ and 60.1% YoY to $221.8 million, a sharp acceleration from a (3.6%) QoQ decline and 46.5% YoY increase in Q1. This was driven by record cloud transceiver shipments.

EPS:

Q2 GAAP EPS was $0.89, up from just $0.05 in Q1 and beating the $0.50 consensus estimate by 78%. Adjusted EPS was $1.67, up 51.8% QoQ and 297.6% YoY, and beating the $1.40 estimate by 18.4%.

For Q3, Lumentum guided for $2.15 to $2.35 in adjusted EPS, pointing to YoY growth of 294.7% and QoQ growth of 34.7%. At midpoint, this represented a 40.6% beat to the consensus estimate of $1.60.

Margins:

Lumentum reported solid expansion in gross margins in Q2, with GAAP gross margin up 2.1 points QoQ and 11.3 points YoY to 36.1%, and adjusted gross margin up 3.1 points QoQ and 10.2 points YoY to 42.5%.

GAAP operating margin in Q2 was 9.7%, up 8.4 points QoQ and 22.5 points YoY, while adjusted operating margin was 25.2%, up 6.5 points QoQ and 17.3 points YoY (and ahead of guidance for 20-22%).

Lumentum forecast this operating margin to continue at a similar rate, projecting adjusted operating margin of 30-31% in Q3, up 5.3 points QoQ and 19.7 points YoY.

GAAP net margin expanded 11 points QoQ and 26.9 points YoY to 11.8%. Adjusted net margin expanded 5.4 points QoQ and 14.1 points YoY to 21.6%.

Cash:

Operating cash flow of $126.7M for a 19% margin in Q2, up from 6% in the year ago quarter and 10.9% in Q1

FCF of $43.1M for a 6.5% margin, up from (4%) in the year ago quarter and (3.4%) in Q1

Cash and equivalents increased slightly to $1.16 billion while debt was $3.29 billion at the end of Q1. The company recently entered into privately negotiated exchange agreements with certain holders of its 0.50% Convertible Senior Notes due 2026 and 1.50% Convertible Senior Notes due 2029 totaling $474.6 million. The company will issue about 6.3 million of shares in exchange for these notes and will not receive any cash proceeds.

Valuation:

Lumentum trades at a forward P/S ratio of 21. The company traded at a minimum forward P/S ratio of 1.7 and a maximum of 21.9 this month. On the bottom-line, it trades at a forward P/E ratio of 110.5. Lumentum traded at a minimum forward P/E ratio of 11.6 and a maximum of 115.3 this month.

Notable Risks:

Lumentum’s valuation has become more demanding following the stock’s strong move higher, which creates the risk of multiple compression if growth falls short of elevated expectations. The company also carries a relatively high debt load, which adds financial risk and reduces flexibility compared to a cleaner balance sheet.

AAOI: Buckle Up

AAOI grew to become our top position as that’s what a quick 350% return does to a portfolio. We might need to trim back for a more intentional allocation but that does not deter from the carefully placed thesis we put into place months ago.

As you’ll recall last quarter, AOI (Nasdaq: AAOI) missed earnings due to orders getting pushed out to Q4. Therefore, it was quite important that AOI meet expectations following the delay. The company’s revenue grew 34% YoY and 13% QoQ and guided to grow 58% YoY and 17% QoQ for Q1. Of this, data center inflected with growth of 69% YoY and 70% QoQ. Suffice to say, AOI met the bar set for the company with momentum headed into 2026.

During the call, management focused on detailing the ramp for 800G and 1.6T with targets shared through mid-2027. The forecast implies that AOI’s optical attach per unit of compute is rising as network sizes increase to include more lanes and more links. For example, the 800G era is widely expected to require record ports, resulting in higher revenue for optical networking companies. The industry is shifting from 400G to 800G with 1.6T on the roadmap as throughput becomes more critical with the incoming inference phase.

Management offered a forecast for mid-2027 of $378 million per month with the framework of 800G being the bulk of the revenue, 1.6T contributing and some 100G/400G content contributing yet the lowest of the mix. Importantly, management framed this discussion as being capacity-constrained rather than demand-constrained. In the more near-term, management guided for $1 billion in 2026 revenue with $120 million in adjusted operating profit.

The following was stated in the opening remarks:

“Given the recent surge in customer inquiries and apparent rising demand, we believe that by mid-2027, 100G and 400G revenue will be approximately $90 million. 800G revenue will be approximately $217 million and 1.6 terabit revenue will be approximately $71 million monthly. Altogether, this represents $378 million in monthly revenue for transceiver products.”

The company also stated they expect $1 billion in revenue this year compared to analyst estimates that are just shy of $764 million: “Looking more broadly at 2026. While it's still early in the year, we expect to generate over $1 billion in revenue this year, with a non-GAAP operating profit of over $120 million. This revenue level is limited by our production capacity and supply chain, not market demand, which we believe is much larger.”

Analyst estimates greatly missed the mark at $521M per quarter in September of 2027, assuming the $378 million per month plays out ($1.14B per quarter).

Revenue:

Applied Optoelectronics (AOI) Q4 revenue grew by 33.9% YoY and 13.2% QoQ to $134.3 million, beating estimates by 4.7%. The revenue growth was primarily driven by strong data center revenue which grew by 69.2% YoY and 70.4% QoQ to $74.9 million.

During the quarter, the company also announced that they received the fourth 800G volume order from one of their major hyperscale customer to support its AI data center growth, which is likely to be Amazon. AOI has begun ramping up production of this 800G module in anticipation of a strong volume ramp starting in Q2. Management also mentioned in the earnings call that they are in discussion with a new hyperscale customer about qualifying for 800G and 1.6T products and sounded confident about the growth trajectory in both these products with multiple customers.

Management also provided a strong Q1 revenue guide of $150 million to $165 million, implying a YoY growth of 57.7% and 17.3% QoQ at the midpoint. The strong Q1 revenue growth is led by sequential revenue growth in both CATV and data center revenue.

The company’s 2025 revenue grew by a solid 82.8% YoY to $455.7 million. Management expects strong revenue growth to continue in the coming years and guided 2026 revenue of over $1 billion, implying a 119% YoY growth, beating estimates by 31%.

AI Revenue:

The company’s Q4 data center revenue grew by 69.2% YoY and 70.4% QoQ to $74.9 million. The revenue growth sharply accelerated from 7.3% YoY and decline of (1.9%) QoQ in Q3. Revenue of 100G products grew by 54% YoY and 400G products grew by 141% YoY. 100G products accounted for 51% of data center revenue, 200G and 400G transceiver products accounted for 41%, and 8% was from 10G and 40G transceiver products.

EPS:

The company’s Q4 GAAP EPS came at ($0.03), beating estimates by $0.12. While the adjusted EPS came at ($0.01), beating estimates by 91%.

Margins:

The company witnessed a turnaround in margins and expects to be sustainable profitable on an adjusted basis from Q2 driven by the shift to higher margin revenue, operational efficiencies, and leverage.

The company’s Q4 gross profits grew by 46% YoY to $41.95 million. Gross profit margin improved by 250 basis points YoY and 320 basis points QoQ to 31.2%. Adjusted gross margins improved by 250 basis points YoY and 40 basis points sequentially to 31.4%, beating the guidance of 30%. The improvement in gross margins was primarily due to the favorable product mix and cost reduction efforts.

Q4 operating margin was (8.6%) compared to (6.5%) in the same period last year and (15.3%) in the previous quarter. Adjusted operating margin was (5.3%) compared to (2.5%) in the same period last year and (8.7%) in the previous quarter.

Cash:

The company’s cash flows have been weak. However, with improved profitability expected in the coming quarters we could expect cash flows to improve.

Q4 operating cash outflow was ($29.6 million) or (22%) of revenue compared to (24.6%) in the same period last year.

Q4 free cash outflow was ($113.6 million) or (84.6%) of revenue compared to ($53.1 million) or (53%) of revenue in the same period last year. To support the strong expected growth capex grew by 227% YoY to $84 million in Q4.

Cash and short-term investments were $216 million and debt of $197.2 million at the end of Q4 2025. The company also announced an equity offering of $250 million after the announcement of Q4 results.

Valuation:

The company is trading at peak multiples on the top line and the bottom line. The company is trading at a forward P/S ratio of 12.4 and traded at a minimum level of 0.2 in May 2023. On the bottom line, it trades at a forward P/E ratio of 188 and we have limited data here since the company will be profitable on an adjusted basis from Q2 this year.

Notable Risks:

Valuation remains a key risk, as a higher multiple leaves the stock with less room for error if growth or guidance falls short of expectations. The company is also generating negative cash flow, which adds financial risk and can weigh on investor sentiment if profitability takes longer to materialize. Another important risk is that networking supplier dynamics can shift quickly, particularly in AI infrastructure where customer preferences, architectures, and share positions may change faster than expected.

Coherent: Slow and Steady

Coherent is a stock that will test investors as the company has near-perfect positioning, yet the timing is taking longer than what growth investors typically look for. If I had to describe this earnings report, I would use the word “visibility” as the headline numbers will fail to impress, yet I believe the stock price will march upward as the equation of what Coherent offers + where the demand is = will eventually materialize (in 2026).

The data center and communications segment revenue grew by 33% YoY and 11% QoQ in FQ2, accelerating from 26% YoY growth and 7% QoQ growth in FQ1 driven by strong AI demand. The Communications segment grew 44% YoY and 9% QoQ, although this was down from 11% QoQ growth and 55% YoY reported last quarter. However, the data center segment accelerated meaningfully to 14% QoQ and 36% YoY, up from 4% QoQ growth and 23% YoY last quarter. As of this quarter, data center and communications segment represents 70% of revenue.

The company offered strong visibility metrics, such as stating book-to-bill ratio is 4X, meaning they are booking orders 4X faster than they can ship. Much of Coherent’s timing hinges on indium phosphide capacity as the company has been working to increase this capacity by moving from 3-inch wafers to 6-inch wafers, which will produce 4X the amount of chips at half the cost. The words “second half" came up frequently with management emphasizing an incoming inflection: “We expect 1.6T to ramp significantly over the coming quarters, with the early phase of the ramp driven by our EML and silicon photonics-based transceivers, followed by our 200G VCSEL-based 1.6T transceivers ramping in the second half of this calendar year.”

In addition to the transition toward 1.6T being a catalyst, optical circuit switches (OCS) and co-packaged optics (CPO) represent additional catalysts as we move look into 2027. Although in the future, an area where Coherent could stand out is CW lasers for the incoming CPO wave in AI networking. According to management, they secured a large order from a hyperscaler. Management also emphasized their non-mechanical liquid crystal technology for OCS provides an edge, with an update on the call they currently have 10 customers in their pipeline.

Revenue:

Coherent’s FQ2 ending December 2025 revenue grew by 17.5% YoY and 6.6% QoQ to $1.69 billion, beating estimates by 2.7%. On a pro forma basis, excluding revenue from the divested Aerospace and Defense business, which the company sold in FQ1, revenue grew by 9% QoQ and 22% YoY primarily driven by AI Datacenter & Communications demand.

Management guided FQ3 revenue of $1.70 billion to $1.84 billion, implying a YoY growth of 18.2% and 5% QoQ at the midpoint, beating estimates by 3.5%. As per our internal proforma estimate, it implies a YoY growth of 23.8% and 6.3% QoQ in FQ3 after excluding Aerospace and Defense business revenue from the prior year quarter and also the recently sold product division based in Munich. The product business in Munich had averaged $25 million quarterly revenue and had a gross margin well below the company’s corporate gross margin.

Management expects continued strong growth in the second half of fiscal year 2026 and throughout fiscal year 2027 based on strong datacenter and communications demand and the continued production capacity expansion along with improving demand in the Industrial segment.

AI Revenue:

FQ2 data Center segment revenue grew by 36% YoY and 14% QoQ, accelerating from 23% YoY and 4% QoQ growth reported in FQ1. The FQ2 data center revenue growth was driven by growth in both 800 gig and 1.6T transceivers. The company is witnessing very strong AI demand and is also rapidly expanding capacity, and management expects double-digit sequential growth in data center segment in both FQ3 and FQ4.

Management expects revenue growth in the current quarter to be driven by a combination of growth in both 1.6T and 800 gig transceivers as well as growth in the OCS systems. Coherent is witnessing strong demand for the 1.6T transceivers across multiple customers and continue to expect both 800 gig and 1.6T to grow significantly in calendar 2026.

Coherent expects OCS revenue to grow sequentially in the coming quarters as they ramp production capacity as fast as possible to meet the rapidly growing demand. Management estimates over $2 billion of addressable OCS market in the coming years.

EPS:

FQ2 GAAP EPS grew by 72.7% YoY to $0.76, beating estimates by 10.1%. Adjusted EPS grew by 35.8% YoY to $1.29, beating estimates by 7%.

Management has guided adjusted EPS of $1.28 to $1.48 for FQ3, implying a YoY growth of 51.6% at the midpoint and beating estimates by 4.5%.

Margins:

The company’s margins are improving driven by reductions in product costs, manufacturing efficiency gains, and operating leverage.

FQ2 gross profits grew by 22.3% YoY to $622.8 million. Adjusted gross profits grew by 20% YoY to $657.4 million with an adjusted gross margin of 39%, up 80 basis points YoY and 30 basis points sequentially and was in-line with the guide. The improvement in gross margin was driven by reductions in product input costs, efficiency gains from improved cycle times in the manufacturing process, as well as yield improvements. Pricing optimization also continued to contribute meaningfully to the gross margin expansion. The management FQ3 guide is 39.5%.

FQ2 operating income grew by 34.3% YoY to $184 million. Adjusted operating income grew by 26.8% YoY to $336 million with an adjusted operating margin of 19.9%, up 140 basis points YoY and up 40 basis points QoQ and was in-line with the guide. The operating margin improvement was due to operating leverage and operational efficiencies. The management FQ3 guide is 20.9%.

Cash:

Coherent’s balance sheet is beginning to improve, with the company using proceeds from the divestment to pay down debt, though debt to cash remains upside down. Operating cash flow margins were also thin and free cash outflows increased due to high capex to support the strong AI demand.

FQ2 operating cash flow was $57.9 million or 3.4% of revenue, down from $187.4 million in the same period last year and up from $46 million in the previous quarter.

FQ2 free cash outflow was ($95.7 million) or (5.7% of revenue), down from $81.7 million or 5.7% of revenue in the same period last year. FQ2 capex grew by 45.3% YoY to $154 million to support the strong AI demand.

The company had debt of $3.35 billion and cash of $863.7 million at the end of the December quarter.

Valuation:

Coherent trades at a forward P/S ratio of 8.3. The company has traded at a minimum forward P/S ratio of 0.9 in September 2023 and is currently trading at its peak levels. On the bottom line, it trades at a forward P/E ratio of 57.5. Coherent has traded at a minimum of 14.5 in April 2025 and is currently trading at its peak levels on the bottom line too.

Notable Risks:

Coherent carries a relatively high debt load, which adds balance-sheet risk and can pressure the stock if growth or margins fall short of expectations. While the company is beginning to improve its financial profile by using divestment proceeds to pay down debt, leverage remains an important watchpoint. Valuation is another risk, as a stronger stock price leaves less room for error.

Astera Labs: Bouncing off the Lows

Astera Labs has seen a tremendous comeback this year, and although flat YTD, our buy in February (up 40%) puts us in the positive this year.

Astera Labs delivered a solid Q4 beat with revenue up another 17.4% QoQ, though the one point to nitpick from this report was Q1’s softer margin guidance, as it would imply a step down to below the 20% GAAP operating margin level sustained for the last three quarters. In addition, the hypergrowth company is not able to keep up with high comps given sequential growth is expected to be 7.7% QoQ following many quarters of double-digit QoQ growth with some quarters as high as 20%+ sequentially.

There were clues in the call as to when Astera is most likely to see a second wind with Scorpio-X as the catalyst. Overall, Astera has a longer runway than the market is communicating given there is an element of vendor lock-in to their products. Additionally, Ethernet is optimized for reach, whereas Astera specializes in PCIe, which is optimized for something quite different – GPU-to-GPU communication and memory-level workloads inside the rack.

Astera also announced that it entered into a warrant agreement with Amazon, allowing the tech giant to purchase up to 3.26 million shares at $142.82 through February 2033. The warrants will vest in tranches of payments made by Amazon for the purchase of up to $6.5 billion worth of Astera’s smart fabric switch, signal conditioning and optical engine products. The vote of confidence from one of Astera’s major customers is certainly welcomed.

Revenue:

Astera reported Q4 revenue of $270.6 million, topping estimates for $249.6 million by 8.4%. Growth continued to decelerate on both a YoY and QoQ basis, with YoY growth decelerating more than 12 points to 91.8% and QoQ growth by 2.7 points to 17.4%.

For Q1, Astera guided for revenue between $286 to $297 million, more than 12% ahead of estimates for $260.1 million. However, this guidance points to YoY and QoQ growth continuing to decelerate, to 82.9% YoY and 7.7% QoQ. This would represent Astera’s slowest QoQ growth in its public history. As we had covered in detail last quarter, Astera’s higher-ASP Scorpio X-Series product now entered initial production in late January, likely becoming a greater tailwind to growth as its ramp progresses throughout the year.

While there was no specific guidance for 2026, current estimates for $1.36 billion, up 59.1% YoY, and revised higher from $1.18 billion when the company reported its Q4 earnings in February.

AI Revenue:

Scorpio-P contributed 15% of revenue this quarter and it was stated previously that Scorpio-P and Scorpio-X will reach more than 50% of revenue by 2026. The X-Series is highly anticipated as it’s expected to be a much higher ASP product than the P-Series. Management in the past has called the X-Series an “anchor socket” which means it will secure vendor lock-in for Astera and they will be able to add more products, such as modules and silicon level products. Last quarter, management stated: “we expect our overall dollar content opportunity per AI accelerator to significantly increase, representing another step-up from a baseline revenue standpoint.”

The update this quarter is that the X-Series will “incrementally grow revenue in the first half of 2026, followed by a transition to high-volume production in the second half. We continue to make excellent progress with additional engagements looking to leverage PCIe for scale-up networking. As previously communicated, we are engaged with 10-plus customers for Scorpio X family. And our current expectation is that we will ship initial quantities of Scorpio X series to support new customer platforms in the second half of 2026 with volume ramp set for 2027.”

Accounts receivable surged nearly 94% QoQ to $83.2 million, while inventories rose more than 14% QoQ to almost $59 million, both positive signals that revenue growth is likely to remain strong considering the state of demand and hyperscaler capex plans.

EPS:

Astera reported its smallest EPS beat since going public, with its $0.58 in adjusted EPS in Q4 beating the $0.51 estimate by just 13.7%; for comparison, its second-smallest beat was in Q2 2024 at 18.9%, while the prior two quarters saw beats of >25% each. Adjusted EPS growth was 56.8%, decelerating from 113% in Q3.

GAAP EPS was $0.25 in Q4, missing estimates for $0.30, likely due to the sharp net margin contraction related to the income tax provision. GAAP EPS growth was 78.6%.

For Q1, Astera guided for adjusted EPS to be $0.53 to $0.54 and GAAP EPS to be $0.36 to $0.38, both figures barely ahead of estimates for $0.52 and $0.34 respectively. This would point to adjusted EPS growth accelerating slightly to 62.1%, and GAAP EPS growth accelerating to 105.6%.

Margins:

Scorpio-X transitions Astera from selling high-margin silicon with retimers to fabric switches, which could see lower margins in the initial stages until the product scales.

Cash:

Operating cash flow was $95.3 million in Q4 for a 35.2% margin, up 7.1 points YoY and 1.3 points QoQ. For 2025, operating cash flow was $319.3 million for a 37.5% margin, expanding 3 points YoY.

Free cash flow was $76.6 million for a 28.3% margin, up 11.1 points YoY but flat QoQ. For the year, free cash flow was $281.8 million for a 33.1% margin, up 7.3 points YoY.

Cash and equivalents totaled $1.19 billion while debt remained zero.

Valuation:

Astera Labs trades at a forward P/S ratio of 20.9. The company has traded at a minimum forward P/S ratio of 10.5 and a maximum of 60.4 in recent years. Astera Labs is currently trading significantly lower than mid-range. On the bottom line, it trades at a forward P/E ratio of 67.1. The company has traded at a minimum of 29.9 and the highest of 202.2. Astera Labs is currently trading significantly lower than mid-range on the bottom line too.

Notable Risks:

Astera Labs may see near-term margin pressure as hardware becomes a larger part of the revenue mix, which can dilute profitability relative to lighter, higher-margin revenue streams from retimers. In addition, the company is likely to maintain elevated operating expenses as it invests aggressively to support growth and expand its position in AI infrastructure with Scorpio and other product lines. As a result, strong top-line growth may not translate as cleanly into bottom-line upside in the near term.

AI Ethernet Switches and Broadcom Partner

On our Discovery tier, we recently covered a leading supplier in back-end networking with over 41% market share of the 200G switch market and 55% share of the custom switch market, up from 40% in 2024.

The back-end networking positioning is important for this stock as it means the company is exposed to the faster-growing segment of Ethernet switching – the back-end TAM is forecast to grow at a 56% CAGR through 2029 on scale-out, and potentially soon, scale-up demand, whereas front-end (user-facing) is forecast to grow at a 20% CAGR.

Per management, the back-end also sees a much faster refresh rate of every 18-24 months versus >5 years for front-end deployments, and adopts the newest and fastest bandwidths (800G and soon 1.6T) due to the greater performance and reliability requirements of XPU-to-XPU and rack-to-rack communications.

The company is a lead supplier to Broadcom for 800G switches and 1.6T for Tomahawk6. Both 1.6T switches are optimized for AI back-end networking (scale-out and scale-up), as well as large-scale AI fabrics for AI training and inference for frontier model sizes. Management expects the 1.6T upgrade cycle to emerge in late 2026 but primarily land in 2027, with one customer giving visibility to a back-half 2026 ramp and multiple other ramps occurring through 2027.

Cooling Technologies

Vertiv: Facility-Level Cooling is in High Demand

Nvidia’s future design lineup shows continual increases in power consumption, with Vera Rubin expected to boost thermal design power (TDP) by 50% over Blackwell at up to 180 kW to potentially 230kW per rack, with the Rubin Ultra boosting this to 600kW by late 2027. These advancing power requirements place much more emphasis on liquid cooling, fluid management, and related thermal management technology.

Goldman Sachs’ Mark Delaney question about cooling product mix evolution and opportunity per MW, noting that “there was some discussion that Rubin raised racks may not need chillers, and conversely post-Supercompute last fall, there was a proposal from a competitor about stainless steel chillers maybe displacing CDUs.”

Vertiv CEO Giordiano Albertazzi said that this topic is not theirs to confirm, but even if CDUs are reduced, Vertiv stands to benefit as its portfolio spans the entire thermal management chain. He also emphasized that CDUs are likely to persist into the foreseeable future as other cooling tech remains too niche:

“All in all, we see that design continues to be mixed. If anything, this complicates the thermal chain and this complexity is something that we like as someone who has got the entire portfolio, we certainly are perfectly positioned to support our customers. And again, going back to what we're saying enable the right choice for our customers.

Cooling chips directly in other ways than through CDU in this moment is not something that we see. Simply because it would — in most of the cases, it will be niche applications probably, but in most of the cases, that would be too dangerous. Blast radius is a little bit too big, et cetera.”

Regarding CDUs, Vertiv acquired CoolTera in late 2023, a specialist in CDUs and data center liquid cooling. This acquisition expanded Vertiv’s IP, patents and engineering expertise ahead of Vera Rubin, which is primarily liquid cooled.

Revenue:

Vertiv delivered a strong Q4 with exceptional strength across key metrics, with backlog more than doubling YoY, orders more than doubling sequentially, and a significant step-up in book-to-bill ratio. Supported by these strong key metrics and ordering patterns, Vertiv guided for revenue growth to accelerate to 32% YoY in FY26, a more than four point YOY acceleration.

Vertiv reported a solid Q4 with revenue up 22.8% YoY (19% organic) and 7.6% QoQ to $2.88 billion, decelerating from 29% YoY in Q3. This revenue growth was driven entirely by strength in the Americas with revenue up 50.2% YoY, as Europe and APAC both registered YoY declines.

For Q1, Vertiv guided revenue to be $2.5 billion to $2.7 billion, marking a reacceleration to 27.7% YoY and 22% organic growth at midpoint; however, this will mark a QoQ decline of (9.7%) at the midpoint of this forecast, following typical first quarter seasonality (though slightly better compared to Q1 2025’s (13.2%) QoQ decline). As noted above, growth is expected to accelerate towards the 38% range by Q4, supported by orders growth, backlog and book-to-bill.

Looking ahead to FY26, Vertiv laid out initial guidance for revenue to be between $13.25 billion to $13.75 billion, accelerating to 32% YoY from FY25’s 27.7% growth; organic growth is projected to be 27-29% YoY, a slight acceleration from 26%. This also marked a significant beat over consensus estimates for $12.39 billion.

AI Revenue:

Vertiv reported 109% YoY and 57% QoQ growth to $15 billion in Q4, accelerating sharply from 28% YoY and 12% QoQ in Q3. On a dollar basis, Vertiv added $5.5 billion to its backlog sequentially.

This backlog growth was out of the ordinary for a few reasons – over the last two years, Vertiv’s fastest QoQ backlog growth up until this point was 15%, yet now growth was ~57%.

It also created an entirely new dynamic for backlog-to-revenue ratios. Vertiv has seen its backlog to forward revenue (full year guidance from Q4) ratio hover between 72% to 78% over the last three years, yet now this ratio stands at ~111%, suggesting much more elevated revenue visibility through next year with the majority being firm orders.

Additionally, Vertiv’s conversion time for this backlog has been pushed out, from its typical 9 months to roughly 15 months, with management stating it expects the backlog to be shipped in the next 12 to 18 months.

Aiding the backlog growth was an increase in organic orders in Q4, with Vertiv reporting organic orders up 252% YoY (though against a flat YoY comp).

This marked a substantial 192 point acceleration from 60% YoY growth, while QoQ growth accelerated from 20% in Q3. This strong Q4 order intake drove TTM order growth up to 81% YoY, from 21% YoY in Q3. Despite this surge, management emphasized that the pipeline continues to grow across all regions and has not depleted, with the order growth simply reflecting the level of demand in the market with no abnormalities in purchasing.

Despite this strength, Vertiv's management emphasized that orders are lumpy, and in fact, management plans to drop this metric from future reporting.

Driven by Q4’s order growth, Vertiv’s book-to-bill ratio jumped to 2.9X, up from 1.4X in Q3. As is the case with orders, book-to-bill has seen some lumpiness quarter to quarter, though there are some key parallels that we can draw here given the simultaneous strength in orders and backlog.

EPS:

While adjusted EPS decelerated 26 points in Q4 to 37% YoY, Vertiv forecast a sharp rebound in Q1 to 53%, with FY26’s guide implying that growth will persist at a similar rate through the year.

Adjusted EPS was $1.36 in Q4, up 37% YoY but decelerating from 63% in Q3, coming in 4.9% ahead of estimates. GAAP EPS growth was exceptionally strong, up 200% YoY to $1.14, though growth was off a smaller base.

For Q1, Vertiv guided for adjusted EPS to be $0.95 to $1.01, up 53% YoY at midpoint. Estimates point to ~50% growth being maintained in Q2 before a step lower towards the 40-45% range in the second half of the year.

FY26 adjusted EPS was guided to be $5.97 to $6.07, up 43% YoY and decelerating only slightly from 47% growth in FY25.

Margins:
Vertiv saw slight gross and operating margin expansion in Q4, though in line with seasonal trends. Q1 margins are projected to take a step down QoQ but remain higher YoY; however, management added that they expect “to have materially offset unfavorable margin impact from tariffs as of the first quarter of this year,” providing more room for upside beginning in Q2.

GAAP gross margin was 38.9% in Q4, up 1.1 points QoQ and 1.8 points YoY.

GAAP operating margin was 20.1% coming in below management’s guidance for 20.7%.

Adjusted operating margin was 23.2% (versus guidance for 22.4%). Looking ahead to Q1, GAAP operating margin was guided to be 16.3%, down 3.8 points QoQ but up 2 points YoY, while adjusted operating margin was guided to be 19%, down 4.3 points QoQ but up 2.5 points YoY.

GAAP net margin was 15.5%, flat QoQ and up 9.2 points YoY, as the year-ago quarter recorded a $180 million negative impact related to warrant liabilities. Adjusted net margin was 18.5%, up 0.4 points QoQ and 2.1 points YoY.

Vertiv guided for solid margin expansion for FY26, suggesting that Q2 through Q4 will see much stronger margins to offset Q1’s softness. GAAP operating margin was guided to be 20.5%, up 2.6 points YoY, while adjusted operating margin was guided to be 22.5%, up 2.1 points QoQ. This will flow through to net margin, with GAAP net margin guided at 15.4%, up 2.4 points, and adjusted net margin guided at 17.5%, up 1.5 points YoY.

Cash:

Driven by the surge in orders and larger advanced payments, Vertiv reported robust cash flows in Q4.

Operating cash flow in Q4 was $1.01 billion for a 34.9% margin, up 15.9 points QoQ and 16.8 points YoY; for the full year, operating cash flow was $2.11 billion (with Q4 accounting for nearly half of that) for a 20.7% margin, up 4.1 point YoY.

Adjusted free cash flow was $910 million, up 151% YoY, representing a 31.6% margin, up 14.3 points QoQ and 16.2 points YoY. For FY25, adjusted FCF was $1.89 billion for an 18.4%, up 4.2 points YoY.

Cash and equivalents were $1.83 billion, while debt was $2.91 billion; however, Vertiv’s net leverage ratio remained at 0.5X.

Inventories increased marginally in Q4, up ~1.8% QoQ to $1.46 billion, while accounts receivable showed a larger jump at 10.6% QoQ to $3.11 billion.

In accordance with the order surge, deferred revenue jumped more than 60% QoQ to more than $1.81 billion, with management noting that order mix and order type are the two drivers, with mix possibly having a larger influence in Q4.

Valuation:

Vertiv trades at a peak forward P/S ratio of 8.4 and traded at a minimum forward P/S ratio of 2.2 in April 2025. On the bottom line, it trades at a forward P/E ratio of 48.7. Vertiv has traded at a minimum of 14.4 and a maximum of 52.5 in recent years.

Notable Risks:

As long as hyperscalers continue building capacity, demand for Vertiv’s power and cooling infrastructure should remain supported, particularly since Blackwell systems already require advanced thermal solutions. However, if analysts are modeling a step-function increase in revenue per rack from Rubin’s higher power density and more demanding liquid cooling requirements, that uplift could be pushed out depending on when the Rubin delay resolves.

Dell: Margin Story; then Revenue

Dell is not a stock we would own indefinitely, but given the strong recent performance, there’s a chance the stock is in play right now. Above and beyond revenue, Dell’s stock depends on its margins.

Dell reported some of the strongest AI revenue numbers in the industry in Q4 with AI server revenue up 342% YoY to $9.0 billion, orders up 1,906% YoY to a record $34.1 billion and backlog up 177% QoQ to a record $43 billion.

Margins:

The market was growing concerned that rapidly rising memory costs would squeeze on Dell’s margins (“you're supposed to miss numbers, by the way, when memory prices go up”), yet Dell’s margins are among the highest they’ve been since we began tracking the stock. This is quite impressive given the AI server and memory headwinds, with storage being a key piece of this margin strength despite being a much smaller portion of revenue at $4.8 billion this quarter.

Q4 gross profits were $6.7 billion or 20.2% of revenue compared to $5.7 billion or 23.7% in the same period last year. The lower margins reflect higher proportion of AI revenue mix.

Q4 operating income grew by 43.2% YoY to $3.1 billion primarily driven by operating leverage. Operating margin was 9.3% compared to 9% in the same period last year.

Q4 net income was $2.3 billion or 6.8% of revenue compared to $1.5 billion or 6.4% of revenue in the same period last year.

Revenue:

Dell’s Q4 revenue grew by 39.5% YoY and 23.6% QoQ to $33.4 billion driven primarily by outperformance in AI servers. Revenue growth accelerated by 28.7 percentage points from 10.8% YoY growth in the previous quarter and significant improvement from the (9.3%) QoQ decline in the previous quarter.

Management also provided strong Q1 guidance of $34.7 billion to $35.7 billion, implying YoY growth of 50.6% and 5.5% QoQ at the midpoint.

Cash:

Similar to margins, Dell’s cash flows were equally as strong, with operating cash flow margin expanding by double digits and free cash flow following. Cash flow margins were also around the highest they’ve been over the last three years.

Q4 operating cash flow was $4.7 billion or 14% of revenue compared to $585 million or 2.4% of revenue in the same period last year.

Q4 adjusted free cash flow was $5.1 billion or 15.2% of revenue compared to $474 million or 2% of revenue in the same period last year.

The company had a high debt of $31.5 billion compared to cash & investments of $13.3 billion at the end of Q4. The company repurchased shares worth $1.85 billion and paid dividends of $346 million in Q4.

Valuation:

Dell trades at a forward P/S ratio of 0.9. The company has traded at a minimum forward P/S ratio of 0.4 and a maximum of 1.3 in recent years. The company is currently trading at the mid-range. On the bottom line, it currently trades at a forward P/E ratio of 15.8. The company has traded at a minimum forward P/E ratio of 7.2 and a maximum of 22.3. The company is currently trading at the mid-range on the bottom line too.

Notable Risks:

The company had a high debt of $31.5 billion compared to cash & investments of $13.3 billion at the end of Q4.

AI Software:

Meta: Tied for the Best Mag 7 Stock

Meta is an “eyeballs” company, and thus, an important lever to growth is increasing user engagement. In the most recent quarter, the company drove incremental engagement from ranking and product improvements. Primarily, the company optimized their systems to consider longer interaction histories to better identify a person’s interests. This led to the highest lift in feed views that the company has seen in two years: “The optimizations we made in Q4 drove a 7% lift in views of organic feed and video posts on Facebook, resulting in the largest quarterly revenue impact from Facebook product launches in the past two years.”

Moving forward, Meta’s goal this year is to scale their training data to offer more personalized recommendations. By moving away from algorithms driving the feeds to LLMs, Meta can make the systems more responsive to real-time interest.

This may seem like a subtle shift, but it’s actually not subtle at all – Meta is proposing a complete overhaul in how their systems surface content. Moving forward, LLMs will offer reasoning for a level of personalization not possible in the current approach, which is more pattern recognition based. Think of how Spotify works – it surfaces music you’ve already listened to. Facebook feeds are similar. However, moving forward, Meta can offer a personalized agent approach to where AI optimizes a feed to suggest content that does not require a direct signal.

Here is what was stated on the call:

“We're seeing in our early testing that personalized responses drive higher levels of engagement, and we expect to significantly advance the personalization of Meta AI this year. This dovetails with our investments in content understanding, which will enable our systems to develop a deeper understanding of each person's interests and preferences while also identifying the most relevant content across our platform to pull into responses.”

Although Meta uses AI in its recommendations, the current systems are based on pattern and behavior-driven algorithms. For 2026, Meta will offer content that goes beyond the bounds of what you’ve already searched for/engaged with AI agents that can more intelligently infer your interests.

The result will be more time spent on the platform and with higher engagement. Even incremental gains here will lead to more advertising dollars.

The second area that Meta is making “big bets” by increasing monetization efficiency. Last quarter alone, the company doubled the number of GPUs used to train their GEM model for ads ranking. Similar to what was stated above, part of the improvements is using longer sequences of user behavior to inform the feed plus which ads are placed and when: “This new sequence learning architecture is significantly more efficient than our prior architectures which should enable us to further scale up the data, complexity and compute we use in our future ranking models to deliver performance gains.”

Meta’s main approach to increasing the effectiveness of ad placements remains user targeting, but just smarter user targeting. This results in 4X better results than using AI to increase overall ad load: “In fact, in the second half of 2025, our initiatives on Facebook to redistribute ads across users and sessions delivered a nearly 4x larger revenue impact than Facebook ad load increases.”

As you’ll see below in the Financials section, these improvements are making a material difference with Q4 revenue growing 17% QoQ and with a forward guide that implies the highest YoY growth rate for Meta since Covid-fueled 2021.

Revenue:

Q4 revenue grew by 23.8% YoY and 16.9% QoQ to $59.9 billion, beating estimates by 2.4%. Although strong sequential growth in Q4 is seasonal and Meta posted a 19.2% QoQ increase in Q4 2024, the current sequential growth is being achieved on a substantially higher revenue base of $51.2 billion versus $40.6 billion in the prior-year period. The strong revenue growth was primarily driven by robust demand stemming from AI advancements in ad recommendations, monetization, and user engagement.

Management issued strong revenue guide of $53.5 billion to $56.5 billion, implying a 30% YoY growth and a sequential decline of (8.2%) at the midpoint. While the QoQ contraction reflects normal seasonality, the implied 30% YoY growth represents the fastest pace in the last 4.5 years.

The company’s 2025 revenue grew by 22.2% YoY to $200.97 billion. Looking ahead, revenue growth is expected to accelerate 2.7 percentage points to 24.9% YoY growth to $250.97 billion in 2026 and will moderate to 17.8% YoY to $295.7 billion in 2027.

AI Revenue:

Meta is already seeing tailwinds from AI recommendation models driving higher ROI for advertisers following increased time spent across its family of apps.

Q4 advertising revenue grew by 24.3% YoY to a record $58.1 billion. Notably, absolute advertising revenue growth reached $11.3 billion in the quarter, surpassing the $10.2 billion increase recorded in Q3.

Perhaps the most important metric for Meta’s ad monetization is Family ARPP (average revenue per person). It reached a record $16.56 in Q4 2025, highlighting that Meta’s AI-driven ad performance improvements and monetization efforts are bearing fruit. While the 16.2% YoY growth in Q4 reflects a deceleration from the 17.7% seen in Q3, such a trend is common on a higher base and less of a concern given Meta is guiding for a modest acceleration this fiscal year. Notably, Q4 ARPP outpaced the 15.6% growth recorded in the prior-year period.

EPS:

Q4 GAAP EPS grew by 10.7% YoY to $8.88, beating estimates by 8%, driven primarily by higher revenue from stronger AI monetization. Analysts expect EPS to grow 2.9% YoY to $6.6 in Q1 2026.

Looking ahead, GAAP EPS is expected to grow 25.8% YoY to $29.5 in 2026 and 15.9% YoY to $34.2 in 2027.

Margins:

Q4 gross margin was 81.8%, up 10 basis points YoY and down 20 basis points sequentially.

Q4 operating income grew by 5.9% YoY to $24.7 billion with an operating margin of 41.3%, up 130 basis points sequentially and down 700 basis points YoY primarily due to higher AI-related operating expenses.

Q4 net income grew by 9.3% YoY to $22.77 billion with a net profit margin of 38% compared to 43.1% in the same period last year.
Cash:

Meta’s cash flows improved in Q4, driven by higher profits.

Q4 operating cash flow grew by 29.4% YoY to $36.2 billion with an operating cash flow margin of 60.5% compared to 57.8% in the same period last year and 58.5% in Q3.

Q4 free cash flow grew by 7% YoY to $14.1 billion with a free cash flow margin of 23.5% compared to 27.2% in the same period last year, and 20.7% in Q3.

The company had cash & marketable securities of $81.6 billion and debt of $58.7 billion.

Valuation:

Meta trades at a forward P/S ratio of 6.4. The company has traded at a minimum forward P/S ratio of 5.3 and a maximum of 9.9 in recent years. Meta is currently trading slightly lower than mid-range. On the bottom line, it trades a forward P/E ratio of 21. Meta has traded at a minimum of 15.2 and a maximum of 27.9. Meta is currently trading around the mid-range on the bottom-line.

Notable Risks:

Elevated capex increases financial risk by requiring substantial upfront investment before returns are fully realized. If monetization lags spending, margins and sentiment could come under pressure.

Google: Tied for First Place Among Mag 7

Revenue:

Google delivered Q4 revenue of $113.83 billion, up 18.2% YoY, accelerating from 16.2% YoY in Q3 and marking the fastest growth since Q1 2022, driven by the accelerations in both Search and Cloud revenues.

AI Revenue:

Of the Big Three, Google reported the strongest AI-driven cloud acceleration this quarter, coupled with strong AI metrics and backlog growth that support this acceleration continuing through 2026.

Google Cloud growth accelerated each quarter this year, though Q4 recorded the sharpest acceleration at 14 points to 48% YoY, with revenue coming in at $17.66 billion. Notably, this marked the segment surpassing a $70 billion annualized run rate, up from less than $50 billion annualized at the start of 2025. This would also mark its fastest revenue growth in more than four years. For Q1, Google expects strong growth to continue despite having tight accelerator supply.

While the sharp acceleration is certainly impressive, sequential growth figures show a strong underlying trend within Cloud – for three quarters in a row, Cloud has delivered >$1 billion in QoQ growth, with each quarter larger than the last and Q4 increasing more than $2.5 billion versus Q3. Putting this in perspective to highlight Google Cloud’s strong AI-driven momentum, this was nearly as large as a QoQ increase as AWS, which rose $2.57 billion sequentially despite being double the size of Google Cloud.

In percentage terms, Cloud growth accelerated from ~11% QoQ in Q2 and Q3 to 16.5% QoQ in Q4; this compares to 7.8% QoQ for AWS in Q4 and likely <2% QoQ for Azure.

Google also provided a handful of stats accentuating AI’s impacts to growth. Revenue from products built on Google’s own genAI models increased nearly 400% YoY. Revenue from third-parties building AI applications rose 300% YoY. In total, Google Cloud has 14 product lines spanning infrastructure, platform and high-margin AI products and services exceeding $1 billion in annual revenue.

It’s important to note that growth is currently off of a small base, thus the market will likely look toward overall AI revenue to justify the capex increase Alphabet is guiding for. While there were no specific updates to Cloud’s AI revenue or contribution, assuming that AI contributed roughly half of the quarter’s 48% YoY growth, this would place AI’s run rate at more than $11 billion.

EPS:

Google reported EPS of $2.82 in Q4, beating estimates by 6.8% and representing a growth of 31.1% YoY.

Margins:

Google reported a gross margin of 59.8% in Q4, up 1.1 points YoY.

Operating margin was 31.6%, down 0.5 points YoY but up 1.1 points QoQ.

Net margin was 30.3% in Q4, up 2.8 points YoY but down 3.8 points QoQ (as Google recorded a $10.7 billion gain on equity investments in Q3 that impacted the bottom line).

Cash:

Google’s cash flows remained rather resilient in 2025, with free cash flow margin declining marginally in the face of a 74% increase in capex. However, FCF must be tracked closely as the capex surge could easily bring free cash flow margin to the single-digits. Google has guided capex of $175-$185 billion in 2026, up 96.7% YoY at the midpoint.

In Q4, Google reported operating cash flow of $52.4 billion for a 46% margin, up from a 40.6% margin in the year ago quarter but down from a 47.2% margin in Q3. For the full year, Google reported OCF of $164.7 billion for a 40.9% margin, up from 35.8% in 2024.

Q4 free cash flow was $24.55 billion for a 21.6% margin, contracting on both a YoY and QoQ basis, from 25.8% in the year ago quarter and 23.9% in Q3. For 2025, free cash flow was $73.3 billion for an 18.2% margin, down from 20.8% in 2024.

Looking ahead to 2026, analysts project Google to generate operating cash flow of $195.9 billion, though this would leave just $15.9 billion in FCF at the midpoint of capex guidance. Based on current revenue estimates for $471.4 billion, this would roughly project FCF margin to be 3.4%.

Google’s balance sheet remains healthy with cash and marketable securities of $126.8 billion, while debt was $46.5 billion, up from $21.6 billion in Q3 as Google issued more than $26.5 billion in debt in the quarter. Debt is likely to rise sharply again in Q1 as Google’s recent bond sale reportedly took in over $30 billion.

Valuation:

Google trades at a forward P/S ratio of 8.6. The company has traded at a minimum forward P/S ratio of 4.4 and a maximum of 9.7 in recent years. Google is currently trading slightly higher than mid-range. On the bottom line, it trades at a forward P/E ratio of 28.9. Google has traded at a minimum of 13.7 and a maximum of 30.5. Google is currently trading slightly higher than the mid-range on the bottom line too.

Notable Risks:

The high capex would put pressure on the company’s cash flows.

Reddit: The Scarce Asset in an AI-Generated Internet

Reddit reported revenue of $725.6M for 70% YoY growth and 24.1% QoQ growth, which reflects seasonality from the holiday quarter. When comparing to last year's Q4, the company reported 130 basis points higher growth on a QoQ basis – no small feat given the tough comps the company is lapping with six quarters of 60%+ growth.

The bottom-line shines with this stock as adjusted EBITDA was 45.1%, up from 36.1% in the year ago quarter. The GAAP operating margin of 31.9% has expanded sizably from the 12.4% margin reported last year for operating income of $232M. The free cash flow margin is 36.3%, leading the company to announce $1 billion in share repurchases.

Although many investors consider Reddit niche compared to larger sites like Facebook or Google, the key metrics steadily move up on this audience of roughly 500 million monthly users and 120 million daily users. Global average revenue per user (ARPU) grew 42% YoY, up from 23% YoY growth in Q4 of last year. Advertising revenue also accelerated to 75% growth compared to 60% last year.

Despite the strong report, the stock price has been slightly volatile. Management guided for a deceleration to 52.9% YoY growth, which leaves the market wondering if there is a catalyst in Reddit’s future. On the call, management pointed out they’ve guided conservatively for a few quarters now and discussed a new initiative to onboard advertisers at the bottom of the funnel with their AI-powered MAX platform. Another reason is that the company will no longer report logged-in users separately from logged-out users. This has been a point of contention for the Street for some time, which we covered in our previous analysis.

That said, stocks with unwavering fundamentals with 50%-60% growth on the top line and 100%+ growth on the bottom line have a way of being mispriced quickly during periods of uncertainty. Consider that Reddit offers a Rule of 40 (revenue growth plus adjusted EBITDA margin) of 115 compared to Palantir’s Rule of 40 (revenue growth plus adjusted operating margin) of 127. Reddit’s rule of 40 is up 7 percentage points sequentially and 8 percentage points YoY.

Reddit has always monetized through advertising, but Reddit Max marks a shift from primarily brand and contextual ads toward AI-driven, automated performance advertising that can increase the number of advertisers that Reddit onboards.

Although early, this could put Reddit on the map for using its personalized data to compete for ad dollars in performance advertising. Should it prove successful, this would also be a strong motivating factor for Reddit to drop the logged-in/logged-out user metric given users will see the performance ads regardless of logged-in status. Most importantly, these ads monetize at a higher rate than brand ads.

Revenue:

Reddit once again reported stellar revenue growth of 69.7% YoY and 24.1% QoQ to $725.6 million. Revenue growth has been more than 60% for the sixth consecutive quarter. The company’s revenue beat estimates by a solid 8.8% and was better than last quarter’s beat of 6.4%. The strong revenue growth was primarily driven by 75% YoY growth in the advertising revenue to $690 million. While its other revenue, which includes licensing deals with Google and OpenAI, rose by a modest 8% YoY to $36 million. Regionally, U.S. revenue grew 68% and international revenue grew 78% YoY.

Management guided Q1 revenue of $595M to $605M, implying a YoY growth of 52.9% YoY and down (17.3%) QoQ. The company’s Q1 guide beat the analysts estimates by 4% and was also stronger than last quarter’s beat of 3.5%. Analysts expect Q2 revenue to grow 42.8% YoY and Q3 revenue to grow 40% YoY to $818.8 million.

Full year 2025 revenue grew by 69.4% YoY to $2.20 billion. Looking ahead, analysts expect 2026 revenue to grow by 42.7% YoY to $3.14 billion and 2027 revenue to grow by 30.2% YoY to $4.1 billion.

AI Revenue:

Q4 advertising revenue grew by 75% YoY to $690 million, accelerating from 74% growth in the previous quarter. Management attributed to impression growth as the main driver of revenue growth as the company’s AI investments are driving efficiency for advertisers delivering more outcomes and lower cost per action. Since last year, enhancements to the shopping ad ML models delivered over 75% improvement in advertisers return on investment.

In Q4, click volume in the mid-funnel grew over 60% and lower funnel conversion volume doubled YoY. The company’s active advertisers grew by 75% YoY in Q4 and Reddit added new customers across its channels, including large, mid-market and SMBs.

The company’s average revenue per user (ARPU) grew by 42% YoY and 19% QoQ to $5.98. ARPU growth accelerated from 41% YoY and 11% sequential growth in the previous quarter.

The US ARPU grew by 53% YoY to $10.79. Although it slightly decelerated from 54% YoY growth in Q3, on a sequential basis it accelerated to 19% growth from 15% QoQ in the previous quarter.

EPS:

Q4 GAAP EPS grew by 244.4% YoY and 55% QoQ to $1.24, beating estimates by a solid 33.1%.

Analysts expect EPS to grow by 286.6% YoY to $0.50 in Q1 and 86% YoY to $0.84 in Q2.

Looking ahead, analysts expect 2026 EPS to grow by 56.9% YoY to $4.11 and 39.5% YoY to $5.74 in 2027.

Margins:

The company is experiencing strong profit growth, primarily driven by operating leverage.

Q4 gross profits grew by 68.5% YoY to $666.9 million with a gross margin of 91.9%. The company reported its sixth consecutive quarter of above 90% gross margins.

Operating margin improved by 19.5 percentage points YoY and 8.2 percentage points sequentially to 31.9% primarily driven by strong operating leverage.

Net profit margin improved by 18.1 percentage points YoY and 6.9 percentage points sequentially to 34.7%.

Q4 adjusted EBITDA grew by 112% YoY to $327 million with an adjusted EBITDA margin of 45.1%, beating the management guidance of 42.4%. Adjusted EBITDA margin improved by 9 percentage points YoY and 4.8 percentage points sequentially.

Management has guided Q1 adjusted EBITDA margin of 35.8%, down 9.3 percentage points sequentially and up 6.4 percentage points YoY.

Cash:

Reddit reported strong cash flows primarily driven by record profits. The company’s balance sheet is robust, providing financial flexibility to invest in future growth and support share repurchases.

Q4 operating cash flows grew by 196.5% YoY to $266.8 million with an operating cash flow margin of 36.8%, up 15.8 percentage points YoY.

Q4 free cash flows grew by 195.7% YoY to $263.6 million with a free cash flow margin of 36.3%, up 15.5 percentage points YoY.

The company has cash and marketable securities of $2.48 billion with no debt and cash increased by $250 million sequentially.

Valuation:

Reddit trades at a forward P/S ratio of 8.9. The company has traded at a minimum forward P/S ratio of 4.2 and a maximum of 24.4 in recent years. Reddit is currently trading significantly lower than mid-range. On the bottom line, it trades at a forward P/E ratio of 22.4. Reddit traded at a minimum of 18.2 and a maximum of 95.8. The company is trading significantly lower than mid-range on the bottom line too.

Notable Risks:

Reddit’s decision to stop reporting logged-in and logged-out user metrics in the second half of 2026 may lead to a transparency risk for investors. Those metrics help the market assess engagement quality, traffic mix, and monetization potential across the platform. Where the site ranks in terms of web traffic could change at any time as it’s entirely dependent on the Google partnership.

Palantir: Commercial Surges, Yet Software Stocks Will be Tested

Palantir reported another very strong quarter in Q4, with revenue accelerating to 70%, an impressive 57 point acceleration over the last ten quarters, while guiding for revenue to accelerate further to 73.6% in Q1.

US commercial momentum remained unabated, with revenue accelerating 16 points sequentially to 137% YoY, surpassing the $500 million mark in the quarter. When looking at the strength of both QoQ and YoY growth, it’s likely Palantir represents the highest AI segment growth across the AI universe.

On top of that, Palantir initially guided for fiscal 2026 revenue to accelerate from 56.1% to nearly 61% YoY, driven by US commercial revenue accelerating six points to >115% YoY. Driving such an acceleration at these growth rates is undeniably difficult, yet there are hints that Palantir could go above and beyond these figures by this time next year.

If Palantir can outperform to a similar degree as 2025, such as 45-50 points above the first guidance, the revenue projection for US commercial would look much different. This scenario would need around a 10 to 12 point raise each quarter, and could project revenue as ~160% YoY, a 51 point acceleration. In dollar terms, this would project $3.82 billion, or ~$680 million above guidance.

The main takeaway here is that even a modest outperformance and guidance raises of a few points each quarter could easily drive US commercial revenue growth to a double-digit acceleration from 2025’s 109% growth.

Revenue:

Palantir reported revenue of $1.41 billion in Q4, accelerating to 70% YoY while QoQ growth ticked 1.5 points higher to 19.1%, and marking a 50 point acceleration over the last two years. This also is Palantir’s highest revenue growth in their history as a public company.

More impressively, Palantir guided for this revenue acceleration to continue into Q1 and for 2026, suggesting that the AI-driven growth engine that propelled shares higher through 2024 and 2025 is still intact, and potentially strengthening.

Q1 revenue was guided to be $1.532 billion to $1.536 billion, accelerating 3.6 points to 73.6% YoY at midpoint (and what would be a fresh record growth rate), though QoQ growth would be just 9%.

For 2026, Palantir offered an initial guide for $7.182 billion to $7.198 billion, up 60.7% YoY at midpoint, or $900 million ahead of consensus for $6.29 billion for 42.8% growth. This would also mark a 4.6 point acceleration, a significant feat considering the swift acceleration the company saw through the back half of 2025.

AI Revenue:

Palantir’s AIP-driven US commercial segment remains the company’s core revenue driver, with growth accelerating once again in Q4 to the fastest rate in four years. What’s more impressive is that Palantir not only has guided for US commercial revenue to more than double in 2026, but that it was guided to accelerate from 2025’s already-rapid 109% growth.

US commercial revenue rose 137% YoY and 29% QoQ to $507 million in Q4, surpassing a $2 billion annualized run rate in the quarter, up from a $1 billion run rate at the start of 2025. QoQ growth accelerated only one point from 28% in Q3, though accelerating sequentially at this pace is difficult.

On a YoY view, US commercial continued to accelerate, with the 137% growth in Q4 marking a 16 point acceleration from 121% YoY in Q3. Since the start of the year, US commercial revenue growth has accelerated a tremendous 66 points.

RPO saw a meaningful step up in Q4, rising 62% QoQ to $4.21 billion, with YoY growth accelerating from 65.6% in Q3 to 143.4% in Q4. This also represented the company’s strongest RPO growth since the start of 2023 on both a YoY and QoQ basis.

EPS:

Palantir reported $0.25 in adjusted EPS in Q4, up 78.6% YoY, with GAAP EPS coming in at $0.24, up 700% YoY and beating estimates by 8.7% and 33.3% respectively.

Palantir did not provide guidance for Q1, though consensus estimates currently call for adjusted EPS of $0.28, up 114.5% YoY, and GAAP EPS of $0.24, up 200% YoY.

For the full year, Palantir delivered adjusted EPS of $0.75, up 82.9% YoY, and GAAP EPS of $0.63, up 231.6% YoY. Again, Palantir did not provide guidance for the forward fiscal year, though current consensus points to adjusted EPS up 76.2% to $1.32 and GAAP EPS up 79.4% to $1.13.

Margins:

While its revenue growth and acceleration are second-to-none in AI software, so are Palantir’s margins, with the company showcasing an impressive ability to drive margin expansion of >10 points while simultaneously accelerating revenue.

For example, Palantir’s adjusted operating margin in Q4 was a record 57.4%, well ahead of its guidance for 52.4% and expanding 12 points YoY. This is a remarkable feat as it highlights Palantir’s ability to maintain its cost profile despite meaningfully accelerating revenue quarter after quarter.

Adjusted EBITDA margin also showed strong expansion, coming in at 57%, up 6 points QoQ and 11 points YoY.

Looking down the line, gross margins expanded nicely in Q4, with GAAP gross margin at 85%, up 6 points YoY and 3 points QoQ. Adjusted gross margin also expanded but at a smaller degree, up 3 points YoY and 2 points QoQ to 85%.

The operating margin expansion was where Palantir shined. GAAP operating margin was 41% in Q4, up 40 points YoY (coming against a low comp due to the one-time stock appreciation rights (SARs) expense) and 8 points QoQ.

As noted above, adjusted operating margin was 57.4%, up 12 points YoY and 6 points QoQ. Palantir guided for adjusted operating margin to remain strong in Q1 to 56.8% at midpoint, up 13 points YoY and down marginally QoQ.

Cash:

Palantir’s cash flows were robust in Q4, and management guided for adjusted FCF margin to expand in 2026 from an already strong 51% in 2025.

Operating cash flow was $777.3 million in Q4 for a 55% margin, down slightly from a 56% margin in the year ago quarter but rebounding solidly from a 43% margin in Q3. For the year, Palantir delivered operating cash flow of $2.13 billion, or a 48% margin, up from 40% in 2024.

Adjusted free cash flow was $791.4 million in Q4 for a 56% margin, down from a 63% margin a year ago but up from 46% in Q3. For 2025, Palantir generated $2.27 billion in adjusted FCF for a 51% margin, up from 44% in 2024.

For 2026, Palantir guided for a step up in adjusted FCF, projecting it to increase more than 77% YoY to $3.925-$4.125 billion. This would represent an adjusted FCF margin of 56%, a five point expansion from 2025.

Palantir’s balance sheet remained extremely healthy with cash of $7.18 billion and zero debt.

Valuation:

Palantir trades at a forward P/S ratio of 44.8. The company has traded at a minimum forward P/S ratio of 12.5 and a maximum of 112.3 in recent years. Palantir is currently trading significantly lower than the mid-range. However, forward P/S ratio > 30 is considered high. On the bottom line, it trades at a forward P/E ratio of 103.5. Palantir has traded at a minimum of 41.7 and a maximum of 285.8. Palantir is currently trading significantly lower than the mid-range.

Notable Risks:

Investors should be prepared for even well-insulated software names like Palantir and Cloudflare to face valuation pressure — not necessarily because their businesses are deteriorating, but because the pace of iteration from Anthropic, OpenAI, and a growing cohort of well-funded private startups continually resets the market's assumptions about who captures value in the AI stack and how quickly incumbents can be commoditized.

Cloudflare: Strong Positioning, Timing is the Main Question

While Big Tech witnessed weak price action following capex estimates for 2026, Cloudflare’s earnings report was being met with enthusiasm. Rather than competing with hyperscalers head-on, the company is taking a different route by offering an edge network where latency, global reach and lower costs matter more than compute and scale.

Key metrics are suggesting an important inflection is underway, which was a theme from our coverage last quarter. Cloudflare reported the strongest revenue growth since Q1 2023. The company’s Q4 revenue grew by 33.6% YoY and 9.3% QoQ to $614.5 million, beating estimates by a solid 3.9%. The company’s Q1 revenue guide also beat estimates by 1%.

The company reported a record new annual contract value (ACV) in Q4, which grew by nearly 50% YoY and was the fastest growth rate since 2021. Q4 remaining performance obligations (RPO) grew by 48% YoY and was the fastest growth rate since June 2022. Similarly, paying customers grew by 40% YoY and accelerated by 7 percentage points from 33% growth in the previous quarter. Notably, active developers on the Workers platform grew by 50% YoY to 4.5 million.

Cloudflare’s CEO buried the lead a bit in the opening remarks, finally stating what is perhaps the most important element to his quarter’s beat: AI Agents. Although the key metric was provided for January, it’s clear that Cloudflare is seeing a strong inflection: “Over the month of January alone, the number of weekly requests generated by AI agents more than doubled across the Cloudflare network. This is driving increased demand for our whole platform.”

According to management, this creates a “virtuous flywheel” as more agents drive more code execution on their Workers Platform, which in turn, drives more demand for their security products and networking services.

AI agents also drive sheer infrastructure consumption for Cloudflare as agents look at many more sites and are always-on – which leads to more overall usage.

Here was some commentary from the previous earnings call:

“You've got a bunch of the agents of the world that are interacting with the Internet and they're interacting with it at a volume that we've just never seen before. And that's just driving more need for what are classically Cloudflare’s services. So the fact that more than 20% of the Internet sits behind us means that the agents have to interact with us, which means we have a seat at the table in defining exactly what the rules and the rails and the guardrails of the future of agentic commerce is going to look like; and be, and we are sitting in the middle of that.”

Revenue:

Cloudflare reported the strongest revenue growth since Q1 2023. The company’s Q4 revenue grew by 33.6% YoY and 9.3% QoQ to $614.5 million, beating estimates by a solid 3.9%. Revenue growth accelerated 2.9 percentage points from 30.7% growth in Q3 and was primarily driven by strong AI demand for its services, particularly from its enterprise customers. The company guided Q1 revenue of $620 million to $621 million, implying a YoY growth of 29.5% YoY and 1% QoQ and beating estimates by 1%.

The company 2025 revenue grew by 29.8% YoY to $2.17 billion. Management provided a strong 2026 revenue guide of $2.785 billion to $2.795 billion, implying a YoY growth of 28.7% and beating estimates by 1.8%.

AI Revenue:

Note that Cloudflare does not have enough AI revenue to breakout into a standalone segment. However, many of the companies key metrics are benefitting from the overall increased internet traffic from AI agents with the CEO stating: “If you look at the last 30-plus years of the Internet and software ecosystem, they were built for human consumption, people in seats and clicks. Now the agentic Internet is emerging, and we can already see its trends. If humans looked at 5 sites when they were making a decision, agents might look at 5,000.”

Over time, Cloudflare will see more revenue from edge inference, but right now, it’s mainly visible in internet usage. Here are some examples:

Q4 remaining performance obligations (RPO) grew by 48% YoY and 16% QoQ to $2.496 billion, accelerating from 43% YoY and 8% QoQ growth in Q3. It was the fastest growth rate since June 2022. Current RPO was 63% of total RPO and grew 34% YoY.

Cloudflare reported a record new annual contract value (ACV) in Q4. Matthew Prince said in the earnings call, “We blew away our previous record for new ACV in the quarter, with strong year-over-year and quarter-over-quarter acceleration. In Q4, new ACV book grew nearly 50% year-over-year, making it not only a record quarter in absolute ACV dollars but also the fastest growth rate we've delivered since 2021.”

However, what has us on alert is the company’s billings grew by 27% YoY and 11% QoQ to $694.9 million. Among the key metrics, billings growth was blemish as it decelerated from 40% YoY and 12% QoQ growth in Q3. Billings represents real-time demand, and thus, RPO could be less meaningful if it’s signaling multi-year contracts.

EPS:

The company’s Q4 adjusted EPS grew by 47.4% YoY to $0.28, beating estimates by 3.2%. GAAP EPS was in line with estimates of ($0.03) compared to ($0.04) in the same period last year.

Management Q1 adjusted EPS guide of $0.23 was lower than the estimates of $0.25. However, it implies a YoY growth of 43.8%.

Margins:

Q4 gross profits grew by 28.8% YoY to $452.5 million. Adjusted gross profits grew by 29% YoY to $460.18 million with an adjusted gross margin of 74.9%, down 270 basis points YoY and 40 basis points sequentially due to higher network expenses from the increase of paid customer traffic.

Q4 operating loss was ($49.2 million) compared to ($34.7 million) in the same period last year. Adjusted operating income grew by 33.3% YoY to $89.6 million with an adjusted operating margin of 14.6%, which was flat YoY and down 70 basis points sequentially and beat the guidance by 40 basis points. Management Q1 guide is 11.4%. The company reported $132.4 million in stock-based compensation in Q4, which explains the difference between GAAP and non-GAAP operating income.

Q4 net loss was ($12.1 million) compared to ($12.8 million) in the same period last year. Q4 adjusted net profit grew by 55.2% YoY to $106.8 million or 17.4% of revenue compared to 15% in the same period last year.

Cash:

Cloudflare’s Q4 operating cash flow grew by 49.6% YoY to $190.4 million with an operating cash flow margin of 31%, up 3 percentage points YoY and 1% QoQ. Similarly, free cash flows grew by 108% YoY to $99.4 million with a free cash flow margin of 16%, up 6 percentage points YoY and 3 percentage points QoQ.

The company had cash and available-for-sale securities of $4.1 billion, while convertible senior notes outstanding were $3.27 billion at the end of Q4 2025.

Valuation:

Cloudflare trades at a forward P/S ratio of 23.1. The company has traded at a minimum forward P/S ratio of 13.8 and a maximum of 41.4 in recent years. Cloudflare is currently trading slightly lower than mid-range. On the bottom line, it trades at a forward P/E ratio of 164.2. Cloudflare has traded at a minimum of 90.6 and a maximum of 277.3. Cloudflare is currently trading slightly lower than the mid-range on the bottom line too.

Notable Risks:

The slowdown in billings is an important data point, as it may point to softer demand trends and reduced momentum in future revenue growth. At the same time, the company remains unprofitable on a GAAP basis, which suggests the path to sustainable profitability may be longer than investors typically want from a software company.

Energy Stocks

Bloom Energy

The most important piece of information from Bloom’s Q4 earnings report was the company announcing its total current backlog at $20 billion, including $6 billion in product backlog, up 2.5X, and $14 billion in service backlog, up 1.5X.

The backlog was driven by “half a dozen” hyperscale and neocloud customers compared to one customer a year ago.

Bloom says the product backlog is attributable to its existing contractual commitments for purchases by a financier or customer in the future, including expected product revenue and anticipated ITC/tax incentives.

Product backlog grew 140% year-over-year. Service backlog includes revenue for contracted operation and maintenance services for past and future product sales, in terms ranging from five to 20 years, meaning this backlog will take much longer to convert.

Revenue:

Bloom Energy once again delivered revenue more than 20% above analysts' expectations, with Q4 revenue of $777.68 million beating the consensus estimate for $643.5 million by 20.5%. This represented 35.9% YoY growth, decelerating from 57.1% YoY growth in Q3; however, sequential growth was very strong at 49.8% QoQ, accelerating from 29.4% QoQ in Q3 – this is because Q4 is typically Bloom’s seasonally strongest quarter.

For the full year, Bloom reported record revenue of $2.02 billion, driven by significant AI data center growth and demand from commercial and industrial sectors. This represented 37.9% YoY growth.

For 2026, Bloom guided for a sharp acceleration to 58% YoY at the midpoint of its guide for $3.1 to $3.3 billion, supported by its capacity expansion towards 2GW. This is a notable 24% beat over the consensus estimate and also would represent just 16% of its total $20 billion backlog.

Product revenue was $638.5 million in Q4, up 35.4% YoY and 66.1% QoQ, though YoY growth did decelerate from 64.4% as Q4 faced a much tougher, seasonally strong comp. FY25 product revenue increased 41.1% YoY to $1.53 billion.

Installation revenue was $67.3 million in Q4, up 86.4% YoY, though this did decelerate from 105.2% growth in Q3. FY25 installation revenue increased 66.9% YoY to $204.1 million.

Service revenue was $61.7 million, up 14.7% YoY, decelerating slightly from 15.5% in Q3. FY25 service revenue increased 6.9% YoY to $228.3 million.

Electricity revenue did reaccelerate in Q4 but growth continued to decline. Q4 revenue declined (5.3%) YoY to $10.2 million, improving from Q3’s (25.1%) decline. FY25 electricity revenue was $60.3 million, up 14.2%.

Margins:

Bloom’s margins showed a sharp sequential rebound in Q4 but remained lower on a YoY basis.

Bloom reported GAAP gross margin of 30.9% in Q4, down 7.4 points YoY but up 1.7 points QoQ. Adjusted gross margin was 31.9%, also down 7.4 points YoY but up 1.5 points QoQ.

GAAP operating margin was 11.3% in Q4, down 7 points YoY but up 9.8 points QoQ. Adjusted operating margin was 17.1%, down 6.2 points YoY but up 8.2 points QoQ. Bloom noted that it continues to focus on reducing product cost and driving operating leverage, which will likely be much more visible in 2026 based on its current guide.

GAAP net margin was 0.1% in Q4, down 18.2 points YoY but up 4.5 points QoQ – to note, Bloom incurred a $66.2 million debt conversion expense charge that negatively impacted GAAP income this quarter. Adjusted net margin was 17.2%, down 3.5 points YoY but up 10.4 points QoQ.

Earnings:

Bloom reported GAAP EPS of $0.00 in the quarter, though adjusted EPS saw a large 50% beat, coming in at $0.45 versus the $0.30 estimate.

Cash:

Q4 is seasonally Bloom’s largest quarter for cash flows, with operating and free cash flow margins in excess of 50% this quarter, though this was much lower than the >80% margins it reported in Q4 2024. However, these large margins simply offset weak cash flows in the rest of the year, with full-year margins in the single-digit range.

Operating cash flow was $418.1 million in Q4 for a 53.8% margin, down from an 84.6% margin in the year ago quarter.

Free cash flow was $395.1 million in Q4 for a 50.8% margin, down from an 82.7% margin in the year ago quarter.

Bloom reported $2.45 billion in cash, though debt rose to $2.61 billion, as Bloom raised $2.5 billion in convertible notes while also paying down $975 million in existing debt in the quarter.

Valuation:

Bloom Energy is currently trading at a peak forward P/S ratio of 19.1. The company has traded at a minimum of 1.4 in February 2024. On the bottom line, the company trades at a forward P/E ratio of 157.9. The company has traded at a minimum forward P/E ratio of 28.8 and a maximum of 462.4 in recent years.

Notable Risks:

Due to the strong stock outperformance of 1,180% in the past year. Bloom Energy is currently trading at a peak forward P/S ratio of 19.1 and leaves with less room for error if growth or guidance falls short of expectations.

GE Vernova

GE Vernova exited 2025 with one of the strongest AI demand and backlog profiles in the energy industry. In Q4, management emphasized accelerating slot reservations, rising pricing, improving backlog margins and multi-year visibility extending into the end of the decade.

The company signed 6GW of incremental gas contracts in the final three weeks of December, bringing total Q425 contracts to about 24GW. As a result, the Gas Power backlog plus slot reservation agreements (SRAs) expanded from 62GW to 83GW sequentially.

Management now expects to reach 100GW under contract in 2026, an upward revision from the 60GW discussed in mid-2025. Notably, the current 83GW under contract is heavily allocated toward 2029 delivery. By the time that 100GW is reached, both 2029 and 2030 capacity will be sold out.

Revenue:

GE Vernova Q4 revenue grew by 3.8% YoY to $10.96 billion, beating estimates by 7.1%, driven by rising AI energy demand. Organic revenue grew by 2% YoY to $10.8 billion. The company is a major beneficiary of the increasing energy requirements from the global AI infrastructure build-out, positioning the company as a key beneficiary of this secular trend. The continued slowdown in the Wind segment was offset by the growth in power and electrification segments that are benefitting from rising electricity consumption driven by data centers and artificial intelligence demand.

AI Revenue:

Q4 power orders increased 77% YoY to $11.7 billion, driven primarily by a sharp acceleration in gas power equipment orders, which more than tripled on higher volumes and favorable pricing. Gas turbine orders rose 71% YoY to 41 units, while power services orders grew 15%, reflecting continued customer investment in existing fleets.

Q4 power segment revenue grew organically by 5% YoY to $5.7 billion. Management expects high single-digit organic growth in Q1.

Electrification orders were 2.5x revenue and were up 50% YoY to $7.4 billion primarily due to growing grid equipment demand, particularly for synchronous condensers, substations partially to support data center growth and switchgear. The company also witnessed strong equipment orders growth in the Middle East, which increased over $1 billion and in North America, which more than doubled YoY.

Q4 organic electrification revenue grew by 32% YoY to $2.9 billion primarily driven by strong growth in switchgear and High-Voltage Direct Current (HVDC) equipment. Management expects a similar revenue as Q4 in the next quarter, which will also include Prolec GE.

Due to a sudden surge in AI-related electricity demand, the company’s turbine orders are vastly outpacing demand, and the company’s order book is sold out through 2028.

Margins:

The company’s Q4 adjusted EBITDA grew by 7.3% YoY to $1.16 billion with an adjusted EBITDA margin of 10.6%, an improvement of 250 basis points sequentially and 40 basis points YoY. Organic adjusted EBITDA margin improved 10 basis points YoY to 10.7%.

Q4 net income was $3.7 billion or 33.5% of revenue compared to $484 million or 4.6% of revenue in the same period last year. The Q4 net income included a one-time tax benefit of $2.9 billion.

Earnings:

Q4 GAAP EPS was $13.39, up from $1.73 in the prior-year period, reflecting a one-time tax benefit of $10.58. Excluding this benefit, GAAP EPS would have been $2.81, below the consensus estimate of $3.13, primarily due to losses in the Wind segment.

Cash:

The company’s cash flows are improving driven by growth in profits and also improvement in working capital.

Q4 operating cash flows grew by 169% YoY to $2.48 billion with an operating cash flow margin of 22.6% compared to 8.7% in the same period last year. The company benefitted from down payments on higher orders and slot reservations at Power as well as higher orders at Electrification.

Q4 free cash flow grew by 214.7% YoY to $1.8 billion with a free cash flow margin of 16.5% compared to 5.4% in the same period last year.

The company had cash of $8.85 billion and no debt at the end of Q4. In February, the company issued $2.6 billion of debt and completed the previously announced acquisition of the remaining 50% ownership stake of Prolec GE.

Valuation:

GE Vernova is currently trading at a peak forward P/S ratio of 6.0. The company has traded at a minimum forward P/S ratio of 0.96 in April 2024. On the bottom line, the company is trading at a forward P/E ratio of 69.4. The company has traded at a minimum of 38.5 and a maximum of 136.7 in recent years. GE Vernova is currently trading slightly lower than the mid-range on the bottom line.

Notable Risks:

The ongoing weakness in the wind segment is to be watched. That said, management expects a meaningful recovery in the wind business to materialize in the second half of 2026.

NextEra Energy

NextEra has traditionally been known as a regulated utility with a renewables development arm, yet is pivoting to become one of the few companies in the United States that can build power infrastructure at large scale across renewables, storage, gas, transmission and potentially nuclear. As you’re well aware, data center demand is insatiable, and NextEra’s ability to work across two growth engines is poised to benefit: Florida Power and Light provides the large, regulated utility platform while the Energy Resources solutions (NEER) provide renewables and storage. This can help break NextEra out of the bucket of being a passive beneficiary of load growth and into a builder that is enabling critical data center growth. In other words, NEE is pivoting toward being one of a handful of credible, large-scale solutions for the power demands of AI.

Revenue:

NextEra Energy’s (NEE) Q4 2025 revenue grew by 20.7% YoY and down (18.4%) QoQ to $6.5 billion. Revenue growth accelerated by 15.4 percentage points from 5.3% YoY growth in the previous quarter. The company is a beneficiary of AI data center energy demand. The Q4 sequential decline was seasonal as the company’s Q4 2024 revenue was down (21.7%) YoY and (28.8%) QoQ.

During the Investor Day in December, management said they expect to develop data center hubs totaling 15 GW to 30 GW by 2035, and they reiterated this guidance during the Q4 earnings call. They have already identified 20 potential hubs and expect to identify 40 by the end of 2026.

Margins:

The company’s Q4 operating margin improved YoY, primarily driven by operating leverage.

Q4 operating income was $1.59 billion or 24.4% of revenue compared to $941 million or 17.5% of revenue in the same period last year.

Q4 net income was $1.54 billion or 23.6% of revenue compared to $1.2 billion or 22.3% of revenue in Q4 2024.

Q4 adjusted net income was $1.13 billion or 17.4% of revenue compared to $1.1 billion or 20.3% of revenue in the same period last year.

Earnings:

The company’s Q4 adjusted EPS grew by 1.9% YoY to $0.54. Analysts expect Q1 adjusted EPS to be down (2.3%) YoY to $0.97 and expect adjusted EPS growth to accelerate to 5.6% and 12.4% in the subsequent two quarters.

Looking ahead, analysts expect adjusted EPS to grow by 8.2% YoY to $4.01 in 2026 and 9% YoY to $4.37 in 2027. During the Q4 earnings, management reiterated its guidance set at Investor Day in December to grow adjusted EPS at a CAGR of 8% from 2025 to 2032 and at the same rate from 2032 to 2035.

Cash:

The company has steady operating cash flows. However, due to high capex, there is a wide difference between operating cash flow margin and free cash flow margin.

Q4 operating cash flow was $2.5 billion or 38.4% of revenue compared to $1.98 billion or 36.8% of revenue in the same period last year.

Q4 free cash flow was $519 million or 8% of revenue compared to $204 million or 3.8% of revenue in Q4 2024.

The company had a high debt of $95.6 billion compared to cash of $2.8 billion at the end of Q4 2025. The company recently priced a $2.3 billion offering of equity units on March 3. The hybrid security will consist of a contract to purchase the common stock in about three years and undivided beneficial ownership interests in two series of debentures issued by NextEra Energy Capital Holdings. It provides the company with immediate liquidity while deferring common equity dilution for approximately three years.

Valuation:

NextEra Energy is currently trading at a forward P/S ratio of 6.1. The company has traded at a minimum forward P/S ratio of 4.2 and a maximum of 6.5 in recent years. NEE is currently trading slightly higher than the mid-range. On the bottom line, it trades at a forward P/E ratio of 23.1. The company has traded at a minimum forward P/E ratio of 16.1 and a maximum of 25. NEE is currently trading slightly higher than the mid-range on the bottom line too.

Notable Risks:

The company has high debt of $95.6 billion compared to cash of $2.8 billion at the end of Q4 2025.

Conclusion:

The 70-page report is not meant to explain the AI market or what AI companies do. Plenty of commentary already does that. Rather, the report and our I/O Fund Research site are designed to help our members act before the rest of the market catches up. What we offer is execution; not merely information.

The AI trade is evolving, but the opportunity is far from over. If anything, the next phase will prove even more important as leadership broadens and the market becomes more selective. I can’t think of a better team to take on this challenge.

Outsized returns will come not from following the crowd, but from being positioned ahead of it. That requires more than information. It requires judgment, discipline, and the willingness to act before consensus fully forms. Previous Quarterly Top 15 reports identified Bloom, Lumentum and AAOI early in their cycles, and the same discipline that found those names is driving this report.

Our earnings season officially kicks off on Wednesday – Let’s go!

Royston Roche and Damien Robbins, Equity Analysts at I/O Fund contributed to this analysis.

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The I/O Fund’s Top 15 Stocks for Q1 2026

Posted on January 29, 2026June 30, 2026 by io-fund

The stocks selected for the Q1 report passed stringent tests for technical positioning, competitive advantage, and underlying fundamentals. Before presenting the list, I also revisit the trends driving the AI market—as you’ll see, much has changed in just three months.

Despite these trends being long-term bullish, the team at the I/O Fund fully accepts the inevitable downturns that characterize not only technology, but the growth markets that historically drive a disproportionate share of returns.

For example, last year Nvidia reported mild returns, and did not even beat the broader semiconductor sectors SMH and PHLX, despite continuing to offer some of the strongest fundamentals the market has ever seen (the keyword here is “continuing”). The market is clearly not static and requires a level of discipline that comes naturally to the analyst team at the I/O Fund.

On the topic of investment discipline, what you have in your hands is a 61-page report totaling over 24,000 words – nearly a novel. What drove this report is a mind-numbing amount of due diligence on the stocks included in the report, but also those we passed on.

Below are the I/O Fund’s Top 15 AI Stocks for Q1 2026 and the trends driving the AI market forward.

Reference our Q4 2025 AI Stocks list here and our Q3 2025 AI Stocks list here.

Top 3 Emerging AI Trends for 2026-2028

#1 Networking Shifts with Rubin, Yet Importance Remains

As you’ll recall from our previous coverage, Blackwell and Blackwell Ultra are fundamentally a networking problem. We began to form this thesis nearly a year ago with non-stop AI networking coverage, and we have ample evidence the thesis is playing out.

Nvidia’s networking segment surged again this past quarter to 162% growth YoY and was up 13% QoQ for $8.2 billion in revenue. We began to see initial signs last quarter from Nvidia with 78% growth YoY and was up 46% QoQ.

This represents an acceleration of 84 percentage points from 78% YoY growth in Q2, driven by NVLink scale-up, Spectrum-X Ethernet and Quantum X-InfiniBand. For Nvidia’s systems, there is a 75% attach rate which leaves about 25% for smaller networking vendors – therefore, even though this growth is driven by Nvidia’s proprietary networking stack, the growth rates are directionally aligned with smaller players, as well.

As discussed in last quarter’s Top 15 AI Report, Nvidia’s Blackwell architecture drives a new growth trajectory for AI networking, as it requires 5× to 9× more networking components for 72-GPU and 36-CPU systems to operate as a single node. Because these systems are now shipping in volume, the current networking stack largely reflects the companies capturing this demand. As a result, it is reasonable to expect growth rates among the highest-growth networking stocks to remain healthy over the next one to two quarters.

Rubin Redefines AI Networking as a Bandwidth-First Constraint

Inside the Rack: The Copper-to-Optics Boundary

However, as we turn our attention to the Vera Rubin generation, there is a notable shift in the networking stack. While copper-based links remain essential for short-reach, low-latency connections—particularly within NVLink scale-up domains—the expansion of Ethernet fabrics, higher port counts, and the adoption of co-packaged optics are driving an inevitable shift toward optical content.

Further necessitating a need for higher bandwidth is Rubin’s “extreme co-designed” nature, as CEO Jensen Huang puts it, where “GPUs, CPUs, networking, security, software, power delivery, and cooling are architected together as a single system rather than optimized in isolation” to deliver substantial performance upgrades for inference, such as a 5X increase in FP4 performance with just a 1.6X increase in transistor count on Rubin’s GPU.

The increasing amount of computing nodes (especially as Nvidia pushes towards the NVL576 with Rubin Ultra) along with increasing amount of interconnects means that bandwidth must also increase, from 400G to 800G and now to 1.6T, to ensure that low-latency, high-throughput communication remains across the entire platform.

With Rubin, Nvidia is doubling NVLink scale-up bandwidth over Blackwell with its sixth-gen NVLink 6 interconnect, offering 3.6 TB/s of bidirectional bandwidth for GPU-GPU communication and 1.8 TB/s for GPU-CPU communication.

This is accomplished with 36 NVLink 6 switches, deployed as a full all-to-all fabric across the NVL72 rack, delivering 2X throughput for inference at scale with total bandwidth of 260 TB/s per rack, versus Blackwell’s 130 TB/s.

Source: Nvidia

Packing more NVLink switches per rack (18 in Blackwell to 36 with Rubin) and doubling bandwidth emphasizes Nvidia’s goal of maximizing scale-up bandwidth to deliver increasing throughput and inference performance gains.

However, the content opportunity for copper and AECs may slowly erode at the copper-to-optics boundary as the design goal with Rubin is to bring Ethernet closer to the switch, in a shift that favors silicon photonics over time, first through shorter electrical reaches and earlier optical transitions, and eventually through architectures such as CPO, while leaving copper relevant at the shortest distances.

The industry remains favorable on copper in the near future, with Broadcom CEO Hock Tan saying that the industry will “try to do scale-up within a rack in copper as long as possible” but the shift to SiPho at the electrical-optical transition point appears to be inevitable. Therefore, copper is not going away, rather it faces a lower attach rate. This is due to copper’s reach limitations and needing GPU systems to scale further with a low power, low latency and high bandwidth solution.

For Credo, the company is expanding its presence into optics as well with its ZeroFlap Optical DSPs and transceivers, though it faces potential decreasing AEC content.

Scale-Out: CPO Signifies the Shift Toward SiPho

For scale-out networking, Nvidia announced its new NVIDIA Spectrum-X Ethernet Photonics switch, which it says will deliver 10X greater reliability with co-packaged optics (CPO), bringing 1.6T silicon photonics (SiPho) optical engines directly onto the switch. Maximum bandwidth is also doubled to 102.4Tb/s per ASIC, matching Broadcom’s new Tomahawk6 switch, though Nvidia is also offering the industry’s first four-ASIC design, delivering 409.6Tb/s bandwidth.

The push towards the new Spectrum-X Ethernet switches will reduce reliance on traditional pluggable transceiver designs. There are a few main advantages this architectural shift: it eliminates the need for digital signal processing (DSP) retimers, reducing latency, and it reduces network power, driving up to 5X better power efficiency with a lower cost versus pluggable transceivers.

It also will drive increasing content for the SiPho-laser ecosystem and CPO photonics components, as SiPho will serve as the backbone for the CPO switches. This extends beyond the photonics ICs to include CW lasers, ultra-high-power (UHP) lasers for external light source (ELS) modules, fiber array units, optical interconnects, and more.

PCIe Remains Relevant from Nvidia’s “Extreme Co-Design"

Inside the server, PCIe remains firmly intact. Growth should persist as PCIe continues to serve as the foundational interconnect for intra-server connectivity between GPUs, CPUs, DPUs, NICs, and NVMe SSD storage.

This directly ties back to Nvidia’s “extreme co-design” philosophy. As Rubin brings multiple compute, networking, and memory components together into a single, tightly integrated platform, the need for rapid, low-latency data movement within the server increases—therefore, it is our understanding PCIe as the connective tissue does not decrease.

This extends further with Nvidia’s move to PCIe Gen6 alongside expanded CXL support on its Vera CPU, up from PCIe Gen5 on Grace. CXL enables low-latency, high-bandwidth memory and cache sharing between CPUs, GPUs, and attached memory devices, reinforcing PCIe’s role at the heart of the system architecture. PCIe fabric switches are also expected to remain critical for backend GPU-to-GPU communication and for linking CPUs, NICs, and storage at scale.

#2 AI Energy: AI's Biggest Bottleneck

The AI market has moved from being compute-constrained to being energy constrained. Hyperscalers have access to GPU supply, making the limiting factor how quickly those GPUs can be energized and deployed.

As we’ve discussed in our analysis, Why Power is Critical for Data Centers and their Hyperscaler Customers, every month that GPUs sit idle waiting for power delays – revenue, profits and market share can be affected. This is especially true given GPU generations refresh annually and is driving significantly higher power requirements.

For the energy section, I break down both the problem and the solution — each central to how we plan to position heading into 2026. Many of these energy solutions have existed for decades yet are now experiencing a resurgence in product-market fit driven by rapid AI data center expansion. For that reason, even if we have already covered the scale of AI data center investment, it is critical to double-click on why energy has become the bottleneck nearly overnight.

The Problem:

Nvidia’s Blackwell lineup is bringing a significant increase in power consumption, nearly double the H200’s 70 kW at 120 kW for the GB200 NVL72 and 140 kW for the upcoming GB300 racks.

Beyond Blackwell, Nvidia’s future design lineup shows continual increases in power consumption. Its Vera Rubin generation is expected to boost thermal design power (TDP) by 50% over Blackwell at up to 180 kW to potentially 230kW per rack, with the Rubin Ultra boosting this to 600kW by late 2027.

In its largest configuration, the Vera Rubin NVL576, dubbed the ‘Kyber’ rack, could draw as much as 600 kW (0.6 MW), or 5x that of the GB200 NVL72 in just a two-year design timeframe. These figures do not include networking, interconnects, cooling and other hardware, which will further boost power draw per rack.

Existing data center infrastructure is largely incompatible with next-gen AI. Nearly 70% of data centers were built for 4-9kW racks with fewer than 2% able to handle even 50kW, which is forcing new construction and major retrofits.

Furthermore, there exists a significant disconnect between when hyperscale and colocation developers expect to have site power, and when utilities expect to be able to deliver said power. Connecting new data centers to the grid in quick fashion may not be the most feasible option for hyperscalers looking to deploy gigawatts of capacity quickly, and instead, alternative power sources may be in higher demand.

For example, across the board, developers are expecting to have power delivered by late 2026 to early 2027 on average, with most regions seeing expectations as early as late 2025. This is likely driven by consistent strong demand for AI infrastructure services, as new capacity will allow hyperscalers to meet more demand and drive more revenue.

Most importantly, the AI race is not merely a battle between companies like Google, Amazon and Microsoft. Rather, it is a battle among global powers. While the news has latched onto China-fears such as DeepSeek, tariffs or rare earth materials, and H200 bans (that are later lifted), the true challenge lies in the fact that China has significantly more power than the United States.

In a recent Fortune article, energy experts stated China’s reserve margin has never dipped below 80% to 100% nationwide, meaning it’s at 2X the capacity the country needs. Meanwhile, the United States is at a 15% reserve margin. The article states, “The gap in readiness is stark: While the U.S. is already experiencing political and economic fights over whether the grid can keep up, China is operating from a position of abundance.” Specifically, the article calls out that large-scale infrastructure projects depend heavily on private investment, yet returns can take years and up to a decade to pay off. Meanwhile, private investors greatly prefer software with returns realized on a much shorter timeline.

Therefore, there are dual forces placing outsized pressure on this trend – not only is the AI data center expansion physically dependent on power availability and it is now the bottleneck, but one could argue that United States global dominance is also highly dependent on this sector. The United States undeniably has the world’s best design companies with Nvidia, AMD, Broadcom and soon TSM will be on our soil. We also have the best software companies – from Big Tech to the entrepreneurial culture of our country with startups coast to coast.

What the United States doesn’t have is enough power.doesn’t have is enough power.

The Solution:

The bottleneck has shifted from compute supply to energy. As a research firm, we want to be early in providing you analysis on the companies that solve this problem, as energy determines the timing and economics of AI deployment.

The disconnect described above is driving demand for behind-the-meter power, on-site natural gas turbines, fuel cells, nuclear and SMRs in the long-term and retrofitted Bitcoin mining sites. Each GW of AI data center capacity costs roughly $30 to $38 billion all-in, which puts total required capex into the trillions this decade.

Compute still remains the bulk of the data center spend (i.e., the overall pie), however, energy is growing its slice of the pie. Breaking it down on a MW basis, Alpha Matica, an AI consultant company that specializes in AI, states electrical systems are 50% of the initial construction costs which range from $900M to $1.5B per 100MW.

There are multiple different ways that hyperscalers, neoclouds and developers can get power to data centers to meet upcoming demand growth over the next few years, each offering its own benefits and drawbacks.

Grid interconnection: This is when data centers connect to the power grid under standard service, providing access to flexible power needs with no additional capex and a wide range of power generation options, including renewables. However, grid interconnection requests are often the longest time to power, ranging from three to seven years for hyperscale data centers in most key markets.

Behind-the-meter: How Power is Contracted can offer a time to power advantage

BTM refers to when data centers connect directly to the power source and bypass the retail grid (meter) and associated tariffs, which can offer significant time advantage with stand-up times often in the range of several months to a year, along with cost savings from buying power direct versus at retail price.

BTM arrangements also provide greater control over power supply and reduce exposure to grid outages. These deals can be structured across multiple power sources, including solar, wind, nuclear, and natural gas.

On-site power generation: Where Power is located can offer time to power benefits and is increasingly becoming attractive to AI data centers

With on-site power, data centers will install their own power source within the facility grounds or adjacent, also offering a relatively quicker time to power of a few months to over a year as this bypasses the need for a grid connection and transmission upgrades.

These solutions are modular and designed for rapid installation, as they can be manufactured off-site and be built in parallel with a data center. This also offers the benefit of foregoing regulatory risks and delays that come with grid connections. Controlling the timeline can be a significant asset for the reasons described above in terms of when increasingly-power-hungry GPUs are shipped.

In addition, grids are designed for lower, flatter power loads and gradual increases. With Blackwell Ultra, Rubin and Rubin Ultra on the product road map through 2027, data centers need ultra-dense loads and to scale power locally without overwhelming the grid. In addition, as discussed above, time-to-power is technically time-to-revenue, and thus, circumventing the grid as much as possible is the aim.

Lastly, on-site power is seen as more reliable as it’s not subject to grid failures. This is why on-site backup power sources are also becoming a major growth market.

On-site power can come in many forms, such as Bloom’s fuel cells, natural gas turbines or generators such as those from GE Vernova or Caterpillar, and in the 2030s and beyond, potentially small modular nuclear reactors. These power sources are discussed more below.

Natural gas turbines/generators: Behind-the-meter and on-site

NG is a widely available fuel source with a broad pipeline in the US, offering continuous power to data centers. Turbines can come in a range of sizes and be easily deployed, such as Caterpillar subsidiary Solar’s SMT-130 turbines that xAI is using, or GE Vernova’s LM2500XPRESS that Crusoe is using, scaling up to 1GW capacity. Notably, NG turbines could help meet substantial future demand, as GE Vernova is expanding manufacturing in South Carolina to be able to ship 20 GW worth in 2027. Large (>225MW) turbines are reportedly sold out over the next three years.

Fuel cells: Behind-the-meter and on-site

Similar to NG, fuel cells can be quickly deployed (in as little as three months per Bloom and Oracle’s deal), and provide continuous power for operations. Due to being a relatively newer tech, SOFCs can come at a higher cost than NG, but without the related emissions. Bloom is planning to double its SOFC manufacturing capacity to 2GW in 2026 to meet rising on-site power demand.

Small modular reactors: Not behind-the-meter right now (will be around 2030) and on-site or near-site

SMRs are drawing more interest for future demand needs, as commercialization at scale is not likely until 2030 or beyond. Google is working with Kairos to bring 0.5 GW of SMR capacity online from 2030 through 2035, while Oklo and NuScale are progressing with commercialization plans and a long-term combined ~20 GW backlog.

Retrofitting existing infrastructure, i.e. Bitcoin mining: How power is contracted and delivered is nuanced (see below); effectively on-site

Miners leverage existing infrastructure with secured power to the building, offering quick delivery times as short as a few weeks to a year, depending on cooling, flooring or other upgrades needed. Overall, the value proposition of Miners is that they are cheaper and faster than new, greenfield data center sites.

Bitcoin mining is not behind-the-meter in a strict sense, but it is effectively behind-the-meter because miners secure direct, wholesale power through upfront contracts that are not renegotiated.

They are considered on-site power as there is minimal transmission dependency due to co-locating near a mix of power sources (near gas plants, augmented by wind, solar, water/hydro). In most cases, even if a utility meter exists, the power system is purpose-built for that site and is not shared retail infrastructure.

While this method can offer quick time to power for >100MW sizes with low latency, low electricity costs and cooling expertise compared to greenfield projects, miners are capital constrained and may be unable to build-out capacity beyond what is currently in their pipelines. For example, they are not suitable for training a frontier model.

Miners have been attracting substantial deal activity, primarily from neoclouds, from an ability to deliver larger chunks of power quickly, with capex costs well below greenfield builds.

Click here for our most recent full write-up on Why Power is Critical for Data Centers and Their Hyperscaler Customers. The I/O Fund first covered this topic in June of 2024, many quarters before the problem became well-known. We furthered this by investing early in a Bitcoin miner and one of the year’s highest-performing AI energy stocks.Why Power is Critical for Data Centers and Their Hyperscaler Customers. The I/O Fund first covered this topic in June of 2024, many quarters before the problem became well-known. We furthered this by investing early in a Bitcoin miner and one of the year’s highest-performing AI energy stocks.

#3: The Incoming AI Inference Market (i.e., the AI Boom Hasn’t Happened Yet)

As you’ve likely noticed, we have been writing 10,000-foot level analysis on the AI inference phase, which is synonymous with the Monetization Phase for AI. The last few years have been marked by intense R&D and high compute costs, yet the economic reality is that training large language models is an initial research stage, and this is not the stage to expect recurring revenue and expanding profits.

Rather, it is my assertion that AI development is nearing a crux where peak capex spending intersects steeply with low ROI. However, to call this a bubble or to claim that AI does not drive enough revenue in exchange for the hundreds of billions being spent on data center expansion is to assume we are in the final stages of AI rather than the early stages. The AI market will take off when the inference phase fully arrives – my estimates are 2027-2028 for this. However, as you know by now, the I/O Fund has no intention of being late to this trend.

The aggregators and distributors for AI – whether that’s Big Tech, best-of-breed software companies, or enterprises that are already using AI to increase profits will be able to fully leverage LLMs and AI automation once AI inference becomes faster and cheaper. It is a mix of hardware and software that will achieve this, and we will want to assess this market carefully as the inference opportunity is expected to exceed the training market in both size and velocity. You can expect to hear extensively from us on this trend over a 2-3 year time period.

For now, what is most important is to track some of the hardware companies that are unlocking this opportunity. We want to understand the “why” behind Nvidia’s Vera Rubin architecture, the “why” behind AMD’s Helios and the “why” behind Broadcom’s rise in custom silicon. The breadcrumbs are crucial for positioning correctly into H2 2026 and 2027.

We will also highlight select software opportunities with the understanding that timing may be early. In these cases, price action will play a decisive role. That means if we see a breakout or strength in the chart align with product, we will move accordingly.

Memory:

Memory's medium-term thesis is based on the shift from training to inference. Inference workloads require only a forward pass, making them significantly less compute- and power-intensive than training. However, to achieve low latency, especially at small batch sizes, models must remain resident in device memory, which shifts the primary bottleneck from compute over to memory capacity and bandwidth.

Forward pass refers to taking an input and pushing it through a trained neural network. No learning occurs and no weights are updated. Rather, input tokens are embedded – which requires frequent memory access, yet this step has low compute requirements. Attention layers read fixed, pre-trained model weights, and the GPUs repeatedly read the weights from memory. From there, KV cache grows with usage to where the longer the conversation, the larger the KV cache. While reading from the KV cache reduces redundant computation, it materially increases memory capacity and bandwidth requirements.

The point of the above paragraphs is to help illustrate the technical shift toward memory for the inference workloads, whereas compute requirements on a relative basis become reduced.

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Top 15 Stocks List

Section 1: AI Accelerators

AI accelerators are technically the #1 trend in the AI market by size, and in my opinion, offer a solid way to participate with lower risk than other AI trends over a longer-time frame. While we did not rank accelerators among our Top 3 themes, given that other areas of the market offer higher near-term growth rate, that should not be mistaken for a lack of structural strength.

As last year illustrated, keeping up on the ins/outs can be advantageous given AMD outperformed Nvidia with 3X higher returns whereas Nvidia underperformed its sector. I review this in more detail below.

Additionally, in a similar way that doctors check vital signs, we revisit capex ahead of earnings and immediately following Big Tech earnings as this remains a critical signal to the strength of the AI market. One day, we will be tracking enterprise AI spend and sovereign AI. However, those markets are not large enough to offset Big Tech’s investment levels for many quarters (if not years). Therefore, the customer concentration works in our favor as these particular customers must disclose their budgets in their quarterly filings.

Capex signals from Big Tech/hyperscalers (Microsoft, Meta, Alphabet, Amazon, Oracle) are projected to be around $435 billion for 2025, while initial estimates for 2026 capex are around $583 billion, up approximately 34% YoY. On a dollar basis, this points to an initial estimate of ~$148 billion in growth, versus ~$173 billion in 2025, signaling AI demand is poised to continue. 

Keep in mind, capex estimates for 2025 started out much lower – estimates entered the year at about $320 billion, or more than $100 billion short of where the year ultimately ended. Therefore, the same could be true for 2026 to where capex ultimately ends up higher by year-end — some analysts are already penciling in the five to spend more than $600 billion next year, which could mean absolute dollar growth on a YoY basis this year surpasses 2025.

Nvidia: Greater Emphasis on Memory

Overview:

There are two primary factors to track when assessing Nvidia’s path toward a potential $20 trillion market capitalization by 2030. The first is the cadence of GPU generations and the product road map, which when executed well, supports higher average selling prices and drives system-level expansion in data centers. The second is analyst estimates, which when conservative, can create opportunities for valuation upside as expectations are forced to reset.

Jensen Huang spoiled the CY2026 alpha party by stating that management has a line of sight to $500 billion across two years from Blackwell and Rubin. Our firm had already stated we would see over $300 billion this calendar year, and that statement puts Nvidia’s revenue squarely at our estimate. Nvidia resuming H200 sales could perhaps bump that up 10% to 20% – not chump change for a stock this size yet a bit boring for I/O Fund’s purposes.

From there, things get interesting. If we look at calendar year 2027, we see 27% growth estimated to $409 billion. If we look at calendar year 2028, we see only 8.4% growth to $443 billion. Yet in the 27% growth year we will see Rubin Ultra, a 144-GPU AI system that will shatter all previous records on training frontier models as it tests the upper limits of the amount of compute, memory and networking that can function as a single node. In terms of what is accomplished on the inference side, quite a bit depends on how memory and networking evolves over the next 1-2 years to improve efficiency at the system-level.

Let’s say we get to CY2028 and Nvidia growth flatlines – what would cause this? While the broader market likely anticipates it will come from the pace at which compute can be monetized, yet the more likely cause would be power availability first and foremost, but also deployment complexity, as we saw from the meaningful delays in Blackwell’s 72-GPU systems.

In the more near-term, 2026 is shaping up to be a year where Nvidia is firing on all cylinders. Vera Rubin was officially launched at CES and is an architecture that opens doors for the impending inference market. Jensen Huang calls the Rubin “extreme co-design" across six elements– CPUs, GPUs, NVLink, Ethernet, DPUs and NICs – with this generation more focused on memory movement and networking than the architectures in the past (which were centered around raw compute).

The Rubin architecture delivers substantial performance gains at the system level, with up to ~5× improvements in inference and ~3.5× in training relative to prior generations (as always, this depends on workload and configuration).

A key driver of these gains is a significant expansion in memory capacity and bandwidth, with Rubin designed to support up to roughly 288GB of HBM-class memory per GPU and materially higher memory bandwidth. This addresses one of the primary bottlenecks in inference: memory access and data movement.

To support this shift, Nvidia is focusing on the context memory window, which refers to the memory used to store and access the model during inference. The key-value (KV) cache is a memory mechanism used in transformer models to store attention keys and values from prior tokens. This allows models to reuse previous computations and reduce latency from increased memory usage.

In a Discovery tier article where we covered a major memory beneficiary of the KV cache increase, it was stated the KV cache has a substantial memory footprint, and during deployment it can consume 30% of GPU memory, making it a major bottleneck for large-context applications, such as coding, natural language processing, or handling simultaneous requests from many users on large models.

In day-to-day use, the key-value cache is the memory that lets LLMs remember what’s already been said so it doesn’t have to rethink everything for each query. Each new response then builds on the stored context instead of recomputing the conversation again. When you use ChatGPT or Claude, the prior context is stored in the KV cache rather than relying on repeated compute.

With the Rubin generation, by expanding the KV cache capacity, Nvidia greatly reduces the need for recomputation, and redirects resources to memory capacity, bandwidth and data movement to improve throughput and responsiveness.

This becomes even more important in agentic AI systems, where models operate autonomously across multiple inference steps rather than responding to a single prompt. Agentic workflows require longer context windows and sustained access to KV cache as agents reason, plan, and act across extended sequences.

As a result, memory and networking increasingly determine real-world inference performance and scalability as opposed to raw compute. This marks a shift for Nvidia – and one we argued years ago would open the door to more competition in AI accelerators as we exit the training-dominate phase and we approach the inference-driven monetization phase.

Overall Revenue Growth:

Nvidia’s Q3 rev grew by 62.5% YoY and 22% QoQ to $57B. Revenue growth accelerated by 6.9 percentage points from 55.6% YoY growth reported in Q2. Revenue beat estimates by 3.5% and is the strongest beat in the last four quarters.

Management also provided a strong Q4 rev guide of $65B billion, YoY growth of 65.3% and up 14% QoQ. Beat the estimates by 5.1%.

Nvidia’s total supply-related commitments, such as for CoWoS wafers, HBM memory, or other components, surged nearly 52% QoQ to $50.3 billion in Q3, with management noting that they are “ordering to secure long lead-time components, meet the demand for Blackwell, and support future architecture ramps.”

Where the disconnect happens with analyst estimates is what will happen after next year as this is where analyst estimates show minimal growth through 2030 revenue with $437 billion whereas I am calling for double that by 2030. While Blackwell Ultra gets us to a new milestone of $50 billion to $75 billion quarterly revenue, quite a bit of my thesis depends on Vera Rubin, Rubin Ultra and the Feynman generations – not only execution on Nvidia’s side but also power availability is crucial.

AI Segment Growth:

Data center rev grew by 66% YoY and 25% QoQ to $51.2B. Rev growth accelerated 10 percentage points from 56% growth reported in Q2. Management sounded confident to achieve the $500B target in Blackwell and Rubin revenue set for FY2026/27 and hinted it could be more. Networking rev grew by 162% YoY and 13% QoQ to $8.19B. Rev growth accelerated by 84 percentage points from 78% in Q2. Largest QoQ growth in about two years (and done at scale).

Nvidia’s guide pointed to this momentum continuing into the fourth quarter, implying that data center revenue could be on track to rise another $8 billion QoQ for 15% growth. Management repeated they “currently have visibility to $0.5 trillion in Blackwell and Rubin revenue from the start of this year through the end of calendar year 2026.”

Q4’s guidance suggests that this $50 billion data center segment will quickly be in the rear view mirror, with the $65 billion guidance implying data center revenue of around $59 billion assuming similar mix shift as Q3. This represents another 15% QoQ growth on top of Q3’s 25%, or essentially the data center segment rising nearly 44% in just two quarters.

Earnings:

Q3 adjusted EPS grew by 60.5% YoY and 23.8% QoQ to $1.30, beating estimates by 3.5%.

Looking forward, analysts expect FY2027 adjusted EPS to grow 49.5% YoY to $6.83 and 26.7% YoY to $8.65 in FY2028.

Margins:

Q3 GM was 73.4%, beat the guidance by 10 bps. Q4 GM guide is 74.8%, up 140 bps seq and up 180 bps YoY. Mgmt expects to maintain GMs in the mid-70s range for FY2027 despite the increase in the input costs.

Cash:

Q3 FCF grew by 31.6% YoY to $22.1B with a FCF of 38.7%, compared to 47.9% last year and 28.8% in Q2. The company has cash and marketable securities of $60.6 billion and debt of $8.47 billion.

Valuation:

Nvidia trades at a forward P/S ratio of 24.3. The company has traded at a minimum forward P/S ratio of 9.6 and a maximum of 45.8 in recent years. Nvidia is currently trading slightly lower than mid-range. On the bottom line, it trades at a forward P/E ratio of 39.4. Nvidia has traded at a minimum of 15.8 and the highest of 50.7. Nvidia is currently trading slightly higher than mid-range.

Notable Risks:

The risks to Nvidia are low – perhaps the lowest of any stock in the tech universe. With that said, I recently stated in a Seeking Alpha webinar that the predominant constraints are memory and energy now, which means Nvidia is losing its top place in terms of GPUs no longer being the top supply constraint in the AI market.

Broadcom: Ethernet Wins at Scale-Out & Custom Silicon will Prevail with Inference

It’s widely understood that Broadcom supplies Google with its custom TPUs. The incoming inference growth curve, that the I/O Fund detailed here, has led CEO Hock Tan to state Broadcom may witness an acceleration of XPU demand into the back half of 2026.

Tan stated, “In fact, what we've seen recently is that they are doubling down on inference in order to monetize their platforms. And reflecting this, we may actually see an acceleration of XPU demand into the back half of 2026 to meet urgent demand for inference on top of the demand we have indicated from training.”

Something similar was echoed in the FQ3 call, with Tan stating: “But also as for these guys, they got to be accountable to being able to create cash flows that can sustain their path. They [are] starting to also invest in inference in a massive way to monetize their models.”

On that note, Google’s TPU business received a significant vote of confidence recently with Anthropic signing a deal for up to one million TPUs, including Ironwood, coming online in 2026. The deal is said to be worth tens of billions.

For Broadcom, TPUs are expected to be the primary driver of AI revenue growth in fiscal 2026 – estimates from HSBC earlier this summer projected Google’s TPUs to represent ~58% of Broadcom’s ASICs shipments at 1.79 million, but account for ~78% of ASICs revenue at $22.1 billion. This is because Google’s TPUs were estimated to carry a significant price premium at $13,000 per chip versus Broadcom’s other projects at $5,000 per chip. However, this is still less than half the cost of Nvidia’s chips at $30,000 to $40,000 for a solo B200 ($60,000 to $70,000 for a GB200).

Looking beyond fiscal 2026, projections for TPU shipments are surging. Morgan Stanley now expects 5 million TPUs to be shipped in 2027, a 67% rise from its prior estimate for 3 million; for 2028, the firm estimates shipments as high as 7 million, a 120% increase from its prior estimate. This would project YoY growth of 40% from 2027 to 2028, a substantial increase from 6% previously, and will represent more than 2X growth in two years.

The I/O Fund first covered TPUs versus GPUs back in 2019 and revisited the topic in February 2024 in our analysis, Broadcom: Networking/ASICs Giant and the Second Largest by AI Revenue. Since then, we’ve provided quarterly coverage for two years. Broadcom: Networking/ASICs Giant and the Second Largest by AI Revenue. Since then, we’ve provided quarterly coverage for two years.

The shift to Ethernet and away from Nvidia’s lock-in ecosystem of GPU + InfiniBand is benefiting Broadcom, with the industry pointing to rising Ethernet demand. Arista said that momentum for Ethernet “has really shifted in the last year” while Nvidia touted that its new Spectrum-X Ethernet is annualizing at $10 billion in revenue, or $2.5 billion quarterly.

The company is committed to remaining on the leading edge of networking with its Tomahawk 6 switch, the industry’s first 102.4 Tbps Ethernet switch. The next-gen switch doubled the bandwidth of its predecessor, while offering flexible deployment ability with 1,024 100G or 512 200G SerDes options, reducing switch count.

This raw performance upgrade paves the way for >100K to 1 million accelerator clusters by allowing larger leaf-spine fabrics to be constructed, while drawing less power and keeping latency low. Broadcom exec Ram Velaga said that the demand for the new switch is “unprecedented” with multiple >100K accelerator deployments “using Tomahawk 6 for both the scale-out and scale-up interconnect.”

When discussing Tomahawk 6, management points toward the flattening of the AI cluster as an important catalyst for this product, stating: “[…] Tomahawk 6 enables clusters of more than 100,000 AI accelerators to be deployed in just two tiers instead of three … this flattening of the AI cluster is huge because it enables much better performance in training next-generation frontier models through a lower latency, higher bandwidth and lower power.” The two-tier topology also reduces complexity of cluster construction and reduces congestion choke points significantly, addressing another critical pain point of building larger and larger clusters.

Additionally, in terms of the AI networking opportunity, scale up is 5-10X more than scale out – setting up a nice trajectory as AI clusters grow. Oppenheimer analyst Rick Schafer highlighted that they expect next-gen Tomahawk6 volumes to ramp up in the second half of next year, providing added growth and gross margin boost.

Overall Revenue Growth:

Second-highest in AI revenue among the semis. Broadcom’s FQ4 revenue grew by 28.2% YoY and 12.9% QoQ to $18.02 billion, beating estimates by 3.2%. Management also provided a strong FQ1 revenue guide of $19.1 billion, implying a YoY growth of 28.1% and 6% QoQ, beating estimates by 4.3%. The expected strong growth is primarily driven by AI revenue, which is expected to double YoY to $8.2 billion.

FQ4 semiconductor solutions revenue grew by 35% YoY to $11.07 billion, primarily driven by strong AI revenue. Revenue growth accelerated by 9 percentage points from 26% growth reported in FQ3. Management expects semiconductor revenue growth to further accelerate 15 percentage points to 50% YoY, reaching $12.3 billion in FQ1, driven by a surge in AI revenue. For FY2025, semiconductor revenue grew by 22% YoY to a record $36.9 billion.

Management expects renewals to be seasonal in Q1 and expects Infrastructure Software revenue to be $6.8 billion, down (2%) sequentially and up 1% YoY.

AI Segment Growth:

FQ4 AI revenue grew by 74% YoY and 25% QoQ to $6.5 billion and was higher than the management guide of $6.2 billion. For the FY2025, AI revenue grew by 65% YoY to $20 billion. Management expects AI revenue to accelerate in FY2026 and drive most of Broadcom’s growth in FY2026.

During fiscal year 2025, AI revenue grew 65% year-over-year to $20 billion, leading to semiconductor revenue seeing an all-time high of $37 billion

Next quarter, AI revenue is expected to double year-over-year to $8.2 billion.

Broadcom’s total AI-related orders on hand exceed $73 billion, nearly half of the company’s consolidated $162 billion backlog. The $73B backlog is expected to ship over the next 18 months. This backlog includes not only XPUs but also networking components. Most of the earnings call was management explaining the $73 billion is a baseline for the next 18 months.

Earnings:

FQ4 adjusted EBITDA grew by 34.4% YoY to $12.2 billion with an adjusted EBITDA margin of 68% and was better than the management guide of 67%. For FQ1, management expects adjusted EBITDA margin to be down 100 basis points sequentially and YoY to 67%.

Adjusted EPS grew by 37.3% YoY to $1.95, beating estimates by 4.3%.

FQ4 GAAP EPS grew by 93.3% YoY to $1.74. While adjusted EPS grew by 37.3% YoY to $1.95, beating estimates by 4.3%. Analysts expect adjusted EPS to grow by 23.3% YoY to $1.97 in FQ1 and 28.7% YoY to $2.03 in FQ2.

Margins:

Adjusted gross margin was 77.9%, up 100 basis points YoY and down 50 basis points sequentially.

Operating margin improved 8.8 percentage points YoY and 4.8 percentage points sequentially to 41.7%, primarily driven by operating leverage. This is up 2X from 1-2 years ago.

The company will have to pass-through more third-party components such as memory, optics, and power infrastructure, which will lead to gross margins contracting. However, management was clear that gross profit dollars and operating income dollars will continue to rise due to scale and operating leverage.

Cash:

Broadcom’s cash flows are improving, driven by higher profits. FQ4 free cash flows grew by 36.2% YoY to $7.47 billion with a free cash flow margin of 41.4% compared to 39% in the same period last year.

The company has debt of $65.1 billion and cash of $16.2 billion. The debt is high due to the past acquisitions. However, the company has a history of successfully reducing debt. Also, the company has strong cash flows. Cash has increased to $16.2 billion from $10.7 billion due to higher free cash flows.

Valuation:

Broadcom trades at a forward P/S ratio of 15.9. The company traded at a minimum forward P/S ratio of 6.7 and the maximum of 28.8 in recent years. Broadcom is trading slightly lower than mid-range. It is trading at a forward P/E ratio of 31.7. The company traded at a minimum forward P/E ratio of 17.3 and a maximum of 57.2. Broadcom is trading slightly lower than the mid-range on the forward P/E ratio as well.

Notable Risks:

Similar to Nvidia, the company is a high-quality stock with a relatively low risk profile. The primary risk is high debt, which as we have discussed above, is well controlled. However, Broadcom is in sharky waters on networking in terms of competition, and even on custom silicon with a rumor Google could be moving some orders for its next generation of TPUs (v7 and v8) over to MediaTek.

AMD: The Element of Surprise

Overview:

AMD is a great example of the paradox of stock investing, which is that despite Nvidia and Broadcom posting higher growth on a much larger revenue base, AMD outperformed Nvidia and Broadcom last year by roughly 2X.

Five years ago, I dubbed AMD the “Dark Horse” for my premium research members as the company had a mere 4% share in the CPU-data center and was up against the near-monopoly of Intel. AMD has proven there is an element of catching the market off guard that helps to compound returns. The opposite of this is known as a crowded trade – which leads us back to the chart pictured above.

In more recent years, the I/O Fund has remained consistent in our conviction that AMD will eventually contend with Nvidia on GPUs while emphasizing that timing is key. About 18 months ago, I spelled out AMD could outpace Nvidia’s returns by 2030 stating in a Real Vision video interview that the company’s opportunity is closely tied to the inference market. At the time, AMD was in the doghouse:

“Core to this thesis on AMD is giving time for the budding inference market to take off and mature – [I explained that]“where AMD is going to compete with Nvidia is a market that is very early, so we need time for that to mature, which is inference. Many people may get that confused, because we are fully in the AI market today because Nvidia is putting up those huge data center numbers. We are in the data center training market today; one day, we will be an AI market led by inference.”

It’s important to note that my prediction that AMD can outpace Nvidia’s returns by 2030 hinges on AMD capturing 20% to 25% of the GPU-market. We all know that Nvidia is not Intel, and thus AMD faces a fiercer competitor on all accounts. However, the path that AMD took to overcome Intel is highly relevant. You can read more about that here and here.

That said, if you’ve followed AMD’s AI story as closely alongside the I/O Fund (and I know many of you have), then the most important leap in this generation of GPUs is not found in Helios specs or even this quarter’s commentary. Rather, it’s in the demand signals. For the first time, some of the most influential AI customers — including OpenAI, Oracle, and Meta — are preparing to deploy the MI400 Series in meaningful volume. That level of hyperscaler commitment is something AMD hasn’t enjoyed in prior GPU generations (MI300s), and it represents an important shift in the company’s competitive positioning.

There are many investment opportunities in AI across AI networking, AI energy, AI software, AI data layer and more – but none compare to the sheer size and strategic importance of GPUs, particularly when there are so few players competing for that share. That scarcity dynamic is precisely why AMD remains a special case in our portfolio.

Overall Revenue Growth:

Q3 revenue grew by 35.6% YoY and 20.3% QoQ to a record $9.25 billion, beating estimates by 5.7%.

Q4 revenue guide is $9.6 billion at the midpoint, representing a YoY growth of 25.4% and 3.8% sequentially. It beat the analyst's estimates by 4.3%. Similarly, to the last quarter, the revenue guidance does not include any MI308 chip sales to China. However, this time management indicated that MI308 chip sales could be coming soon.

AI Segment Growth:

Data Center revenue rebounded strongly in Q3 as it grew by 22% YoY and 34% QoQ to a record $4.3 billion. The strong growth was primarily driven by the ramp of the Instinct MI350 Series GPUs and server share gains. However, we aren’t quite there yet in terms of a strong inflection as it was stated data center would grow 4% QoQ with strong growth server (a nod toward CPUs instead of GPUs). Server CPU revenue reached an all-time high as adoption of 5th Gen EPYC Turin processors accelerated rapidly, accounting for nearly half of overall EPYC revenue in the quarter. The sales of prior generation EPYC processors also continued to be strong.

The last guide that AMD provided on GPUs was $6.5 billion in revenue by the time we exit this year. Management is hinting they will see “tens of billions” in their AI business by 2027. If we assume this means a minimum of $20B (perhaps more) then it coincides with roughly 200% growth in AMD’s AI business over a two-year time span.

Margins:

The gross margin was 52%, up 200 basis points YoY primarily driven by a higher profitable product mix. Management has guided an adjusted gross margin of 54.5% for the fourth quarter.

The operating margin improved by 300 basis points YoY to 14%. Adjusted operating margin was down by 100 basis points YoY to 24% and missed the management guidance of 25% as the adjusted operating expenses increased by 42% YoY to support the significant AI opportunities and go-to-market activities for revenue growth. Management has guided an adjusted operating margin of 25% for the fourth quarter.

EPS:

GAAP EPS grew by 59.6% YoY to $0.75, beating estimates by 10%. Adjusted EPS rose by 30.4% YoY to $1.20, beating estimates by 2.4%.

Analysts expect adjusted EPS to grow by 22.3% YoY to $1.33 in Q4 and accelerate to 26.4% growth in Q1 and 183.2% YoY growth in Q2 to $1.36. Looking forward, they expect the adjusted EPS to grow by 61% YoY to $6.35 in 2026 and 45.7% YoY to $9.25 in 2027.

Cash:

Q3 free cash flows grew by 208% YoY to $1.53 billion or 17% of revenue, up 10 percentage points YoY.

Cash of $7.24B and debt of $3.22B.

Valuation:

AMD is trading at a forward P/S ratio of 9.2. The company has traded at a minimum of 3.7 and a maximum of 13.3. AMD is trading at mid-range. On the bottom-line, it is trading at a forward P/E ratio of 38.6. The company has traded at a minimum of 19.7 and a maximum of 66.5 in recent years. AMD is trading at mid-range on a forward P/E ratio as well.

Risks:

AMD carries execution risk as taking Nvidia head-on is not for the faint of heart. Margins tend to be lower with AMD as one of their tactics is to offer much lower prices than their competitors.

TSM: Multi-Year Visibility for AI Megatrend

TSMC is one of the least sensational management teams in the AI space, yet management explicitly called AI a multi-year “megatrend” in their most recent earnings call, with demand now being pulled not just by chip designers, but directly by hyperscale cloud providers seeking to lock in capacity.

Management stated:

“Our customers’ customers, who are mainly the cloud service providers, are also providing strong signals and reaching out directly to request the capacity to support their business. Thus, our conviction in the multiyear AI megatrend remains strong, and we believe the demand for semiconductor will continue to be very fundamental.”Thus, our conviction in the multiyear AI megatrend remains strong, and we believe the demand for semiconductor will continue to be very fundamental.”

When the world’s most advanced foundry says hyperscalers are coming to them directly for capacity, it signals that AI demand remains foundational. Perhaps most importantly, TSM is not a “flip the switch" business model to where demand can be turned on and turned off quickly. Wafer capacity must be planned years in advance, which makes these signals particularly meaningful.

While 2nm defines the next phase of the roadmap, 3nm remains the node supporting most AI deployments today. The company’s advanced 3nm node offers roughly 15% better performance than 5nm at equal power and transistor density, with die sizes estimated to be ~42% smaller. TSMC also states the 3nm process can reduce power consumption by up to 30%, underscoring power efficiency as a key competitive advantage.

This efficiency helps deepen TSMC’s moat. While Samsung introduced 3nm chips in 2022, it has lagged TSMC on yield and power efficiency by an estimated 10%–20%. This advantage is reflected in pricing power, with TSMC charging roughly 25% more for 3nm versus 5nm, as customers are willing to pay a premium to avoid Samsung.

The company entered volume production of its most advanced node, N2, in 4Q 2025, marking a transition from FinFET to gate-all-around (GAA) transistor architecture. By wrapping the gate around all sides of the channel, GAA improves electrostatic control and reduces leakage versus FinFET designs.

N2 introduces NanoFlex technology, enabling designers to mix cell types and optimize for performance or power by adjusting nanosheet dimensions. According to management on the Q2 2025 earnings call, N2 delivers 10%–15% speed improvement at the same power or 20%–30% power reduction at the same speed, along with more than 15% chip density gains versus N3E.

As chips migrate to advanced nodes—such as Nvidia’s Rubin moving to 3nm and AMD building CPUs on 2nm—TSMC stands to continue to benefit from rising pricing power, as these nodes command significant wafer premiums in exchange for material performance and power efficiency gains.

Overall Revenue Growth:

TSMC reported Q4 revenue of $33.73 billion, up 25.5% YoY and 1.9% QoQ and exceeding guidance range for $32.2 billion to $33.4 billion, and coming in $1 billion ahead of estimates.

Full-year revenue was $122.42 billion, up 35.9% YoY; TSMC guided for Q1 revenue between $34.6-35.8 billion, up 37.9% YoY and 4.4% QoQ (also outpacing Q1 '25 growth of 35.3% YoY); 2026 revenue guided to be up close to 30% YoY in USD

AI Segment Growth:

HPC revenue rose 4% QoQ in NT$ and accounted for 55% of revenue in Q4. For FY25, HPC revenue in NT$ was up 48% YoY to 58% of revenue. Recent development in the AI market continue to be very positive. Revenue from AI accelerator accounted for high teens percent of the total revenue in 2025.

Earnings:

GAAP EPS up 40.2% YoY in Q4 to $3.14, beating estimates by 5.2%. FY25 EPS was $10.65, up 51.3% YoY; GAAP EPS is expected to be $3.28 in Q1, up 54.7% YoY while FY26 EPS is currently estimated to be $13.05, up 22.5% YoY (subject to revisions)

Margins:

GAAP gross margin in Q4 was 62.3%, well above guidance for 59-61%, and up 2.8 points QoQ and 3.3 points YoY on due to cost improvement efforts, favorable foreign exchange rate and high capacity utilization rate. For Q1, TSMC guided gross margin to be 63-65%, up 1.7 points QoQ and 5.2 points YoY at MP. GAAP operating margin was 54%, up 3.4 points QoQ and 5 points YoY; For Q1, TSMC guided operating margin to be 54-56%, up 1 point QoQ and 5.5 points YoY at MP; Net margin was 48.3%, up 2.6 points QoQ and 5.2 points YoY.

Cash:

Q4 operating cash flow was $23.4 billion for a 69.4% margin, down 2 points YoY, and FCF was $11.9 billion for a 35.2% margin, up 5.4 points YoY. Cash of $97.6 billion and debt of $31.6 billion.

Valuation:

TSM is trading at a forward P/E ratio of 22.9. The company has traded at a minimum of 13.5 and a maximum of 29.6 in recent years, placing the current valuation near the midpoint of that range.

Notable Risks:

TSM carries geopolitical risk that has been muted in recent quarters, yet could heat up again at anytime.

Memory: The Leading Constraint in AI Systems

Memory is typically a cyclical industry that is lower margin and lumpy, yet it is seeing a newfound resurgence from AI that is strong enough to transform commoditized hardware into a secular trend as the AI economy is built out. AI servers use more DRAM and NAND than traditional servers, relying heavily on high-bandwidth memory (HBM) for training and inference.  

The HBM market is projected to reach $35 billion this year, doubling YoY, with Micron’s September results confirming that the market was well on track to be over $30 billion as of Q3. Looking ahead, the shift to HBM4 with Nvidia’s Rubin architecture and AMD’s MI400 series will represent another important growth lever come 2026 as HBM content per GPU and per rack surges, paving the way for HBM to potentially triple again by as early as 2028.

Not only is HBM a focal point due to its rising importance and thus increasing content per GPU, but other memory products are quickly coming to the forefront, notably low-power DDR5 memory (LPDDR5X) and data center solid state drives (SSDs).

Through 2026 and 2027, the outlook for HBM remains fairly positive, with SK , SK Hynix, Samsung and Micron already selling out of HBM3e and HBM4 capacity through the end of 2026. This underscores the robust demand environment stemming from AI accelerators, with Micron seeing HBM bit shipments outpacing DRAM bit growth, but also may limit revenue upside as prices have been contracted over the next four quarters.

On pricing, HBM4 is expected to carry a significant premium to HBM3e, currently used for Nvidia’s Grace Blackwell chips. Analysts from UBS had estimated that HBM4’s price premium could be as much as 30%, though reports of Samsung’s discussions over HBM4 supply with Nvidia dwarfed that – Samsung was said to be targeting price parity with SK Hynix on HBM4 around $500, up ~50% from the mid-$300s for HBM3e. These price increases will support strong growth as HBM4 volumes ramp.

Looking forward, industry analysts project the HBM market to reach $98 billion to $100 billion by 2030, representing a 31.5% CAGR from 2024’s $18 billion, outpacing DRAM’s growth by 3X, which is expected to rise at an 11.7% CAGR to $194 billion. As a result, HBM’s share of DRAM revenue is expected to surpass 50%.

However, in its Q1 report, Micron said it now expects the HBM TAM to reach $100 billion as early as 2028, two years sooner than its prior forecast. This would represent a ~42% CAGR from $35 billion, or more than 10 points faster than the base case forecasts.

For information on HBM3e and the shift to HBM4, DDR5 prices surging and the rising demand for memory bandwidth, plus why NAND SSDs are surging, read our December report “The AI Memory Boom has Arrived.”The AI Memory Boom has Arrived.”

Micron: Memory Market Takes the Crown from Compute on Growth

You would be hard pressed to find another segment of the AI data center industry posting growth to this degree on a sequential basis. Data from TrendForce estimates that the global DRAM market recorded growth of 30.9% QoQ in calendar Q3 to $41.4 billion. In dollar terms, this represented QoQ growth of ~$9.7 billion, or nearly as large of a QoQ jump as Nvidia reported in its most recent quarter. This growth was driven by “significant increases in conventional DRAM contract prices, higher bit shipments, and growing HBM volumes.”

For a supplier breakdown, SK Hynix’s revenue grew 12.4% QoQ to $13.75 billion, fueled by seasonal price increases and significant bit shipment growth. Samsung also reported similar significant growth in bit shipments, with revenue up 30.4% QoQ to $13.50 billion. Micron followed with a substantial 53.2% QoQ increase to $10.65 billion, per TrendForce (note that this is for calendar Q3 which does not align with Micron’s fiscal year calendar).

As of November, TrendForce estimates that DRAM contract prices will accelerate into Q4, predicting conventional DRAM contract prices will surge by another 45% to 50% QoQ, while total contract prices (which includes HBM) will increase by 50% to 55% QoQ – this is a substantial uplift from projections for 18-23% QoQ growth in Q4 at the end of October.

Contributing to strong pricing is DDR5 DRAM, where prices rapidly skyrocketed – from late September to early November, prices have as much as quadrupled, with impacts felt most on consumer products. Samsung also reportedly just boosted DDR5 prices by 100%, citing no stock left.

However, revenue growth in Q4 could potentially be lower than pricing growth as bit shipments are projected to decline sequentially due to rapid inventory depletion. DRAM supplier inventory levels are projected to range between two to four weeks, a major crunch from 5.5 weeks on average last quarter and more than 15 weeks at the start of the year.

Overall Revenue Growth:

Micron reported record Q1 revenue of $13.64 billion, beating estimates by 5.9% and accelerating 10.7 points to 56.7% YoY growth. Sequentially, growth was 20.6% QoQ, just one point slower than Q4’s 21.7% QoQ growth.

Revenue accelerated from 46.1% YoY in FQ4 to 56.7% in FQ1 at $13.64B; FQ2 guidance points to sharp acceleration to 132.2% YoY, QoQ growth to accelerate from 20.6% to 37.1% QoQ. Some analysts are saying this is the biggest headliner beat they’ve seen since Nvidia’s 2023 moment.

AI Segment Growth:

DRAM products (within that HBM and LPDDR5X) were the primary driver of Q1’s results, with revenue up 69% YoY and 20% QoQ to $10.8 billion, or 79% of revenue.

DRAM revenue up 69% YoY and 20% QoQ to $10.58B in Q1

Micron’s Cloud Memory Business Unit (CMBU), which consists of its HBM, high-capacity dual in-line memory modules (DIMMs), and low-power server DRAM solutions, saw Q1 revenue of $5.28 billion, up 99.5% YoY and 16.3% QoQ

HBM, high-capacity DIMMs and LP server DRAM revenue reached $10 billion as of Q4, up more than fivefold YoY

Earnings:

In Q1, Micron reported GAAP EPS of $4.60, up 175% YoY; this also is a sharp uptick from $2.83 in Q4. For Q2, Micron guided for GAAP EPS to be $8.19, +/- $0.20, nearly 74% ahead of estimates for $4.71 and corresponding to YoY growth of almost 481%, a 306 point acceleration. GAAP EPS growth is expected to remain >250% for both Q3 and Q4 to $9.37 and $10.04.

For the full year, Micron is expected to deliver GAAP EPS of $31.17, more than quadrupling from $7.59 in fiscal 2025. Earnings estimates also moved more than 60% higher following Q1’s report and Q2’s blowout guide, moving from $19.42 to the now $31.17 estimate.

Margins:

GAAP gross margin in Q1 was 56%, up 17.6 points YoY, aided by the strong growth in CMBU which carried a 66% gross margin in the quarter. For Q2, GAAP gross margin was guided to be 67% at midpoint, an 11 point sequential expansion and up 31.2 points YoY.

GAAP operating margin was 45%, up 12.7 points QoQ and 20 points YoY, again aided by CMBU which carried a 55% margin in the quarter. For Q2, Micron implied operating margin to be 58.7%, up 12.7 points QoQ and 36.7 points YoY, signaling strong tailwinds from surging DRAM prices.

GAAP net margin was 38.4% in Q1, up 10.1 points QoQ and nearly 17 points YoY.

Cash:

Operating cash flow was $8.41 billion in Q1, up more than 159% YoY and nearly 47% QoQ. OCF margin was 61.7%, up 10 points QoQ and up 24.4 points YoY.

Adjusted free cash flow was $3.91 billion in Q1, up sharply from $803 million in Q4 and $112 million in the year ago quarter. Adjusted FCF margin was 28.6%, up from 7.1% in the prior quarter and 1.3% in the year ago quarter.

Micron reported total cash and equivalents of $12.0 billion and total debt of $11.76 billion.

Valuation:

Micron is now trading at peak multiples on the top line as shares continue to rally, currently valued 6.5x forward PS, in line with the highest level it achieved in the summer of 2024, and well above its 3.6x average multiple over the past five years.

However, on the bottom line, Micron is trading at a much more reasonable 12.8x forward PE multiple due to the strong margin expansion and expected 300% earnings growth this fiscal year to $33+. This is notably below Micron’s 2025 peaks around 16x forward PE.

Notable Risks:

Sharply rising DRAM prices from tight supply could cut into demand for consumer electronics products, which is Micron’s second largest segment and growth driver (Mobile and Client) with nearly $4.3 billion in revenue and a 47% operating margin in Q1. Any demand softness from price hikes could be felt more acutely in 2026 with forecasts now pointing to smartphone and PC shipments declining YoY.

SanDisk: Marketing-Leading Returns in 2026; Can the Stock Repeat?

Overview:

On a broader level, data center/enterprise SSDs are often overlooked but equally critical as HBM when it comes to AI training and inference. This is because data center SSDs offer higher read-write speeds critical for accessing and transferring data rapidly, along with higher performance and energy efficiency, vital factors for larger-scale AI training and inference workloads.   

Nvidia is positioning NVMe SSDs to become the backbone for the Inference Context Memory Storage architecture discussed at CES, there is the potential for SSD suppliers to see solid medium/long-term tailwinds from increased SSD capacity requirements in inference-optimized deployments over the next few years.

For example, Bernstein estimates that Huang’s CES comments on SSDs and KV cache requirements suggest an additional 16TB per GPU, compared to 3-4TB per GPU today, or 4-5X growth. This will be more weighted towards year-end and into 2027 as ICMS rolls out with Rubin.

Similar to DRAM, data center SSD shipments and prices were strong in Q3, driven by hyperscaler demand for AI infrastructure and general-purpose servers. Revenue from the top five companies – Samsung, SK, Micron, Kioxia and SanDisk – rose ~28% QoQ to a new record at $6.54 billion, per TrendForce. Notably, this was broad-based strength, with growth at the five firms all ranging between 26-30% QoQ.

For Q4, there are a few dynamics in play that are likely to keep prices and thus revenue growth strong. For example, supplier inventories are expected to have fallen sharply, from 10-15 weeks in early Q3 to just 7-10 weeks at the start of Q4, which was said to be ‘below healthy levels’, with enterprise SSD supply growth substantially lagging demand. SanDisk says that its storage-focused SSD is “growing in demand with 2 hyperscaler qualifications underway and a third hyperscaler along with a major storage OEM planned for calendar year '26.”

In November, TLC and QLC SSDs reportedly experienced strong price increases, with 1 TB TLC SSDs seeing sharp increases and the “most significant shortage due to persistent enterprise SSD demand.” 512 GB TLCs were estimated to see the most significant price hikes at ~65% MoM, while the QLC supply chain tightened and forced prices higher.

Additionally, TrendForce points out that these inventory and demand dynamics mean “supply shortages in 2026 are becoming increasingly apparent,” providing an additional lever for SSD prices to rise through next year and support more revenue growth as long as inventories and bit shipments do not hinder that.

Overall Revenue Growth:

SanDisk reported a strong sequential revenue acceleration in its fiscal Q1, driven by NAND demand outpacing supply and increasing demand in its data center, edge and consumer end markets. Q1 revenue increased 22.6% YoY and 21.4% QoQ to $2.31 billion, accelerating from 8% YoY and 12.2% QoQ growth in fiscal Q4. Higher-than-expected bit growth drove the outperformance in the quarter relative to guidance of $2.1-2.2 billion, per management. Next quarter is expected to see 16.5% QoQ at the $2.69 billion consensus.

AI Segment Growth:

SanDisk’s data center revenue, as mentioned above, declined (10%) YoY but rose 26% QoQ to $269 million, driven by increasing demand for its ‘Stargate’ enterprise SSD product line. However, revenue contribution remains small, at less than 12% of revenue. 

Management also increased their forecast for data center exabyte growth, explaining that last quarter, exabyte growth expectations were in the mid-20% range, but now are in the mid-40% range. As a result, data center is expected to be the largest market in NAND on an exabyte basis in 2026, surpassing mobile. 

SanDisk’s Edge segment was the primary growth driver in Q1 with revenue up 30% YoY and 26% QoQ to $1.39 billion, driven by increasing NAND content in PCs and smartphones and a positive PC refresh cycle. Consumer revenue rose 27% YoY and 11% QoQ to $652 million, while data center revenue was down (10%) YoY but up 26% QoQ to $269 million. 

Earnings:

SanDisk stands out for its strong expected earnings growth through fiscal 2026 and fiscal 2027, with adjusted EPS expected to reach more than $21 by then, or >7X higher than the $2.99 it earned in fiscal 2025. 

Q1 GAAP EPS was $0.75, a strong improvement from a ($0.16) loss in Q4, though this was down (49%) YoY from $1.46 in the year ago quarter as margins remained lower YoY. Adjusted EPS was $1.22, up 321% QoQ but down (33%) YoY. 

For Q2, SanDisk guided for adjusted EPS of $3.00 to $3.40, up more than 162% QoQ. Adjusted EPS is expected to further increase to $3.78 in fiscal Q3 and $4.82 in fiscal Q4.  

For fiscal 2026, SanDisk is expected to generate $13.29 in adjusted EPS, up 344.6% YoY, while GAAP EPS is projected to be $11.53, up from ($11.32) in FY25 due to the spin off. Fiscal 2027 is expected to see earnings power surpass $21, with GAAP EPS estimated to be up 86% to $21.47 and adjusted EPS up nearly 62% to $21.50.

Margins:

Margins are lower YoY compared to pre-spinoff margins, but Q1 saw strong sequential margin expansion that is expected to accelerate in Q2.  

Q1 GAAP gross margin was 29.8%, down 8.8 points YoY but up 3.6 points QoQ. Adjusted gross margin was 29.9%, down 9 points YoY but up 3.5 points QoQ. 

GAAP operating margin was 8.3%, down 8.3 points YoY but up 5.6 points QoQ. Adjusted operating margin was 10.6%, down 8.2 points YoY but up 5.3 points QoQ. 

For Q2, SanDisk guided adjusted gross margin to be 41-43%, or up just over 12 points QoQ at midpoint on higher pricing and cost reduction tailwinds, while adjusted operating margin is implied to be 24.2% at the midpoint of opex guidance, or up 13.6 points QoQ. Fab startup costs are expected to transition from headwinds to tailwinds during the quarter, potentially aiding more margin expansion into fiscal Q3 and Q4.

Cash:

Operating cash flow was $488 million in Q1 for a 21.1% margin, up from a (7%) margin in the year ago quarter and a 4.9% margin in Q4. 

Adjusted free cash flow was $438 million in Q1 for a 19% margin, up from a (10.5%) margin in the year ago quarter and 2.6% in Q4. 

SanDisk’s total gross capex to support the JV was $387 million in Q1, though its cash capex spend was only $40 million (1.7% of revenue) as the remainder was funded through external sources such as subsidies or tool depreciation recorded in COGS.

Cash and equivalents totaled $1.44 billion while debt totaled $1.35 billion. 

Valuation:

SanDisk’s valuation is somewhat hard to pin down given the company’s limited history on the public markets after its February spinoff, and its 1,000% rally in the past six months. On the top line, SanDisk is trading at 6.6x forward PS, having traded as low as 0.6x last summer and with an average multiple of 1.6x for its limited public history.

On the bottom line, SanDisk is trading at 36.3x forward PE, having traded as low as 3x last August with an average around 13.3x.

Notable Risks:

The NAND flash market has historically been quite volatile, and is shifting from significant oversupply in 2023 to expectations for substantial supply shortages through 2026. However, if NAND capacity begins to come online quickly through next year, or if demand for PCs and smartphones falters due to rising memory prices, the NAND cycle could reverse and lead to pricing pressures cutting into revenue growth and margins. SanDisk also has limited AI data center exposure, contributing with <12% of revenue last quarter.

AI Networking Stocks

Please refer to the section above entitled “Rubin Redefines AI Networking as a Bandwidth-First Constraint” for an update on the AI Networking trend, which is a Top 3 trend for the I/O Fund in 2026.

Lumentum: EMLs Power 400G/800G Transceivers as Networking Scales

EMLs are a critical component with Nvidia’s Blackwell generation, as the scale-up in GPU counts per rack from eight to 72 and subsequent increases in bandwidth and switch density will require low-power, efficient high-speed optics. The power advantages over SiPho also come to the forefront as power consumption becomes a central concern in scaling AI data centers, with Blackwell doubling power consumption versus Hopper at 140kW per rack.

EMLs are the main driver for Lumentum’s growth as these are good for short-to-medium reach inside data centers up to 2km and a strong choice for 400G and 800G optical transceivers, with the company having begun its 100G EML ramp for these data rates in early 2024. EML laser shipments reached a fresh record in fiscal Q1 2026, driven once again by 100G speeds and an increase in 200G shipments.

Lumentum’s Q1 provided more confirmation that EML laser shipments are ramping in full force, with another record quarter driven by 100G speeds and an increase in 200G shipments. EMLs have been the primary driver of growth so far for Lumentum, though the supply-demand imbalance is widening due to tight indium-phosphide (InP) capacity. Looking ahead to 2026, InP capacity will be a key factor to focus on as Lumentum is targeting 40% capacity growth over the next few quarters, with the potential for this to drive even stronger revenue growth.

One important discussion on EMLs is that the supply-demand imbalance continues to widen, meaning that substantial growth in capacity through 2026 should quickly convert to revenue. CEO Michael Hurlston explained that “last quarter, I think we characterized it as roughly a 20% shortfall relative to total customer demand. Even with the add in supply, I would say that number has increased to 25% to 30%. We are quite a bit short right now relative to the customer demand.”

On the positive side, Lumentum shared that while its indium phosphide fab is fully allocated due to high demand, it has made “better-than-expected progress on yields and throughput and now see a line of sight to add approximately 40% more unit capacity over the next few quarters.” CEO Michael Hurlston clarified at UBS’ tech conference that “we gave in the last earnings call a new benchmark saying, over the next 3 quarters, meaning our December, March and June quarters, we expected to add that 40%. So that’s a forward-looking statement where we’d expect an increase in capacity of 40% on what already is a doubled number.”

Management expects to be well positioned for both EML and CW lasers ramping for 1.6T transceivers, as its capacity is interchangeable between the two components, despite management noting a difficulty in forecasting how the two will ramp – the primary takeaway here is that even if faster data rates such as 1.6T are less dependent on EMLs, management believes there is more than enough content for them to do well.

Overall Revenue Growth:

Lumentum fulfilled its guidance for a >$500 million revenue quarter in calendar 2025, reporting a record $533.8 million in revenue in fiscal Q1, beating estimates by just 1.4%. Revenue growth accelerated 2.5 points to 58.4% YoY through QoQ growth slowed to 11%. Lumentum guided for $630 to $670 million in revenue in Q2, accelerating to 61.6% YoY and 21.8% QoQ, whereas consensus estimates were pegged at almost 40% growth to $561.5 million.

On the financials side, the number one item was Q2’s impressive 22% QoQ revenue growth guide to $650 million at midpoint. This is significant as Lumentum is reaching its $600 million quarterly revenue target two quarters ahead of schedule, with this also marking its highest revenue in company history. The 22% QoQ guide would also reflect Lumentum’s fastest sequential growth since the September 2020 quarter.

To put in perspective how strong Lumentum’s growth curve is, current estimates for the June 2026 quarter sit at $740.3 million, more than 23% ahead of the company’s target revenue. This is also up from $689.9 million on November 7, a 7.3% revision higher in less than one week.

As discussed previously, Lumentum guided for $630 to $670 million in revenue in Q2, accelerating to 61.6% YoY and 21.8% QoQ, whereas consensus estimates were pegged at almost 40% growth to $561.5 million.

AI Segment Growth:

Components revenue rose 18.4% QoQ and 63.9% YoY to $379.2 million, fueled by “robust demand inside the data center”, strong momentum for DCI products, and record EML shipments. Looking through 2026, Lumentum expects another breakout year for laser chip shipments, supported by “better-than-expected progress on yields and throughput” providing “line of sight to add approximately 40% more unit capacity over the next few quarters.” Management added that they also “expect a significant increase in shipment volumes in the second half of calendar 2026” for ultra-high power laser assemblies, which are currently in the initial ramp phase.

Management provided a deeper discussion on margins moving through 2026, with product pricing from supply-demand imbalances serving as a strong lever for margin expansion:

“I think we're moving the margin line up. Pricing, obviously, is a lever. And when you look at that very, very carefully, I think what you see in the guide is some pricing, very targeted price increases happening. I think as you look out next year in 2026, our agreements with customers will include more pricing, more broad-based price increases, just given the supply-demand imbalance.”

Earnings:

Lumentum reported a razor thin $0.05 in GAAP EPS, while adjusted EPS of $1.10, up 511% YoY, beat estimates by 6.8%.

For Q2, Lumentum guided for adjusted EPS in a wider range of $1.30 to $1.50, up 233% YoY, coming in well ahead of the $1.16 estimate at the midpoint.

Lumentum did not provide a full year adjusted EPS guide, though consensus now sits at $5.35, up from $4.90 and pointing to growth of 160% YoY.

Margins:

GAAP gross margin was 34.0%, in Q1, up nearly 11 points YoY and 0.7 points QoQ. Adjusted gross margin was 39.4%, up 6.6 points YoY and 1.6 points QoQ.

GAAP operating margin was 1.3%, up nearly 26 points YoY and 3 points QoQ. Adjusted operating margin was 18.7%, up 15.7 points YoY and 3.7 points QoQ, ahead of guidance for 16-17.5%. For Q2, management guided for continued expansion to 20-22%.

GAAP net margin was 0.8%, up 25.3 points YoY and not comparable QoQ due to an income tax benefit in Q4. Adjusted net margin was 16.2%, up 12.6 points YoY and 3 points QoQ.

Cash:

Operating cash flow was $57.9 million in Q1 for a 10.8% margin, down from 11.8% a year ago and 13.3% in Q4. Free cash flow was ($18.3 million) for a (3.4%) margin, up from (10.2%) a year ago but down from 2.1% in Q4.

Cash and equivalents were $1.12 billion while debt was $3.24 billion.

Valuation:

Lumentum is valued at peak multiples, with shares now trading above a 10x forward PS multiple, up from the 4x range in September and October. This is also 3x its five-year average forward PS of 3.3x and at peak levels.

On the bottom line, Lumentum is trading at 64.6x forward PE, above its prior peaks around 50x and above its 40.6x average over the past five years. Similar to the top-line, shares have seen a pretty rapid expansion from the 25-30x range in October.

Notable Risks:

Lumentum has many competitors in the optical transceiver space, while navigating rather severe InP and EML capacity shortages may pose a near-term challenge as the supply-demand imbalance continues to widen. Cash flows are also thin with FCF negative, and debt is around 3x of cash.

Coherent: InP Capacity to Double

Overview:

Coherent is not nearly as flashy as Lumentum when it comes to revenue growth or even data center growth, yet the company is sitting in a prime position moving through 2026 as the industry navigates extremely tight indium phosphide (InP) capacity coupled with elevated demand for InP-based EML lasers. This is because Coherent is preparing to double indium-phosphide capacity via a multi-faceted expansion plan with multiple facilities ramping output in unison, while shifting to a larger wafer size that can deliver 4X output per wafer at half the cost.

This dynamic is expected to help drive a reacceleration in Coherent’s data center segment to 10% QoQ growth next quarter, a notable uplift from 4% this quarter, along with margin expansion driving solid adjusted EPS leverage. Management also stated they expect “strong sequential growth through the balance of this fiscal year given very strong demand and improving supply.”

On the product side, Coherent sees strong demand for both its 800G and 1.6T transceivers, with 1.6T expected to drive a significant portion of the guided sequential growth. This first wave of 1.6T growth is expected to be split between both EML-based and CW laser-based silicon photonics transceivers, with Coherent able to benefit from both as it can quickly shift capacity for whichever customers prefer.

For Coherent’s AI-related revenue exposure, Datacenter and Communications account for ~69% of total revenue. This also includes some contribution from telecom so is not an exact figure yet provides a rough idea as to Coherent’s AI exposure.

Revenue:

Coherent delivered 17.3% YoY and 3.4% QoQ revenue growth in fiscal Q1 to $1.58 billion, beating estimates by nearly 3%. On a pro-forma basis excluding the $33 million in Q1 revenue from the now-divested Aerospace & Defense unit, revenue growth was 19% YoY and 6% QoQ.

For Q2, Coherent guided for revenue between $1.56 billion to $1.70 billion, which on the headline figure would be decelerating to 13.6% YoY and 3.2% QoQ at midpoint, before reaccelerating to 15.9% by Q4.

However, our internal pro-forma estimate shows a better trajectory for revenue through fiscal 2026 – pro-forma growth may decelerate slightly to the 17.4% YoY and ~5.7% QoQ in Q2, before reaccelerating to nearly 21% by Q4, the highest growth rate in the past five quarters.

AI Revenue:

Coherent’s Datacenter and Communications revenue rose 26.2% YoY and 7% QoQ to $1.09 billion, accounting for ~69% of revenue. Growth has decelerated rather steadily since Q1 FY2025’s 68% YoY print.

Datacenter revenue rose 4% QoQ and 23% YoY. As mentioned previously, Datacenter growth was constrained by InP laser supply, with management expecting QoQ growth to accelerate to 10% in Q2 and remain strong through the end of the fiscal year.

Communications revenue, which includes telecom and data center interconnect (DCI) rose 11% QoQ and 55% YoY, driven primarily by DCI products. Management said they witnessed strong growth in demand for ZR/ZR+ DCI products, with 100G, 400G and 800G products expected to continue ramping through fiscal 2026.

Earnings:

Fueled by margin improvements, Coherent reported a solid adjusted earnings beat in Q1, with adjusted EPS rising 73% YoY and 16% QoQ to $1.16, beating estimates by 11.3%.

For Q2, Coherent guided for adjusted EPS between $1.10 to $1.30, decelerating sharply to 26.3% YoY at the $1.20 midpoint, and only showing a small sequential improvement.

Margins:

Coherent made solid progress on the margin front and expects gross margins to strengthen towards 42% with the ramp of its 6-inch InP wafers and higher margin 1.6T transceivers, and continued cost cutting measures.

GAAP gross margin was 36.6%, expanding 2.5 points YoY and 0.9 points sequentially. Adjusted gross margin came in at 38.7%, above the midpoint of guidance for 37.5-39.5%, expanding two points YoY and 0.6 points sequentially. Management said the gross margin expansion was driven by “cost reductions and product input costs as well as yield improvements,” while pricing optimization was also a meaningful contributor.

GAAP operating margin was 16.4%, up nearly 11 points YoY and 16 points QoQ, though this was impacted by a $115 million gain from the Aerospace divestment. Adjusted operating margin was 19.5%, up 3.4 points YoY and 1.5 points QoQ.

GAAP net margin was 14.3%, up 12.4 points YoY and more than 21 points QoQ; adjusted net margin was 14%, up 3.8 points YoY and 1.4 points QoQ.

Cash:

Cash flows were also thin with OCF margin down nearly 10 points YoY, and FCF widened deeper into negative territory due to capex for the upcoming capacity expansion.

Operating cash flow was $46 million in Q1, down from $130.3 million in Q4 and the first time falling below $100 million in the past seven quarters. OCF margin was 2.9%, down from 11.4% a year ago and 8.5% in the prior quarter.

Free cash flow was ($57.9 million), widening from ($1 million) in Q4 and a stark contrast to $61 million in the year ago quarter, driven by capex of $103.9 million. FCF margin was (3.7%), widening from (0.1%) in the prior quarter and down from 4.5% a year ago.

Cash and equivalent totaled $852.8 million, while debt was $3.31 billion, down from $3.69 billion in the prior quarter

As a result, Coherent has made substantial progress on its debt leverage ratio, paying down $400 million in debt in Q1. On that note, Coherent’s debt has declined approximately $1 billion over the last two years, from $4.29 billion in Q1 FY24 to $3.31 billion this quarter – a nearly 23% reduction.

Coherent’s debt leverage ratio has now improved to 1.7x, down from 2x in the prior quarter and 2.4x a year ago

Valuation:

Similar to Lumentum, Coherent is trading at peak multiples on the top and bottom line. Shares are valued at 5x forward PS, more than double its 2.2x average over the last five years and a significant discount to Lumentum’s 10x multiple likely due to Coherent’s lower growth.

On the bottom line, Coherent is trading at 42.5x forward PE, just slightly below its June 2024 peak at 45x, though this is also well above its five-year average forward PE of 26.3x.

Risks:

Coherent’s data center revenue growth was soft in Q1 at 4% QoQ, though management expects this to return to 10% QoQ in Q2 and remain strong, thus the company needs to execute on this given the multi-faceted tailwinds from 1.6T transceiver demand and InP capacity expansion.

Astera Labs: Scorpio-X Set to Provide a Boost Amid Tough Comps

Overview:

In an effort to identify a catalyst that can sustain Astera’s exceptional growth, it would be this product that does so. The X-series is used to interconnect GPUs for higher GPU utilization, resulting in higher ASPs.

Regarding the X-Series: “And this one, like Mike noted, it's a greenfield use case, meaning if you keep Nvidia and NV Switch aside, everyone else is starting to build configurations that are obviously going to need some kind of a switching functionality, which is what we are addressing with our X Series device.”

And on that basis, the X-Series will always be a much more valuable, much more higher ASP product than a P-Series.”

Notably, Astera maintains their largest opportunity for the X-Series is on the custom silicon side although they foresee hyperscalers wanting to customize their racks in a way that prevents vendor lock-in from both Nvidia and Broadcom.

Regarding Ethernet Scale-up Networking (ESUN), ESUN is attempting to make Ethernet work for scale-up whereas UALink was built from scratch for scale-up. The primary benefit ESUN offers is to move quicker than UALink (in the most recent earnings report, ALAB stated it’ll be 2027 for UALink to be fully deployed).

However, in the meantime, Astera’s PCIe solutions are in high demand and deployable now. Even if ESUN moves faster commercially, there is a performance gap that helps to ensure that Astera’s positioning with PCIe/CXL remains intact. That performance gap is best described as the low latency required for what are the most in-demand AI workloads today – those that require memory pooling and GPU-to-GPU communication.

For more information on how the relevancy of PCIe will persist, read more information on this topic under the Top 3 trends section under AI Networking.

Revenue:

Revenue grew by 103.9% YoY and 20.1% QoQ to $230.6M, beating estimates by 11.7%. This maintained Q2’s sequential growth rate of 20%, though YoY decelerated by ~46 points as the company begins to lap tougher comps on a dollar basis.

For Q4, Astera guided for $245 million to $253 million in revenue, coming in well ahead of estimates for $216.5 million and pointing to YoY growth of 77% and QoQ growth of 8%, driven by continued PCIe 6 momentum and robust growth from Taurus Ethernet SCMs. This would technically mark the company’s first <100% growth quarter since the end of 2024.

AI Revenue:

Scorpio P-Series represents 10% of revenue now, yet management stated it will quickly double to exit the year at 20% of revenue. From there, management has implied Scorpio X will exceed Scorpio P’s revenue percentage. Net-net, that means Scorpio will reach 50% of revenue sometime in H1 2026 up from effectively 0% of revenue in H1 2025.

The longer refresher on Scorpio P-Series and Scorpio X-Series is necessary because the primary catalyst we identified earlier this year has not even ramped yet. Scorpio P-Series only began shipping this quarter and Scorpio X-Series will begin to ship next year.

Earnings:

Adjusted EPS grew by 113% YoY to $0.49, beating estimates by 25.6%. GAAP Operating Margin Expands ~32 Points YoY to 24%.

With the strong expansion in GAAP net margin, Astera delivered a 92.3% beat on GAAP EPS, reporting $0.50 in Q3 versus the $0.26 estimate. Adjusted EPS was $0.49, up 113% YoY and solidly ahead of the $0.39 estimate.

For Q4, Astera guided for $0.20 in GAAP EPS, below the $0.26 estimate due to a 45% income tax rate. Adjusted EPS was guided at $0.51, up 38% YoY. This guidance would bring FY25 GAAP EPS to $1.17 (versus estimates for $0.96) and adjusted EPS to $1.77 (versus estimates for $1.58).

Margins:

Operating margin improved 31.9 percentage points YoY to 24% and adjusted operating margin improved by 9.3 percentage points YoY to 41.7% driven by strong operating leverage.

GAAP gross margin was 76.2%, ahead of guidance for 75%. This marked a marginal 0.4 point sequential improvement but a 1.5 point YoY contraction. Adjusted gross margin was 76.4%.

GAAP operating margin was 24.0%, well ahead of guidance for 17.9%, and expanding 3.3 points QoQ and nearly 32 points YoY. This YoY expansion from (7.9%) in Q3 ’24 is quite impressive considering the company was reporting triple-digit revenue growth in each quarter; this also reinforces that the company is comfortably GAAP profitable. Adjusted operating margin was 41.7%, up 2.5 points QoQ and 9.3 points YoY.

For Q4, Astera guided for slight sequential moderation in margins down the line, with gross margin guidance at 75%, in line with prior quarter guidance. GAAP operating margin was guided to be 22.2% at midpoint, down 1.8 points QoQ but still up more than 22 points YoY. Adjusted operating margin was guided at 39.9%, down 1.8 points QoQ but up 5.6 points YoY.

Cash:

The company free cash flows grew by 41% YoY to $65.8M. Cash of $1.13B and debt is Nil.

Cash flow margins contracted sharply Q3, though this was primarily driven by a large QoQ increase in accounts receivable, providing an extra layer of confidence in the upcoming revenue acceleration in the next couple of quarters.

Operating cash flow was $49.1 million for a 6.4% margin, though OCF margin had been >22% for the past five quarters. The sharp contraction was primarily due to a $161 million sequential increase in accounts receivable.

Free cash flow was $2.4 million for a 0.3% margin, down from 20.2% in the prior quarter due to the jump in AR.

Valuation:

Unlike many of the other networking stocks on this Top 15 list, Astera is below its average multiples, with shares nearly one-third off the highs. On the top line, Astera trades at 23.8x forward PS, around 10% below its five-year average of 26.6x and far below its 50x peak at the highs of $250 in September.

On the bottom line, Astera trades at 71.5x forward PE, nearly 13% below its 82x five-year average multiple, with shares having traded as high as 140x in September and as low as 30x last April.

Risks:

Astera has faced some fears in the past that ESUN will become a viable third option due to the familiarity of Ethernet, though PCIe solutions remain in high demand and likely will remain relevant in next-gen GPU systems. On the financials, Astera does have to face decelerating growth rates from tougher comps, with current consensus pointing to 77% growth next quarter to 36% by the end of this year.

SiPho Stock Could See 8X increase in Orders

Our Advanced Market Signals members received an analysis and real-time trade alerts for a supplier of optical modules that has outlined plans to expand capacity for 800G and 1.6T products by 8.5× by year-end. Management reiterated on both Q1 and Q2 earnings calls that the expansion remains on schedule. Equipment ordered earlier this year has begun arriving, and production is expected to scale through the second half.

This expansion stands out in the context of an industry that is growing materially, but not at that rate. Industry demand for 800G and 1.6T optics is generally expected to grow at a multiple closer to 3× this year. A capacity ramp that exceeds industry growth implies a strategic effort to capture incremental share as volumes move higher in 2025 and into 2026.

To learn more—including how this company is rapidly expanding its facilities, why that capacity supports a faster ramp than the broader networking trend, and the resulting revenue implications—join Advanced Market Signals today.Advanced Market Signals today. Members receive real-time trade alerts, access to the I/O Fund’s momentum stock list (including this silicon photonics name), and weekly webinars every Thursday at 4:30 p.m. ET. To Join Advanced with 30% off, please click here to email usplease click here to email us

Key Supplier to the Next Ethernet Upgrade Cycle

On the I/O Fund’s Discovery tier, we recently covered a Broadcom networking supplier that sits at the center of Broadcom’s Ethernet roadmap, supplying customized systems to two major hyperscalers plus a major deal with OpenAI for 2027.

Growth opportunities are primarily centered around its high-bandwidth Ethernet switch portfolio focused on back-end networking, with the company being the leading supplier with 41% share of the >200G switch market through Q2, and with 55% share of the custom switch market (up from 40% in 2024).

The back-end networking positioning is important for this Key Supplier stock as it means the company is exposed to the faster-growing segment of Ethernet switching – the back-end TAM is forecast to grow at a 56% CAGR through 2029 on scale-out, and potentially soon, scale-up demand, whereas front-end (user-facing) is forecast to grow at a 20% CAGR.

The next leg of growth is expected with the transition to 1.6T switches, which will introduce higher system complexity, new cooling architectures, and expanded content per rack. Initial customer ramps are expected to begin in late 2026, with broader adoption unfolding through 2027.

To learn more about this company’s positioning within high-bandwidth AI networking and how it fits into the upcoming 800G and 1.6T upgrade cycle, access the full write-up in the Discovery tier. To subscribe to Discovery with 40% off, click here to email usclick here to email us or email premium@io-fund.com and mention code DISCOVERY40DISCOVERY40

AI Energy Stocks

Please reference above under our Top 3 trends for thematic commentary on Tech’s biggest bottleneck: AI Energy.

Bloom Energy:

Overview:

Bloom Energy needs no introduction to our Research Members as it was one of our biggest winners last year with a return of 376%. Knox carefully layered in at the lows, outperforming Bloom’s 2025 returns of 291%. Even when our trims proved to be too conservative, we gladly bought back near the levels we sold.

Grid interconnection timelines are now misaligned with AI deployment timelines. Utilities often project power delivery in 2028–2029, while hyperscalers need capacity in 2025–2027. Bloom Energy is bridging an important power gap in data center expansion as grid access and delays is becoming a limiting factor. What they offer is onsite power generation through solid oxide fuel cells that are behind the meter to reduce dependency on the grid.

The thesis can be summarized in three words: time to power. Here is what management described as to the competitive advantages regarding time to power for solid oxide fuel cells: “A big shift in our business today is time to power. We are providing solutions to meet the urgent needs of our customers who cannot fulfill their power needs from the grid. In these cases, we rapidly book, build, ship, install and power sites for our customers in a matter of months, a much faster timeline than a grid connection.”

For example, over the past quarter, Bloom stood power up for Oracle in 55 days – lightning fast compared to other power solutions. The company counts one massive energy partner Brookfield, two hyperscalers and one neocloud as customers (ORCL, AWS via AEP and CRWV) plus they hinted of a fourth large customer in the previous earnings call via a gas company partnership. Additionally, Brookfield is a capital partner that can bring Bloom Energy from the MW-level to the GW-level.

Higher utilization rather than relying only on capacity growth can also help drive higher revenue for Bloom. For example, there was a hint on the last earnings call that despite doubling capacity, Bloom may be able to expand revenue by 4X over the coming quarters, stating: “As we have previously announced, we are doubling our capacity to 2 gigawatts by December 2026, which will support about 4x our 2025 revenue. That expansion is all systems go. Bloom's capacity will not be a bottleneck for our customers.”

Overall Revenue Growth:

Bloom smashed analysts' revenue estimates by 21.3%. The company reported record revenue of $519.05 million, versus estimates of $428.07 million. Revenue grew by a solid 57.1% YoY and 29.4% sequential growth, accelerating 37.6 percentage points from the previous quarter’s YoY growth of 19.5%.

AI Segment Growth:

Products revenue grew by 64% YoY to $384.3 million, accelerating from the 31% growth in Q2.

Installation revenue growth spiked 105% YoY to $65.78 million, accelerating from a (13%) decline in Q2

Earnings:

GAAP EPS came at ($0.10) in Q3 compared to ($0.06) in the same period last year. GAAP EPS was negatively impacted by a one-time loss related to unconsolidated affiliates of ($19.6 million) or a ($0.08) per share.

The company reported adjusted EPS of $0.15, beating estimates by 47%, and was up from ($0.01) in the same period last year and $0.10 in the previous quarter. Bloom reported strong profits growth driven by operational efficiency, product cost improvements, and operating leverage.

Analysts expect adjusted EPS of $0.31 in Q4 and $0.04 in Q1. Looking forward, adjusted EPS is expected to grow strongly by 84.7% YoY to $0.93 in 2026 and 122.4% to $2.07 in 2027.

Margins:

Q3 gross profits grew by 92.7% YoY to $151.68 million or a gross margin of 29.2%, up 5.4 percentage points YoY and 2.5 percentage points sequentially. Similarly, adjusted gross margins showed strong YoY and sequential improvement, primarily driven by product cost improvements and manufacturing efficiencies.

Operating margins improved 4.4 percentage points YoY and 2.4 percentage points sequentially to 1.5%, primarily driven by strong operational efficiencies. Adjusted operating profits grew by 470% YoY to $46.2 million or an adjusted operating margin of 8.9% compared to 2.5% in the same period last year and 7.1% in the previous quarter.

Cash:

Q3 operating cash flows were $19.67 million or 3.8% of revenue compared to ($69.5M) or (21%) of revenue in the same period last year. Operating cash flow improvement was primarily driven by higher profits and working capital improvements.

Strong operating cash flows also led to higher free cash flows. Q3 free cash flow was $7.4 million or 1.4% of revenue compared to ($83.8 million) or (25.4%) in the same period last year.

Valuation:

Bloom Energy is trading at a forward P/S ratio of 13.8. The company has traded at a minimum of 1.4 and a maximum of 17.8. Bloom Energy is trading at premium valuation as the company is a key player in solving the AI data center power bottleneck.

Notable Risks:

The valuation is a risk, yet we are less concerned as Bloom Energy is a key beneficiary of the AI-driven energy demand.

GEV: Nat Gas Behemoth – Boring but Steady

GE Vernova is the world’s largest gas turbine supplier at 25% ahead of Schneider at 24%. Even still, GEV nearly tripled its gas turbine equipment this past quarter – a statement that has us sitting up in our seats. Per the earnings call: “Power orders grew 44%, led by Gas Power equipment nearly tripling year-over-year.”

Also, consider that we have been covering Bitcoin miners and other energy sources that can quickly help hyperscalers secure powered shells in the 1GW to 3GW range – yet GEV has 50 GW in backlog for gas equipment contracts with expectations the backlog will reach 60 GW by the end of this year. In other words, the chances that GEV is not a significant player in supplying energy to data centers for many years to come is nil.

In a bid to supply options quickly to alleviate bottlenecks, GEV is also shipping aeroderivative gas turbine packages and doing extensive R&D on a small modular reactor (SMR) design. As detailed below, how exactly GEV evolves to solve the crucial bottleneck around AI power consumption is not set in stone, rather the company is experimenting rapidly with how to leverage their deep experience in natural gas, electrification and renewables like wind to meet global demand.

Overall Revenue Growth:

GE Vernova Q4 revenue grew by 3.8% YoY to $10.96 billion, beating estimates by 7.1%. Organic revenue grew by 2% YoY to $10.8 billion. The company is a major beneficiary of the increasing energy requirements from the global AI infrastructure build-out, positioning the company as a key beneficiary of this secular trend. The continued slowdown in the Wind segment was offset by the growth in power and electrification segments that are benefitting from rising electricity consumption driven by data centers and artificial intelligence demand.

The company’s revenue growth is expected to accelerate to 9.8% YoY growth to $8.8 billion in Q1 and is expected to grow 7.8% YoY to $9.82 billion in Q2 2026.

AI Segment Growth:

Q4 power segment revenue grew organically by 5% YoY to $5.7 billion. Management expects high single digit organic growth in Q1.

Q4 organic electrification revenue grew by 32% YoY to $2.9 billion primarily driven by strong growth in switchgear and HVDC equipment. Management expects a similar revenue as Q4 in the next quarter which will also include Prolec GE.

Due to a sudden surge in AI-related electricity demand, the company’s turbine orders are vastly outpacing demand, and the company’s order book is sold out through 2028.

Earnings:

Analysts expect strong EPS growth in the coming quarter with Q1 EPS expected to grow 127.7% YoY to $2.07 and Q2 EPS to grow 65.1% YoY to $3.07.

Margins:

The company’s adjusted EBITDA grew by 7.4% YoY to $1.16 billion with an adjusted EBITDA margin of 10.6%, an improvement of 250 basis points sequentially and 40 basis points YoY. Organic adjusted EBITDA margin improved 10 basis points YoY to 10.7%.

2025 adjusted EBITDA margin improved 260 basis points YoY to 8.4% and was in-line with the management mid-point guidance of 8.5%. Management expects 2026 adjusted EBITDA margin to improve to 12% in 2026 driven by growing backlog, favorable pricing, and improved operational efficiency. Management also expects adjusted EBITDA to be more second half weighted with highest revenue and adjusted EBITDA in Q4 2026.

Q4 net income was $3.7 billion or 33.5% of revenue compared to $484 million or 4.6% of revenue in the same period last year. The Q4 net income included a one-time tax benefit of $2.9 billion.

Cash:

Q4 free cash flow grew by 214.7% YoY to $1.8 billion with a free cash flow margin of 16.5% compared to 5.4% in the same period last year.

The company had cash of $8.85 billion and no debt at the end of Q4.

In early February, the company expects to issue roughly $2.6 billion of debt in order to complete the previously announced acquisition of the remaining 50% ownership stake of Prolec GE.

Valuation:

GEV trades at a forward P/S ratio of 4.3. The company has traded at a minimum forward P/S ratio of 1.0 and a maximum of 5.3. Similar to Bloom Energy, the company is trading above the mid-range as it is a key beneficiary of rising energy demand from the global AI infrastructure build-out.

Notable Risks:

Valuation remains a key risk to monitor, alongside the ongoing weakness in the Wind segment. That said, management expects a meaningful recovery in the wind business to materialize in the second half of 2026.

Please note, GEV reported earlier today with updated earnings report hitting inboxes Thursday.

PJM Auction Stock: A Stock that Benefits from Grid Stress

For our Discovery tier, we covered a stock that is grid dependent with up to 13GW of power, of this 1.9GW is contracted with a hyperscaler. The remaining capacity includes gas plants that are grid dependent, which means it does not solve time-to-power, but rather is a leveraged bet on auction pricing and wholesale pricing. These gas plants offer sizable capacity as they generate electricity for the grid rather than being load specific.

Although this company does not solve the urgency around the AI data center expansion as transmission and grid allocation remain hurdles, it materially benefits as PJM pricing tightens. The investment thesis for the 13GW is that grid stress would cause the loads to run more often and clear at higher energy and higher capacity pricing.

In our Discovery analysis, it’s pointed out that due to the rapid tightening in power supply, clearing prices for the PJM auction have surged to the tune of 11X over the past two years. Much of this arose in the 2025/26 auction, where clearing prices jumped 833% from $28.92/MW-day to $269.17/MW-day, reaching the annual cap. The 2026/27 auction saw prices once again hit the FERC-approved cap at $329.17/MW-day, a 22% YoY increase.

As a merchant generator, this stock benefits from grid stress. Although hyperscalers must solve the issue of transmission, such as building data centers near the power assets, this can be hard to produce at scale. To help alleviate this, the operator is targeting regions popular for data centers for current capacity and newer acquisitions, such as Pennsylvania, Ohio and Maryland.

To learn more about stocks in our new idea generation (NIG) pipeline, including a Top 10 list of NIG stocks, join Discovery todayjoin Discovery today. To subscribe to Discovery with 40% off, click here to email usclick here to email us or email premium@io-fund.com and mention code DISCOVERY40DISCOVERY40

AI Software: Tougher Trade than Previous Cycles

The I/O Fund has approached the AI software trade with caution as it’s been our contention that cloud software will go through a period of consolidation. In fact, we expressed this quite clearly in December of 2022, stating in the article “Slowing Growth in Cloud Stocks: When Will We Hit a Bottom?”

“In some ways, the Q4 guides – assuming most come in at or near those guides – marks a historic slowdown for cloud as it’s always been a resilient category.”

I emphasized this again in March of 2023:

“There are a lot of cloud software bulls and for good reason, this category has treated investors well with predictable revenue growth. Cloud software is resilient because it drives down costs and increases productivity. We know this scenario well as we wrote about it many times in the past few years to defend cloud. Often, cloud selloffs were welcomed to position for a 6-month bounce back after the category sold off (40%) or more. I pointed this out in the past on the free side and here on MarketWatch (behind paywall) in 2019 (i.e., when we weren’t facing a brick wall on growth).

The issue with this assumption is that Cloud growth is actually slowing down —- that is the reality of things —- and this wasn’t true in 2019 and hasn’t been true in the last decade. Couple this with weak bottom lines that require cash injections, and what get is a sector that is largely out of favor.”

Around that time, I was on Real Vision and was asked for a long-only pick (I chose NVDA) and which stock(s) I would short (I chose GTLB and Bill.com). Here are the results after three years:

I share this perspective because the opportunity cost in technology is immense—staying invested in the wrong areas can be just as costly as missing the right ones. While we spend significant time on AI semiconductors today, many of our Research Members originally found us through cloud software ahead of COVID. At that time, we made a deliberate—and unpopular—call that it was time to move on from cloud and reposition for what was next.

How does this apply to AI software?

First, we continue to see downward pressure on cloud stocks. Anthropic was the cause of a selloff recently after the company announced Claude Cowork, a new autonomous agent tool that builds spreadsheets, draft reports, browses the web and executes multi-step tasks. This marks an early attempt for an R&D firm to go after recurring, high-margin enterprise software budgets. Frankly, it makes a ton of sense that R&D firms will go for this low-hanging fruit, which is enterprise software that is not AI native.

Overall, I predict that we will see immense disruption in the software layer to where the I/O Fund is considering very few software stocks for our portfolio at the moment. For every Palantir, there will be dozens that do not survive the incoming AI inference cycle.

This is distinct from hardware, where in many instances, legacy players offer the most competitive solution given the hardware cycle requires many iterations, requires deeply entrenched supply chains and large, upfront capital investments compared to software. The barrier to entry on hardware is quite high, and that ultimately has played out well for public investors since the biggest winners across compute, networking, memory and power components are on the public markets as opposed to being smaller teams incubated in the private markets.

Conservative tech investors looking for a small slice of AI exposure will gravitate toward software and may capture a winner or two, but that approach does not represent the full-fledged AI participation our portfolio seeks. Those who chase high-margin, recurring revenue only are not seeing the full picture, which is that software is the easiest path to compete and ultimately disrupt.

Finally, because the Street tends to stick to what is familiar, software valuations will skyrocket leaving most investors exposed to buying high from the exuberance and selling low when early participants take gains. Avoiding this trap is critical.

I took the long way to say that AI hardware remains the easier trade for public investors, while private investors will gun for the software market. CrunchBase says North American AI startups raised ~$168B in 2025, led by OpenAI’s $40B round and Anthropic’s $13B round, with funding soaring 46% in 2025. Eventually, venture capitalists will cash-in by putting leading AI software companies on the public markets, but it benefits them to wait a few years. Meanwhile, the I/O Fund is hard at work to make sure our Members can participate early in the cycle, and strategically too – I have no interest in waiting for AI software IPOs with bloated valutions when this report contains stocks supplying that private capital today.

With that said, we have our eyes on the following stocks:

Reddit: Contextual, High-Intent Data

Reddit represents monetization momentum in the AI era as its data is highly valuable for training LLMs. There is something far more important that Reddit provides in the AI era than simply a forum; rather Reddit offers a continuous supply of human-generated conversations. What was once a forum is now a wealth of opinions and loads of sentiment that AI models desperately need to produce more natural and sentient-sounding responses. A few months back, Reddit announced they are suing companies like Perplexity and Anthropic for scraping their site.

In exchange for data, Reddit ranks high on Google Search and in AI search results from Open AI, as well. This has helped Reddit move from #85 ranked site to #2 and #3 in 2025. In the last earnings call, management stated they are currently ranked #3: “Today, Reddit is the #3 most visited site in the U.S. for Semrush October 2025. That puts us in a rare company. YouTube is #2 and Amazon is #4.”

The increased search ranking helped Reddit grow both their daily active users (DAUq) and weekly active users (WAUq) at a rate of 20% YoY.

From the IOF’s internal checks, as of January 15th, Reddit has continued to have the 3rd place among the most visible site with YouTube taking the 2nd place spot.

For user engagement, our internal checks show that Reddit notched 3.972 billion visits in October, up 4.5% MoM. For November, it was down (0.70%) MoM to 3.945 billion, better than Facebook’s decline of (4%) MoM to 11.27 billion. For December, Reddit’s monthly visits grew by 6.8% MoM to 4.2 billion, while Facebook’s MoM visits grew by 5.1% to 11.85 billion.

With that said, Reddit’s report is not a slam dunk. First, the logged-out user growth is outpacing the logged-in user growth, which will take some getting used to for Street analysts as they often imply in the Q&A that logged-out users don’t monetize as well. Reddit may ultimately prove this wrong, but as an analyst team, we like to note where nearly-perfect fundamentals face headwinds. In this case, the concerns are not rooted in results, as the company has reported strong financials since the Google-sparked inflection.

The company is rumored to be seeking a dynamic pricing model “where pay would be determined by how useful or important content is to the answers generated by AI tools.” This could provide more upside to Reddit’s data licensing side, which currently accounts for 6% of revenue in Q3, considering how frequently it is cited in AI Overviews and on ChatGPT.

During the last earnings call, an analyst noted that roughly half of Reddit’s traffic is direct, while half comes from Google. Management confirmed the 50/50 split is “approximate, but pretty close.” This means Reddit is receiving an additional benefit from Google that isn’t fully visible within the data licensing revenue line item – rather, it’s mainly visible in the strong advertising growth from the traffic Google is sending to Reddit. Overall, the true impact of Reddit’s partnership with Google is hard to quantify.

Overall Revenue Growth:

Reddit once again reported stellar revenue growth of 67.9% YoY and 17.1% QoQ to $584.9 million. Revenue growth was more than 60% for the fifth consecutive quarter. The company’s Q3 revenue beat the analyst’s estimates by 6.4%. The strong growth was primarily driven by 74% YoY growth in the advertising revenue to $549 million. The total active advertising customers grew by over a solid 75% YoY as the company added new accounts across businesses, including large mid-market and SMB businesses.

While its other revenues, which include licensing deals with Google and OpenAI, rose by a modest 7% YoY to $36 million. Regionally, revenue grew 67% and 74% YoY in the US and internationally, respectively

AI Segment Growth:

The company’s Q3 Average revenue per user (ARPU) grew by 41% YoY to $5.04. Management believes that this is still low on an absolute basis and remains an opportunity for the company. Though growth has decelerated from 47% reported in Q2 due to tough comps, it was up 11% on a sequential basis.

The US ARPU grew by 54% YoY to $9.04, a 5-point deceleration from a strong 59% YoY growth in Q2. However, it grew by 15% sequentially.

The International ARPU grew by 39% YoY to $1.84, a slight deceleration from the 40% growth reported in Q2 and was up 6% sequentially.

The company’s Daily Active Uniques (DAUq) are witnessing strong international growth. The Daily Active Uniques (DAUq) global grew by 19% YoY to 116 million. While US growth is stabilizing as it grew by 7% YoY to 51.6 million, it showed a sequential growth of 3%, while it was flat in Q2. The international DAUq growth was solid as it was up 31% YoY to 64.4 million.

The company’s Weekly Active Uniques (WAUq) grew by 21% YoY to 443.8 million. International growth outpaced US growth as it grew by 37% YoY to 256 million, while the US grew by 6% YoY to 187.8 million.

Earnings:

Analysts expect strong EPS CAGR of 49% during the period 2025 to 2027. EPS is expected to grow from $2.32 in 2025 to $12.74 for the year 2030, growing at a CAGR of 41%.

The company’s Q3 GAAP EPS grew by 400% YoY and 78% sequentially to $0.80, beating analyst estimates by a solid 53.8%. Analysts expect EPS to grow 119.6% YoY to $0.79 in Q4 and 226.7% YoY growth to $0.42 in Q1 2026. Looking forward, they expect EPS to grow 76.3% YoY to $3.35 in 2026 and 39.9% YoY to $4.69 in 2027.

Q3 adjusted EBITDA grew by 151% YoY to $236 million. Adjusted EBITDA margin improved by 13.3 percentage points YoY and 6.9 percentage points sequentially to 40.3%, beating the management guidance by 5.1 percentage points.

Margins:

Q3 gross profits grew by 69.7% YoY to $532.4 million with a gross margin of 91%. The gross margin is up 90 basis points YoY and up 20 basis points sequentially. The company reported its fifth consecutive quarter of above 90% gross margins.

Operating income was $138.5 million compared to a mere $6.9 million in the same period last year. Operating margin improved by 21.7 percentage points YoY and 10.1 percentage points sequentially to 23.7%, primarily driven by operating leverage.

Cash:

The company reported strong cash flows primarily driven by record profits.

Q3 operating cash flows grew by 158.6% YoY to $185.16 million with an operating cash flow margin of 31.7%, up 11.1 percentage points YoY.

Q3 free cash flows grew by 160.5% YoY to $183.1 million, with a free cash flow margin of 31.3%, up 11.1 percentage points YoY. The company generated $510 million in free cash flows in the last twelve months.

Valuation:

Reddit is trading at a forward P/S ratio of 13. The company has traded at a low of 4.2 and a high of 24.4 since the company’s listing in March 2024. Reddit is currently trading at the mid-range. On the bottom-line, the company is trading at a forward P/E ratio of 35.3 with a low of 18.3 and a high of 95.8. It is trading lower than the mid-range of 57. It is also important to note that the company only achieved GAAP profitability in Q4 2024, which limits the usefulness of earlier P/E comparisons. Looking ahead, earnings growth remains strong, with EPS expected to increase from $2.33 in 2025 to $12.73 by 2030, representing a 40.4% CAGR and suggesting meaningful upside as profitability scales.

Notable Risks:

Reddit’s primary risk is the surge in traffic relies on a third-party relationship with Google that could be terminated at any time. It may not be terminated given the emphasis on contextual data for models, yet the recent success hinges on this data licensing deal.

AppLovin: Sentiment Doesn’t Match Fundamentals

AppLovin is a stock that needs a strong technical analysis overlay. Despite fundamentals that rank the company as one of the strongest FA stocks in the tech sector, the market struggles with AppLovin following short seller reports and other sentiment-driven concerns.

From a 10,000-foot view, AppLovin is in the crosshairs of Big Tech, as it’s one of the only grassroots companies to emerge as a formidable data-driven advertising player since the walled gardens of Facebook and Google solidified in the early 2010s. It’s unfortunate that healthy competition to Big Tech often has a target on its back, as I’ve seen many times throughout the years (Zoom’s so-called security and encryption issues come to mind when they offered similar settings as Microsoft Teams).

Point being, it’s hard to find fault in AppLovin’s exceptional fundamentals, yet technicals suggest there will be continued volatility that must be closely navigated.

Regarding potential catalysts, although very early and based on small numbers, management stated AXON’s self-serve feature is seeing strong traction with advertiser spend growing 50% week-over-week since the launch October 1st. This is invite-only, referral-based demand in the e-commerce vertical with the platform expected to open up more broadly in early 2026.

“While it takes a while for new customers to get going, to integrate, to learn how to use our system and to ramp spend, we're already seeing spend from these self-service advertisers grow around roughly 50% week-over-week. It's too soon to be significant, but this type of early growth gives us even more confidence that our platform will excel at being an open platform to any type of advertiser.”

According to management, their AI models continually learn for better behavior targeting and ad personalization. Generative-AI based creatives are also a feature being built out to generate more effective ads (also leading to higher conversion rates). An area where Applovin sets themselves apart is the 35 second ad creatives compared to 7 seconds on social, which could (presumably) also lead to higher conversions.

According to management, improving conversion rates is a path to sustained growth: “We believe that giving our powerful recommendation engine, a more diverse set of advertisers to recommend will dramatically improve conversion rates, paving the way for elevated growth rates for years to come.”

Overall, it’s important to remember that Applovin is demand constrained rather than supply constrained as they reach over 1 billion users. Therefore, opening up the AXON ad manager to more demand is the primary catalyst for the next few quarters.

Overall Revenue Growth:

AppLovin reported strong revenue of $1.405 billion, beating analysts' estimates by a solid 4.7%. The company’s revenue grew by 68.2% YoY and 11.6% QoQ.

However, investors should be aware that App’s long-term target is much lower at 20% to 30% – yet management has openly discussed their path to > 30% growth. At Goldman Sachs’ Communacopia conference, executives dove deeper into the long-term growth framework provided in Q2, calling for a baseline 20% to 30% annual growth. Management explained that this hinges on two primary factors: reinforcement learning and continuous improvement on the ad engine, and opening the recommendation engine up to e-commerce and exposing it to a wealth of new demand.

The update regarding 20% to 30% growth is the self-service platform could help exceed this baseline: “We're still believing very confidently in this 20% to 30% long-term growth rate in our core category. But even in the core, we're beating that. And then now you're layering on, on top of that, all this opportunity with the self-service platform”

AI Segment Growth:

The company’s Q3 advertising revenue grew by 68.3% YoY to $1.405 billion. The ad revenue exceeded the management guidance by a solid 5.6%, primarily driven by strong gaming advertising revenue.

Management guided advertising revenue of $1.57 billion to $1.60 billion, representing a YoY growth of 58.6% at the midpoint. Management stated that the guidance incorporates optimism around the e-commerce referral program, continued model enhancements, and the normal holiday seasonality.

Earnings:

Gross profits grew by a solid 72.2% YoY to $1.23 billion, with a gross profit margin of 87.6%. The gross profit margin was up 210 basis points YoY and down 10 basis points sequentially.

Operating profits grew by 102% YoY to $1.08 billion, driven by solid operating leverage. The operating margin improved by 12.8 percentage points YoY to 76.8%.

Margins:

Gross profits grew by a solid 72.2% YoY to $1.23 billion, with a gross profit margin of 87.6%. The gross profit margin was up 210 basis points YoY and down 10 basis points sequentially.

Operating profits grew by 102% YoY to $1.08 billion, driven by solid operating leverage. The operating margin improved by 12.8 percentage points YoY to 76.8%.

Cash:

Q3 operating cash flows grew by 91.3% YoY to $1.05 billion with a margin of 75%, up 9.1 percentage points YoY.

Q3 free cash flows grew by 92.4% YoY to $1.049 billion with a free cash flow margin of 74.7%, up 9.4 percentage points YoY.

The company’s cash improved to $1.67 billion, up from $1.19 billion at the end of the previous quarter. While debt remained the same at $3.51 billion.

Valuation:

APP is trading at a forward P/S ratio of 22.7. The company has traded at a minimum of 1.1 and a maximum of 43.2. On the bottom line, the company is trading at a forward P/E ratio of 37.6. APP has traded at a minimum of 3.1 and a maximum of 73.1 in recent years. Currently, it is trading at mid-range.

Notable Risks:

APP is the subject of short reports, and the company has been under an SEC probe over its data collection practices. In addition, the stock’s strong outperformance over the past three years raises the bar for future execution, as market expectations are elevated. However, we think the AI-powered ads business model, which has driven strong revenue and profit growth and a strong market presence, is worth a shot, especially when using technicals to guide our entries and exits.

Cloudflare: Early but the Positioning is One of a Kind

As pointed out in our analysis: “Cloudflare Entering Act 3 to Become a Leader in AI Inference at the Edge,” the company has a few distinct advantages as the platform of choice for AI developers. Here’s a summary:

Does not rely on Big 3 infrastructure and can drive down costs
Is faster on performance because of its position at the edge; this lowers costs and latency for AI inference and keeps data as close to the user as possible
Geographically equipped to handle compliance issues that will inevitably result from using training data for inference.
The company has moved diligently into compute, storage and application services. Combined with its global network, this positions the company for AI inference as-a-service. There is no other company doing both edge network plus compute and storage except the hyperscalers. However, in some cases such as serverless, Cloudflare exceeds the performance of the hyperscalers.
CDN as a core product and security as a seamless upgrade shows the importance of being a middleman, helping to position Cloudflare to innovate around Serverless in ways that outperform even AWS.
Training models is prohibitively expensive by requiring upfront costs, Nvidia GPUs are hard to obtain, and AI development is not democratized for developers with proprietary, blackbox APIs that run counter to an open-source movement (GPT-4 versus Llama). Cloudflare aims to solve these problems by allowing popular models to run closer to the user, which is the next logical step for AI.

Ultimately, the bigger and the faster a network is, the more it’s capable of providing “as a service.” AI can create a fortuitous moment for Cloudflare because the company is both positioned to offer AI inference-as-a-service yet also solves important pain points for developers.

Overall Revenue Growth:

Cloudflare reported its largest beat since Q1 2022, reporting revenue of $562.0 million in Q3, 3.1% ahead of estimates as growth accelerated nearly three points to 30.7%. This also marked Cloudflare’s first >30% growth quarter in the past five and its fastest revenue growth in the last seven quarters. This is the first step in confirming a sustained revenue acceleration aided by AI, yet the more important piece is showing that >30% growth can actually be sustained.

For Q4, Cloudflare guided for revenue of $588.5 to $589.5 million, a slight deceleration to 28% on the topline. This was ahead of estimates for $580.8 million

AI Segment Growth:

Cloudflare has not broken out specific AI revenue or contribution to growth, although other key metrics strengthen significantly in Q3.

RPO was $2.14 billion, accelerating four points to 43% YoY, while current RPO accounted for 64% of RPO, or ~$1.37 billion. Current RPO rose ~30% YoY, a three point deceleration from 33% in Q2. Billings growth accelerated sharply, from 33% in Q2 to 40% in Q3, rising to $624.4 million.

Paying customer growth accelerated six points sequentially to 33% YoY, impressive at this scale considering paying customers now total 295,552. Growth was 10% QoQ, the highest on record since at least 2022. Additionally, DBNRR ticked five points higher sequentially to 119%, the highest since Q4 2022, driven by accelerating spending at its largest customers

Earnings:

Cloudflare reported a solid adjusted EPS beat in Q3, reporting 35% YoY growth to $0.27 versus the $0.23 estimate. GAAP EPS was on the brink of shifting to positive territory at ($0.00), versus the ($0.07) estimate.

For Q4, Cloudflare guided for adjusted EPS to be flat QoQ at $0.27, up 42% YoY. For fiscal 2025, Cloudflare raised its adjusted EPS forecast to $0.91, up from $0.85 to $0.86 previously. However, GAAP profitability is not expected on an annual basis until 2027.

Margins:

GAAP gross margin was 74.0% in Q3, down 3.7 points YoY and 0.9 points QoQ. Adjusted gross margin was 75.3%, down 3.5 points YoY and 1 point QoQ, again impacted by increases in allocated costs from higher network traffic from paying customers.

GAAP operating margin was (6.7%), up 0.5 points YoY and 6.4 points QoQ. Adjusted operating margin was 15.3%, up 0.5 points YoY and 1.2 points QoQ; for Q4, adjusted operating margin was guided to be 14%. GAAP net margin was (0.2%), up 3.4 points YoY and 9.6 points QoQ. Adjusted net margin was 18.3%, up 1.4 points YoY and 3.6 points QoQ.

Cash:

Operating cash flow was $167.1 million for a 30% margin, up from a 24% margin in the year ago quarter and a 19% margin in Q2. Free cash flow was $75 million for a 13% margin, up from 11% in the year ago quarter and 6% in Q2. Network capex was 14% of revenue.

Cash, equivalents and available-for-sale securities totaled $4.04 billion, while convertible notes outstanding totaled $3.26 billion.

Valuation:

Cloudflare is trading at a forward P/S ratio of 22.2. The company has traded a minimum of 10 and a maximum of 41.4 in the last few years. Cloudflare is trading slightly lower than the mid-range after the recent weakness in its share price.

Notable Risks:

The company is not yet GAAP profitable even after 16 years of the company’s operations.

Palantir: The Trade-Off Between Discipline and Conviction

Since 2023, Palantir’s stock has defied gravity, delivering steady performance that no other AI software stock has come close to matching (yet). The thesis is two-fold: the company must continue to scale its Commercial segment after posting multiple quarters of over 50% growth, while also sustaining a high valuation. Both matters and the bar is undeniably high.

What separates Palantir, however, is not simply growth, but capability. The differences matter as unlike traditional AI-enabled database or business intelligence competitors, Palantir can operate effectively even when data sets are incomplete or fragmented—situations where most models struggle. In that regard, traditional business intelligence companies require a complete data set, whereas Palantir can handle situations where one isn't available. You can think of the competitive advantage as actionable depth, as Palantir has described it: “the reasoning that goes into decision-making, not just data.”   

Palantir’s Artificial Intelligence Platform (AIP) integrates generative AI with operational data and workflows, and, when combined with Palantir’s other platforms, Foundry and Apollo, it provides an AI service mesh that can run hundreds of microservices, scale compute via its Rubix engine, and orchestrate updates through Apollo.  

Additionally, Palantir’s knowledge graph, referred to as Ontology, is a distinct advantage. The graph offers better context than a large language model would on its own – or as Palantir states, it’s “the reasoning that goes into decision-making.” Palantir made key upgrades to AIP with the introduction of AI-forward-deployed engineers (FDEs) and the AI Hivemind, and brought Ontology to the edge, enabling deployment on mobile devices.

Palantir Stock leads the AI software pack, delivering one of the best reports across tech in Q3. Revenue accelerated nearly 15 points sequentially to almost 63%, with strong growth in key metrics and a 28-point acceleration in US Commercial revenue to 121% YoY. The Artificial Intelligence Platform (AIP) is driving most of the Commercial growth, as there was a clear revenue inflection when AIP launched in mid-2023.

The company reported strong key metrics, with net retention rate (NRR) expanding six points sequentially to 134%. Over the past two years, NRR has risen an impressive 27 points, and Palantir noted that AIP is continuing to drive existing expansions and new customer conversions. On the other hand, Palantir’s forward P/S ratio trades at an outstanding 64.4 multiple and has been as high as 112 forward P/S.

I don’t recall another stock the I/O Fund has followed this closely without taking action. That caution was intentional, driven by valuation and our focus on risk management. Ultimately, Palantir is an extreme outlier, to where for those ignoring discipline, it worked out. Often times, it does not work out to buy a stock that trades at up to a 100 forward PS, and that must be weighed carefully for each investor.

Overall Revenue Growth:

Palantir reported $1.18 billion in revenue in Q3, up an impressive 18% QoQ and beating estimates by 8.4%, driven by unwavering momentum in US Commercial. On a YoY basis, revenue growth accelerated 14.8 points to 62.8% YoY, the largest sequential acceleration to date and marking Palantir’s highest growth rate since going public. Over the last nine quarters, topline growth has accelerated ~50 points, from just 12.7% in Q2 2023, a rare feat to accomplish.

AI Segment Growth:

Fueled once again by AIP, Palantir delivered one of the best reports across tech in the third quarter, with revenue accelerating nearly 15 points sequentially to almost 63%, with strong growth in key metrics and a 50 point acceleration in US Commercial revenue since the start of the year.

US Commercial revenue grew 29% QoQ and 121% YoY to $397 million in Q3, accelerating from 93% YoY growth in Q2. Since the start of the year, US Commercial growth has accelerated 50 points, and since the start of 2024, growth has accelerated 81 points.

Earnings:

Palantir reported $0.18 in GAAP EPS in the quarter, up 200% YoY, while adjusted EPS was $0.21, beating estimates by 25.5% and rising 110% YoY. Palantir did not provide a specific guide for EPS for Q4, though current estimates are pegged at $0.12 in GAAP EPS and $0.22 in adjusted EPS, up 300% YoY and 57% YoY, respectively.

For FY25, Palantir is expected to earn $0.72 in adjusted EPS, up nearly 76% YoY, before slowing to 39% growth to $1.01 in FY26.

Margins:

Margins strengthened considerably in the quarter, with adjusted operating margin surpassing 50% with more expansion guided for Q4. Palantir’s Rule of 40 score (revenue growth + adj operating margin) expanded to a wild 114%, up from 94% last quarter and 68% last Q3.

Gross margin was 82% in Q3, up one point QoQ and two points YoY, while adjusted gross margin was 84%, up two points YoY and QoQ.

GAAP operating margin was 33%, an impressive 6 point QoQ and 17 point YoY expansion. Adjusted operating margin was 51%, breaking past 50% for the first time and up 5 points QoQ and 13 points YoY. For Q4, Palantir guided for adjusted operating margin to be 52%, showcasing its ability to drive strong margin expansion alongside swift revenue acceleration. Full year adjusted operating margin guidance was raised from 46% to 49%.

Cash:

Cash flows were strong, though cash flow margins dipped on a YoY and QoQ basis. Operating cash flow was $507.7 million for a 43% margin, shrinking from a 54% margin in Q2 and 58% in the year ago quarter.

Adjusted free cash flow was $539.9 million for a 46% margin, down from 57% in Q2 and 60% in the year ago quarter. Palantir raised its adjusted FCF guidance for the year to $1.9 to $2.1 billion, or a 45.5% margin, up from a 42.8% margin previously.

Cash and equivalents totaled $6.4 billion and debt remained zero.

Valuation:

Palantir is trading at a forward P/S ratio of 64.4. The company has traded at a minimum of 6 and a maximum of 112 in the last few years. The company is trading at a significant premium to the other best of breed cloud companies like CrowdStrike that is currently trading at a forward P/S ratio of 23.7 and Cloudflare at 22.2.

On the bottom line, the company is trading at a forward P/E ratio of 167.6. The company has traded at a minimum of 25.6 and a maximum of 285.9 in the past few years.

Notable Risks:

The company’s primary risk is its high valuation.

CoreWeave: Legacy Cloud IaaS Wasn’t Built for AI

CoreWeave breaks all of the rules, including not cooperating with our portfolio criteria. I’ll get right to the point by saying CoreWeave’s cash to debt is frightening. The company reported FCF of ($1.6 billion) with $14 billion in debt and a mere $2.5B in cash on the balance sheet, leaving a cash to debt ratio of 0.18, or said differently; debt is 5.6X cash at the end of Q3. Notably, this excludes the $2.25 billion convertible senior notes issued in December and on a pro-forma basis, debt is 3.4X cash, for a deep net-debt position and very limited balance-sheet flexibility.

Perhaps most concerning, the debt issues are about to worsen as CoreWeave is expected to spend $6.75 billion in Q4 on capex and over $26 billion in 2026, as management expects capex more than double next year. My best estimate is that 2026 will see 12X debt to cash with what I know today. The only way we would touch this stock is with heavy technical analysis and risk management.

There are lower risk ways to participate in AI, yet the positioning CoreWeave offers is second to none. The company is in the “build” phase but will eventually be in the “yield” phase.

The company also entered the US federal market, which should further help to diversify its customer base. CoreWeave will provide secure, compliant, high-performance AI cloud services to US government agencies and their key partners, including the Defense Industrial Base. NASA already uses its services to advance scientific exploration at its Jet Propulsion Lab.

Altogether, CoreWeave sits on the front lines of the shift from legacy cloud infrastructure to AI-optimized workloads. While the full importance of this transition from cloud to AI is difficult to quantify today, its impact is likely to be transformative for how compute is built and consumed. CoreWeave is positioned at the center of a shift too great to fully envision today.

The closest historical parallel is AWS in the mid-to-late 2000s—before the economics of the build-out were fully visible to investors. The key distinction is that CoreWeave represents a pure-play on AI infrastructure. It is now widely understood that AWS went on to generate the majority of Amazon’s profits, providing investors with a clear blueprint of what the yield phase of infrastructure-as-a-service can look like.

For more information on how CoreWeave is unique compared to the Big 3, including why the model FLOPs utilization (MFU) gap matters quite a bit, reference our article “CoreWeave Stock Soars 200% since IPO – Can it Defy the Odds?”

Overall Revenue Growth:

CoreWeave’s Q3 revenue grew by 133.7% YoY and 12.5% QoQ to $1.37 billion. The company beat analyst consensus estimates by a solid 6.6%, driven by continued strong demand for the company’s AI cloud infrastructure services.

Looking ahead, analysts expect 2026 revenue to grow 132% YoY to $12.23 billion, and these estimates will be increased due to the push-out caused by the delay in Q4 revenue recognition to Q1. For 2027, revenue is expected to grow 49.4% YoY to $18.27 billion.

AI Segment Growth:

The backlog of $55B represents nearly double Q2 and is approaching 4X YTD yet the debt is also up 2X YTD. The company stated the backlog grew by $25 billion to $55.6 billion, up from $30.1 billion for growth of 85% QoQ.

Management also highlighted that they reached $50 billion in RPO, faster than any cloud in history.

Active power footprint grew by 120MW sequentially to approximately 590MW with contracted power capacity growing over 600MW to 2.9GW. That represents 25.5% QoQ growth. Management expects to end the year with over 850 megawatts of active power.

Earnings:

Q3 GAAP EPS was ($0.22) compared to the analysts' estimates of ($0.51). However, the strong beat was due to a one-time noncash tax benefit of $0.25. Excluding the one-time benefit, the company would beat estimates by $0.04.

Looking forward, analysts expect GAAP EPS of ($0.84) in 2026 and to be GAAP profitable in 2027 with an EPS of $1.63.

Margins:

The margins are strong yet the cash remains troublesome. For example, CoreWeave is a recent IPO that is already GAAP positive on operating margin at 4% and reported an adjusted EBITDA margin of 61%.

Q3 gross profits grew by 126% YoY to $995.85 million with a gross profit margin of 73%, down 200 basis points YoY and 100 basis points sequentially.

Q3 operating margin was 4%, down from 20% in the same period last year and up 200 basis points sequentially. The operating expenses increased 181% YoY to support strong growth. The adjusted operating margin was 16%, compared to 21% in the same period last year.

Cash:

The company reported negative free cash flow of ($1.6 billion) with $14 billion in debt and $2.5B in cash on the balance sheet at the end of Q3. This leaves net debt of $11.5 billion – yet this is mild given what the company plans to spend in capex next year (expect the debt to go up rapidly).

Free cash flow was ($1.6 billion) compared to ($573.9 million) in the same period last year and ($2.7 billion) in the previous quarter.

Valuation:

CoreWeave is trading at a forward P/S ratio of 3.8. The company has traded at a low of 3 and a high of 17.2 in the past year.

The company is not profitable for a bottom-line valuation and is expected to be profitable on a non-GAAP basis in Q4 2026.

Notable Risks:

The company has negative free cash flow due to high capex for infrastructure, and it also has high debt.

Honorable Mention: Meta

In a recent analysis entitled “The AI Revenue Leader Nobody is Talking About,” our firm was early to point out that Meta’s AI revenue places it as number two, second only to Nvidia. Although Google has many supportive points as to why the stock outperformed compared to other Big Tech names, the I/O Fund is a growth stock portfolio. Margins matter, cash matters, but what matters more is the 3X growth Meta has seen in its Advantage+ segment in less than a year, as the company had reported $20 billion about three quarters ago, with the recent update from last quarter at $60 billion. If this runaway growth continues, then Meta will easily be outpacing Search and Google Cloud combined on AI revenue.

On the other hand, Meta is witnessing a deceleration in margins due to rising expenses supporting its AI infrastructure. Reality Labs also continues to incur losses, recording a $4.43 billion loss from operations in Q3 2025, and its cumulative losses now total $73.04 billion. Due to continued investments in AI infrastructure, the company’s capex is expected to be significantly higher in 2026.

Meta has the weakest balance sheet among the Big Tech companies, with a net cash position of $15.7 billion. Meta has also entered a joint venture with Blue Owl Capital to fund its development at the Hyperion data center in Louisiana. Thereby, helping it to keep about $27 billion in debt off-balance sheet, where it would sit in a special-purpose vehicle tied to Blue Owl. While this approach may improve reported leverage and financial ratios, it carries inherent risks as the company is indirectly responsible for the off-balance sheet debt.

Despite Meta being in the quality bucket for the most part, its high capex spending necessitates technical analysis and a risk management overlay.

For more information on Big Tech with I/O Fund takeaways, please read our free article “The $530 Billion AI Question: Which Big Tech Stock is Winning?”The $530 Billion AI Question: Which Big Tech Stock is Winning?”

What’s Next for Our Discovery and Advanced Tiers …

Miners have been attracting significant deal activity from neoclouds, with a handful notching hyperscaler deals and growing interest. Miners continue to benefit from their ability to offer hundreds of MW for AI data centers in relatively quick fashion, bypassing interconnection queues for greenfield builds, while also offering lower electricity costs through long-term power contracts. A handful of miners have disclosed power costs around $0.046–0.047/kWh, representing a meaningful discount to PJM’s grid and average commercial electricity pricing.

In an upcoming analysis for our Discovery tier, we will recap three Bitcoin miners leading the push to power AI data centers. One has secured a second multi-billion-dollar AI data center deal with a hyperscaler and is pursuing a multi-GW development pipeline that could represent 7–8X growth from current contracted capacity. Another has signed a nearly $10 billion deal for phased deployment through 2026, while the third is targeting several hundred MWs online in 2026 with additional capacity in pre-development for 2027.

While AI-related revenue contributions remain modest today, growth is expected to accelerate through 2026 and 2027 as capacity comes online. However, the risk with miners is that capex requirements to retrofit facilities often exceed current balance sheet capacity, forcing increased leverage to transition assets from mining to AI-ready infrastructure.

Outside of miners, we are also revisiting nuclear power for Discovery members, including an SMR developer with a multi-GW pipeline. Unlike miners or Bloom Energy, SMRs represent a long-term solution, with commercial operations not expected until closer to the end of the decade.

Conclusion:

The I/O Fund team is ready for the upcoming earnings season armed with a list of stocks we will be watching very closely and many honorable mentions prepared to step-in should one of our chosen stocks not perform as expected.

Following a report of this size, it’s worth pausing to acknowledge a reality that often gets overlooked: AI investing remains difficult for many tech portfolios, despite the growing list of winners and the market’s potential to meaningfully reshape GDP.

This raises a fair question—why do so many hedge funds and ETFs remain underexposed to AI beyond a narrow set of Big Tech names, and why is that exposure so concentrated? The AI trade is actually quite complex and unforgiving, demanding deep product-level analysis, precise timing, and disciplined risk management that many portfolios are not built to execute.

Our goal is to solve that problem for our Members—building on our history from prior cycles, striving to be early to market trends in the near-term, and positioning thoughtfully for the second half of this AI-driven decade.

Damien Robbins and Royston Roche, Equity Analysts at I/O Fund contributed to this analysis.

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Discovery members recently received an analysis on a stock poised to benefit as Nvidia tackles the context memory bottleneck and extends KV cache memory with its new Inference Context Memory Storage platform. To subscribe to Discovery with 40% off, click here to email usclick here to email us or email premium@io-fund.com and mention code DISCOVERY40DISCOVERY40

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Recommended Reading:

The I/O Fund’s Top 15 AI Stocks for Q4 2025

Posted on October 28, 2025June 30, 2026 by io-fund

Last quarter, I began providing a comprehensive ranking of the top AI stocks in our universe. Our portfolio benefited from this exercise, and we hope yours did too.

Perhaps most beneficial is taking a moment on a quarterly basis to be as objective as possible. Information in the form of earnings reports, product announcements, news headlines, and even social media exuberance can cloud an investor’s decisions. It is not only the volume of information, but the speed at which information comes daily to where it can be hard to discern the true winners from those catching a fleeting headline.

The report below is designed to be objective in a no holds barred approach. Because we manage our own money full-time, we are laser-focused on ways to improve on a quarterly basis. Similar to the Q3 2025 report, the analysis below tops out at over 16,000 words, totals 43 pages and took three weeks to write. Even if we’ve held a stock for years, we update the investment thesis and re-examine the fundamentals. There is no stock that is immune to being cut from our portfolio if it cannot prove it’s one of the best AI stocks at this moment. Vice versa, to be added for the first time, a stock must be able to prove it can hold its own among already-strong choices.

After rigorous examination, the list below summarizes the strongest AI stocks of Q4 2025 and the top 3 Thematic Trends that I believe will help drive the AI market to new heights.

AI Networking: The Exponential Investment Opportunity

Each quarter, the I/O Fund scans hundreds of tech companies and their quarterly earnings reports for anomalies. To be precise, we track 188 data points on each portfolio company and top-ranking stocks we don't own totaling about 40 stocks a quarter for a total of over 7,000 data points. This quarter, one metric stands out as truly exceptional: Nvidia’s networking growth of 46% QoQ and 98% YoY to $7.25 billion. In the previous quarter, Nvidia’s networking grew 64% QoQ after declining (3%) in the previous quarter. Management stated the networking to compute attach rate is 75% in the fiscal Q4 earnings call.

Here is why this data point is unique – if Nvidia’s networking segment were a standalone segment, it would place #3 in the world on AI revenue with Azure reporting about $36 billion per year in AI revenue (at $75 billion total with a statement that half is AI-related) versus Nvidia’s networking now on a $28 billion run rate. Broadcom would be fourth at $6.2 billion AI revenue guided for next quarter, or about a $25B run rate.

There’s an argument to be made that Google Cloud or AWS would be in the running, however, they do not breakout AI revenue yet. An investor can also reasonably assume if it was at Azure’s level or higher, they would share their first place standing among the Big 3.

Yet, if any of those leading AI companies grew their AI segment 46% QoQ, their stock would go wild. The metric was missed because it was buried in Nvidia’s Compute weakness/China noise, yet this number is truly the bellwether as we move into Q3.

It also gives me a nostalgic pause as I was early to cover the importance of the Mellanox acquisition in both 2019 and 2020 stating: “Mellanox’s Ethernet switch systems are the most used internal system in the top 500 in a recent report released at ISC High Performance, with 247 systems, and InfiniBand is the second most-used, with 140 systems. However, InfiniBand, a computer-networking communications standard, connects the most high-powered computers where the presence of Ethernet is nearly non-existent […] This is a strategic acquisition for Nvidia and Mellanox to become the strongest combination for artificial-intelligence and machine-learning computations.” You will be hard-pressed to find an equity analyst covering the AI market that closely back in 2019-2020 at the height of Covid.

Turning our attention to 2025 and beyond, we want to look at what stocks are downstream from the number one growth market at scale.at scale. As stated, it’s not only the largest QoQ growth across AI, but rather it’s that Nvidia was able to grow its networking segment 46% QoQ while operating as the world’s third-largest AI segment.

My readthrough is that something important is ramping, and it will be back-half weighted. You’ve known for many quarters that the “something” is the new Blackwell GB200 system. What is newer information is that Blackwell Ultra GB300 is also ramping nearly simultaneously.

Per Nvidia, the strong performance in Networking was driven by “growth of NVLink compute fabric for GB200 and GB300 systems, the ramp of XDR InfiniBand products, and adoption of Ethernet for AI solutions.”

Double-Clicking on the Network Requirements of the GB200s and GB300s

Nvidia’s networking segment is a proxy for the AI networking allocation we hold in our portfolio. The quarterly numbers that Nvidia provide relate to their proprietary InfiniBand networking and the NVSwitches that help to route NVlink connections for GPU-to-GPU communication.

However, as the 75% attach rate above describes, there is a roughly 25% opportunity for other networking vendors to participate. Additionally, there are times that Nvidia will outsource components or cabling rather than build every single component in-house. In some instances, sourcing raw earth materials such as indium phosphide (InP) would prove quite challenging. Therefore, the information below may relate to Nvidia’ proprietary networking, yet it has important readthroughs to carefully selected suppliers.

Generally speaking, networking cables, ASICs and components required for GPU interconnects will increase 5X to 9X as we move from the HGX/DGX systems to the NVL72 systems. Given the GPU count will increase 9X from 8 GPUs to 72 GPUs, it makes sense that networking will increase similarly.

This is inferred by a few key points in terms of how the architecture is shifting from the 8-GPU HGX/DGX systems in the Hopper generation. These older systems that shipped in 2023-2024 used four NVSwitch ASICs to connect eight TensorCore H100 GPUs.

Source: Nvidia Technical BlogNvidia Technical Blog

Networking is at the heart of the Blackwell architecture as the increased bandwidth is instrumental in driving the higher performance. The NVLink domain moves from supporting eight GPUs to 72 GPUs with a speed of 1.8 TB/s. Nvidia’s 5th generation NVLink interconnects will deliver a higher aggregate bandwidth of 9X to 18X compared to Ethernet and InfiniBand in previous generations. By increasing the bandwidth, the NVL72 systems will pool together compute and memory for up to 4X faster training and 30X faster inference.

This is accomplished with 18 NVSwitch ASICs, up from four in the HGX/DGX systems. That’s a 4.5X increase in NVSwitch ASICs.

Source: Nvidia Technical Blog, “Nvidia Contributes Nvidia GB200 NVL72 Designs to Open Compute Project”Nvidia Contributes Nvidia GB200 NVL72 Designs to Open Compute Project”

If you look below at the specs between the larger NVL systems and the two HGX SKUs, you can see it’s not only compute performance that increases 10X (petaFLOPs) but also aggregate memory bandwidth and speeds.

The main takeaway is that scale-up architectures are as much about networking as they are about compute. The goal is to add more GPUs that can effectively distribute training and inference across a large cluster, which includes sharing data and memory, synchronizing, and exchanging model parameters.

Therefore, the interconnect or “connectivity layer” must scale accordingly to prevent GPUs from idling and waiting for data across the increased number of GPUs that are operating in parallel and at scale. High-speed communication is central to Blackwell and future generations of GPUs because the goal of a GPU-cluster is to act as a single processor. As AI systems grow GPUs by 9X, but also clusters grow from 100s of thousands to millions, there will be significantly more components required such as retimers, switch fabrics, silicon photonics, transceivers, cables and controllers.

However, despite Nvidia and Broadcom dominating the AI networking space, there remains immense opportunity for smaller, lesser-known suppliers.

Key opportunities mentioned above include PCIe components, as this is needed to connect the GPU to CPUs, memory and storage. Specialized copper cables are needed to connect AI servers to networking switches, and for linking many servers together. Retimers help to extend data integrity beyond short distances. The jump from 400G to 800G to eventually 1.6T on data rates will require an additional upgrade to nearly every component in the network layer, such as switch ASICs, optical transceiver modules, faster digital signal processors (DSPs) and retimers/redrivers. When it comes to products like EML lasers, the indium phosphide (InP) is hard to source. There is expected to be a new market for co-package optics (CPOs) with the new Rubin architecture – to name just a few of the AI networking opportunities currently in play and also squarely in front of us.

AI Energy: How Much and How Fast?

AI energy is all the rage today, yet it was rarely spoken about when we first covered the trend in the article AI Power Consumption Becoming Mission Critical. That article would later grow into lengthier premium thematic coverage, which would spark winning positions such as Bloom Energy, Oklo, NuScale and our first Bitcoin Miner/AI Data Center position Core Scientific in early 2025 (the first Bitcoin miner to retrofit for AI DCs). When we say we work hard to be early to new trends, we mean exactly that.

While networking can get bogged down in jargon and specs, and suppliers can be dropped quite quickly in the ever-shifting landscape, energy presents an entirely different investing landscape.

The problem that AI energy stocks seek to solve is simple to conceptualize compared to the intricacies of networking. Once a power solution is confirmed, the chances it is dropped from a qualified supplier list in the same manner as a networking stock is less likely. Think of energy to AI as water to humans – a daily essential that is less about the competitive landscape and more about the sheer necessity for survival.

Hyperscalers are spending hundreds of billions of dollars annually on AI data center capex, from physical data center space, GPUs and servers, hardware and networking. With these substantial sums flowing towards GPUs that are now being refreshed on an annual cadence, the impetus for hyperscalers, neoclouds and other cloud providers turns to how quickly these GPUs can secure power and be deployed.

There are three reasons the race is incredibly fierce to power these new systems:

The first reason is the stock market, as the current capex numbers are significant, and investors will want to see a return on this investment. If a company like Microsoft buys tens of billions of Nvidia’s Blackwell GPUs, the longer the massive investment in GPUs waits for power, the more delayed that revenue and profits become.

Secondly, for competitive reasons and to keep up with Nvidia’s product road map, the next generation of GPUs will arrive every 1-2 years and Big Tech will want to maximize returns before the next generation comes online. Competitors who can energize the newest generation of GPUs faster will have a critical head start over those that are waiting for power. But there’s a catch, every generation of GPUs requires more power – for example, there will be a 5X increase between the power requirements of the GB200 NVL72 and the Vera Rubin NVL576 “Kyber” rack over a two-year design timeframe. These figures do not include networking, interconnects, cooling and other hardware, which will further boost power draw per rack.

Third, the AI race is not merely a battle between companies like Google, Amazon and Microsoft. Rather, it is a battle among global powers. While the news has latched onto China-fears such as DeepSeek, tariffs or rare earth materials, the true challenge lies in the fact that China has significantly more power than the United States. In a recent Fortune article, energy experts stated China’s reserve margin has never dipped below 80% to 100% nationwide, meaning it’s at 2X the capacity the country needs. Meanwhile, the United States is at a 15% reserve margin.

These three reasons are simple in concept, yet the lack of power having vast consequences cannot be overstated if you combine the sheer size of investments being made in AI alongside fierce, heightened competition.

The push to 600kW racks over the next few years means this is not a transient problem, rather it is one that the industry will continue to face, meaning continuous new construction may be needed to handle surging power demand. For example, Vantage’s upcoming 1.4 GW campus in Texas for Oracle is designed for ultra-high density racks up to 250kW, yet this will not be enough power to able to host NVL576 racks in just two to three years’ time. Additionally, a former Microsoft Azure AI executive reportedly said he estimated that the “requirements in terms of power for the data center would probably at least double every three years and maybe exponentially so over a period of time,” further reinforcing this.

AI Accelerators:

AI accelerators such as GPUs and custom silicon need no introduction – raw compute and compute performance has driven the AI market up to this point. The analysis would be remiss to not acknowledge the trend that is so powerful, it is displacing the FAANGs of the last decade with Nvidia firmly the world’s most valuable company now and Broadcom within striking distance of passing up companies like Meta.

As the market weighs the so-called AI bubble, there are many disparate facts thrown at investors: dot-com fears, China/tariff concerns, stock pullbacks when there are minor announcements, and things like circular investments from OpenAI.

Forgive me if I sound repetitive, but what truly matters is Big Tech capex. This is the single, most important number as it far outweighs the importance of earnings reports, fiscal year guidance, Nvidia’s networking growth or their product roadmap, if AMD has a new deal from OpenAI, Oracle’s insane RPO, Broadcom’s networking chips and custom silicon announcements – all of the above is being single-handedly driven by Big Tech’s large capital expenditure (capex) budgets.

Let me throw a few stats at you.

Analyst estimates cannot keep up with the capital expenditures being spent on AI infrastructure. This time last year, the expectations were for $250 billion in Big Tech capex. Morgan Stanley later forecast $300 billion in Big Tech capex for 2025. That number stands at $365 billion for 2025 with one quarter left to go.
It’s easy to tune out the words “big tech capex” at this point but zoom out for a minute and consider that Big Tech’s TTM capex was $24B at the start of 2015, or up 15X over ten years.
In terms of the opportunity looking forward, McKinsey is predicting 3.5X growth in gigawatts for AI data centers between 2025-2030. The costs associated with AI data centers range from $3 trillion to $8 trillion, or about $5 trillion at the midpoint. This correlates to about 3X growth if we assume the current run rate is $1.8 trillion at the current capex of $365 billion.
On a more near-term basis, Goldman Sachs sees hyperscaler capex increasing sharply through 2027 – capex is projected to be $1.15 trillion from 2025 through 2027, more than double the $477 billion spent from 2022 through 2024.
Going back to the first point, analysts thus far have missed the mark in their estimates. Every quarter, sell side analysts rush to update their models. We are penciling in that 3x is a baseline to work with over a 5-year time frame.

To be objective, there are analysts calling for a stock market crash based on the risks around the consumer and a GDP that is propped up by capex spending.

Stifel stated in August:

“While the capex boom around AI temporarily supports GDP and asset prices, Stifel forecasts this bump will fade as corporate tech spending plateaus. Such a build-out, after all, occurs only once, while consumer spending power is entering a lull that could expose markets to abrupt correction.”

There is weight to what Stifel is describing, which is why tariffs remained a risk on our last Top 15 report and remain a risk for this report, as well. You can read more here about how the consumer is fairly weak under the hood, and how capex spending is creating a false impression that GDP is stronger than it is.

Where I disagree with Stifel is the idea that “such a build-out, after all, occurs only once” This is an antiquated opinion where perhaps the parallels between AI and electricity have gone too far, or perhaps it’s leftover from the cloud era where there were digestion periods every few years.

Portions of the AI buildout will be occurring every 1-2 years with new generations of AI systems. Therefore, AI is less of a static end point that is readily achieved – and rather it is an evolving architecture that enables ambitions to expand each year. Although cloud was also architecture-driven, it reached its end goal rather quickly in terms of driving down costs and improving productivity, allowing companies to quickly scale, and providing pay-as-you-go compute and services rather than significant up-front costs from on-premise servers. The end goal for AI is far more ambitious, as it could take a decade or more before Big Tech accomplishes commercially viable AGI (general artificial intelligence).

When listening to commentary on earnings calls, in sharp contrast to what macro analysts are saying, what we hear is that Big Tech management teams are nearly in a panic to add more capacity. This one is from AWS’ Andy Jassey: “The faster we grow, the more CapEx we end up spending because we have to procure data center and hardware and chips and networking gear ahead of when we're able to monetize it. We don't procure it unless we see significant signals of demand.”

Although the tone on capex can temporarily shift from time to time, the risk that capex will dry up from a one-time buildout is low. In many ways, the greatest risk to AI isn’t within the AI economy itself, but in broader macro conditions. We are seeing many macroeconomists attempt to forecast an AI downturn, yet having followed tech cycles for years, I’ve learned that while the macro economy waxes and wanes, technology consistently resurfaces as the best way to participate in the market — and this is especially true for AI.

For years, there’s been a debate on whether Big Tech’s AI spending will translate to revenue and profits. Meanwhile, during those years, the I/O Fund has been laser focused on where that AI capital is actually being allocated. Rather than thinking of our approach as the picks and shovels for those chasing a gold rush, we think of it as an “AI stack” strategy—investing in the lesser-known layers and components that are driving forward an ecosystem capable of massive GDP.

With that, I present my current Top 15 AI Stocks List.

#1: Nvidia is Simultaneously Shipping Two GPU Systems

Fundamentals: 10/10
Thematic: 10/10
Valuation: 4/10

Brief Overview:

When looking at YTD performance, Nvidia has returned 35% compared to SMH at 42%. Admittedly, it’s not great to underperform your industry. Peers within AI have outperformed Nvidia YTD by a wide margin, such as AMD and MU outperforming 2-3X as they’re up 93% and 135% on a YTD basis.

I was recently asked on Fox if AI chips are due for consolidation. My reply was that any dips should be bought. Although I talk a lot about Nvidia and AI, my process for covering this stock has not changed since the first day I spoke of the company. My process is that we stick close to the GPU releases rather than the earnings reports as we are dealing with the world’s best design company (fact). Therefore, revenue is a step-function of a new design being released. That may seem overly simplistic, but I can assure you, it’s worked quite well for this stock.

You can find a Case Study on Nvidia and our library of research here.library of research here.

While AI hardware players must contend with competitive forces and supply chain qualifications that can change their positioning very quickly, that is not the case with the King of Parallel Processing. Rather, Nvidia’s near-monopoly has been built carefully as each GPU release has virtually zero competitive pressure.

Generally speaking, Blackwell and Blackwell Ultra are shipping simultaneously. There are nuances to this statement, such as the GB200 NVL72 systems began shipping in volume in Q2 2025 and GB300 NVL72 began shipping this quarter and will ship in volume next quarter in Q4 2025.

I want to keep this really simple as the enormity of what Nvidia is shipping would be easy to miss. The market won’t be caught off guard like it was two years ago – we all know who the best slugger in the game is. However, there are two home runs lining up (dare I say, a grand slam) as Blackwell and Blackwell Ultra ship within 6 months of each other. In this analogy of a baseball game, Nvidia has been in the dugout for a few quarters now with the Blackwell delay. I am still in the front row of the stadium awaiting the number one slugger to return to the plate.

Overall Revenue Growth:

Nvidia reported $46.74 billion in revenue in Q2, slightly ahead of estimates for $46.13 billion. This corresponded to growth of 55.6% YoY, decelerating more than 13 points from 69.2% in Q1; on a QoQ basis, revenue increased just 6.1%, slowing from 12% in Q1.

However, its Nvidia’s guide for this upcoming quarter that solidifies the stock as our top pick in AI chips for now. The guide for $54 billion in revenue corresponds to 53.8% YoY growth and a rebound to 15.5% QoQ growth.

As you’ll see below, Broadcom is expected to report higher QoQ growth yet it’s the scale at which Nvidia is putting up these numbers that separates the company from its peers.

AI Segment Growth:

Nvidia’s data center revenue increased 56% YoY and 5% QoQ to $41.1 billion, a marginal miss versus estimates for ~$41.2 billion in the quarter. This is also the smallest sequential increase since Hopper’s breakout quarter at just ~$2 billion.

While compute declined (1%) due to timing of shipments and loss of China revenue, networking was up a whopping 46% QoQ and 78% YoY to $7.25 billion. As stated above under the AI Networking thematic section, this spells good things for what is in the pipeline.

Earnings:

Nvidia reported just a 3.9% adjusted EPS beat in Q2, reporting $1.05 in earnings versus estimates for $1.01. This corresponds to growth of 54.4% YoY, rebounding substantially from Q1’s H20-affected 32.8% growth.

Adjusted EPS growth is expected to remain strong through the rest of the fiscal year, at 47.2% and 53.2% in Q3 and Q4.

Margins:

GAAP operating margin was 60.8% in Q2, improving nearly 12 points QoQ and coming in 1.7 points ahead of guidance for 59.1%. Adjusted operating margin was 64.5%, also up nearly 12 points QoQ and 1.4 points ahead of guidance for 63.1%.

Cash:

Free cash flow was $13.45 billion, down from $26.14 billion in Q1. FCF margin was 28.8%, again down more than 30 points QoQ and more than 16 points lower YoY.

Typically, Nvidia has very strong cash flows and this is not a concern, rather is a transient quarter for cash. Operating cash flow margin and free cash flow margin have been in the 60% range in recent quarters.

Valuation:

There is not a major takeaway based on valuation.

Forward PS Ratio:

Nvidia trades at 20 forward PS and is a strong buy in the 10 forward PS range yet is a strong sell in the 30 forward PS range. We are in the middle of the clear buy/sell indicators for sales valuation.

Forward PE Ratio:

Nvidia trades at 40 forward PE ratio and is a strong buy in the 20 forward PE range yet is a strong sell in the 50 forward PE ratio.

Notable Risks:

Nvidia has far fewer risks than other stocks in this report. China tariffs can affect peers in the supply chain especially since there are hundreds of components in each AI system.

#2: Broadcom: Well-Deserved Second Place Contender

Financials: 8/10
Thematic: 10/10
Valuation: 3/10

The networking opportunity that Broadcom is positioned to capture has been evolving every quarter to where Hock Tan himself has not been able to correctly anticipate its size. Here is what Tan stated on a recent earnings call:

“In fact, the increased density in scale up is 5 to 10x more than in scale out. And that's the part that kind of pleasantly surprised us and which is why this past quarter, Q2, the AI networking portion continues at about 40% from what we reported a quarter ago for Q1. And at that time, I said I expect it to drop. It hasn't.”

This quote illustrates a few things – the strength of the networking market is surprising even to Broadcom, it helps to quantify scale-up versus scale-out in terms of networking components, and it shows that (likely) this is not priced in yet as it’s a relatively new inflection. In fiscal Q2, networking growth was 170% YoY although it’s not expressly broken down in earnings reports.

Regarding custom silicon, the chances ASICs can keep pace with Nvidia on sheer compute is low (to nearly impossible). When it comes to raw compute density combined with the software ecosystem that Nvidia offers, Big Tech’s side projects may never catch up. The rapid product road map that Nvidia offers deepens the moat the company has firmly established with universal CUDA. Meanwhile, custom silicon programs can take years to fully develop and move into production.

So then why are Big Tech companies turning to Broadcom for less flexible (yet highly optimized) AI chips with product road maps that are considerably longer than Nvidia’s? Decades ago Jeff Bezos stated “your margin is my opportunity,” referring to the fact that Amazon’s value proposition was to offer goods at a lower cost to consumers. Broadcom is similar, in that Nvidia’s margin is their opportunity to offer AI accelerators at a lower cost. The same can be true for AMD’s value proposition, as well, especially as we enter the inference stage of the AI market. Nvidia’s gross margin of 72% (and up to 78% about a year ago) is attractive to investors who seek a quality stock, yet the margin is also communicating gluttonous pricing power.

According to a recent article by VentureBeat, industry conversations and analysis suggest that “Google may be obtaining its AI compute power at roughly 20% of the cost incurred by those purchasing high-end Nvidia GPUs. While the exact numbers are internal, the implication is a 4x-6x cost efficiency advantage per unit of compute for Google at the hardware level.”

Where it becomes attractive to drive down costs is the inference market. Hundreds of millions of users interact daily with AI assistants, causing inference to become the focal point for providers such as OpenAI and Google. Meeting these levels of growing demand, without significant response delays or downtime, requires more and more accelerators, networking and interconnect products.

Broadcom’s edge goes beyond the fact that custom accelerators are often multiples cheaper than Nvidia’s GPUs for inference tasks – it's that custom silicon is increasingly performant with each generation. By optimizing algorithms (software), Big Tech can drive higher performance from large language models (LLMs) while continuing to use Nvidia’s compute power excellence for training (and also some inference tasks).

Lastly, the VMWare acquisition has been particularly fun to watch as it’s one of the best execution M&A moments recently. A few quarters back, Tan stated VMWare was the “star of the show” as it’s been reporting accelerating bookings and backlog. Here is why it’s done well post-acquisition: “This allows customers to deploy their AI models on-prem. And wherever they do business without having to compromise on privacy and data — in control of their data. And we are seeing this capability drive strong demand for VCF, from enterprises seeking to run their growing AI workloads on-prem.”

Overall Revenue Growth:

Q3’25 revenue was $15.95 billion, beating estimates for $15.82 billion, and reflecting top line growth of 22.0% YoY and 6.3% QoQ. Looking ahead, management provided Q4’25 guidance of $17.4 billion of revenue, implying 24% YoY growth and a slight uptick to 9% QoQ growth.

AI Segment Growth:

Semiconductor Solutions accelerated nine points to 26% YoY growth due to a rebound in AI accelerators (+63% YoY). Within this, AI Semiconductor revenue surged 63% YoY to $5.2B, showing re-acceleration after a slower Q2 (+46% YoY). AI now represents 57% of Semiconductor revenue and 32% of total company revenue.  

Management guided Q4 AI revenue to $6.2 billion, which would represent ~19% sequential growth and eleven consecutive quarters of YoY growth.

Earnings:

Non-GAAP EPS growth of 38% outpaced revenue growth of 22%. EBITDA margin was 67%.

Margins:

GAAP Gross Margin of 67.1%, down 90 bps QoQ from 68.0% in Q2’25, essentially flat from 66.8% in Q3’24.

GAAP operating margin of 36.9%, down 190 bps QoQ from 38.8% in Q2’25, but up significantly from 30.3% in Q3’24.

Non-GAAP operating margin of 65.5%, slightly up QoQ from 65.3% in Q2’25 and up 180 bps from 63.7% in Q3’24.

Cash:

Free Cash Flow of $7.0B represents a free cash flow margin of 44.0%, compared to 42.7% in Q2’25 and 35.6% in Q3’24.

Valuation:

Broadcom’s valuation is in unchartered territory.

Broadcom trades at a 52 forward PE ratio and has traded as low as 13 forward PE two years ago and as low as 21 forward PE in the April rout.

Broadcom trades at a 26 forward PS ratio and has traded as low as 10 forward PS in April and was at 6.5 two years ago.

Notable Risks:

Valuation is the predominant risk as Broadcom has never traded at these levels in its multi-decade listing history.

#3: AMD: The Dark Horse is Leaving the Stable

Financials: 5/10
Thematic: 10/10
Valuation: 5/10

We are finally seeing evidence that the Dark Horse is leaving the stable.

The company secured a long-term deal with OpenAI to supply 6GW of GPUs with the first GW to be delivered in H2 2026. We saw a flurry of sell-side activity with one analyst raising their price target from $185 to $310 stating the Open AI deal could generate $80 billion in chip revenue for AMD over the next few years.

As stated above under the Broadcom section, this is not a matter of AMD offering the best end-to-end performance. That will remain Nvidia for the foreseeable future. Rather, this is about driving down costs for Big Tech (and Open AI) while focusing less on raw compute power for training and more on memory and throughput for inference.

If we zoom out (as I like to do), you may recall the MI400s are expected to be the moment that AMD tightens the competition with Nvidia. The MI400 series will be the start of rack-scale systems for AMD, starting with Helios, which will connect up to 72 GPUs similar to Nvidia’s NVL72 systems.

According to AMD, Helios will “deliver up to a 10x generational performance increase for the most advanced Frontier models, and we believe it will be the highest-performance AI system in the world when it launches.” The last part is doubtful, yet the effort to close the gap with Nvidia will likely go a long way when coupled with lower pricing.

AMD stated in their last earnings report they have an ambitious goal of reaching tens of billions in MI400 sales. Investors should take note that management is specifically calling out the MI400 for this, arriving in H2 2026. The readthrough is that OpenAI is an early validator that the MI400s have serious chops, and where OpenAI goes, the rest of the AI market tends to follow.

Overall Revenue Growth:

AMD reported a slight beat on the top line at $7.685B in revenue compared to estimates of $7.43B. This represents growth of 31.6% compared to growth of 27.4% expected.

AI Segment Growth:

Last quarter, management had stated, “we expect data center segment to decrease due to the exclusion of MI308 revenue.” Therefore, it was not a surprise when data center was down (11.8%) QoQ yet was up 14% YoY for revenue of $3.24B.

Earnings:

EPS was in line with expectations at $0.48 yet was down (30%) from $0.69 in the year ago quarter. The company is expected to rebound quickly with EPS of $1.15 next quarter.

Margins:

Operating margin of (2%) for operating profits of ($134M) also included the $800M in inventory changes. The adjusted operating margin of 12% was guided correctly and was in line with expectations.

Cash:

AMD’s cash flow margins sustained well at 20% operating cash flow margin compared to 13% last quarter and 10% OCF margin last year. Free cash flow margin of 15% also expanded from a year ago at 8% margin and up from 10% FCF margin last quarter.

Valuation:

Forward PS Ratio:

AMD is trading at 13 current PS with the stock failing to hold 14 current PS two times in the past (precedes a larger selloff). The forward PS ratio of 11.7 is at the stock’s peak forward PS ratio of 12.

Forward PE Ratio:

AMD is trading at 61 forward PE ratio, the highest the stock has traded since the AI boom began in early 2023.

Notable Risks:

As the contender to the world’s most valuable company, AMD has execution risk. The company’s lead in Data Center CPUs are often at risk due to companies like Nvidia wanting to cut down costs on the instructions side of AI systems.

The valuation remains the most notable risk.

#4: Micron Quietly up 120% YTD

Financials: 8/10
Thematic: 10/10
Valuation: 7/10

Micron deserves a second look as the company is no longer tied to consumer device cycles. Instead, high bandwidth memory (HBM) had led to higher margins and multi-year supplier agreements, resulting in a leveraged approach to participate in the AI infrastructure buildout.

As pointed out in our free analysis last week, HBM is seeing a 3.5X increase in per-GPU capacity across the last three years and AI systems are commanding an increase of 34X as the number of GPUs rises and is further compounded by each GPU system requiring more HBM per package.

The B200 features 180GB of HBM3e content, more than double the H100 and a 28% increase versus the H200. In an 8-GPU server configuration, the B200 boasted 1.44TB of HBM content.
The B300 boasts 288GB of HBM3e content, a 60% increase versus the B200 and over 3.5x more than the H100. In an 8-server configuration, the B300 has 2.3TB of HBM content. This chip is beginning to ship now in Q3-Q4 2025.
Putting in context Nvidia’s rack-scale solutions, the GB200 and GB300 NVL72, shows just how rapidly HBM content is increasing. The GB200 supports up to 13.4TB of HBM content, while the GB300 supports up to 21.7TB of HBM, nearly 34X higher than the 640GB of HBM content in the 8-GPU DGX H100 servers.

The line in the sand for AI hardware companies is the margins and Micron has performed beautifully in that regard. I have to admit, when I saw their last earnings report at end of September, I had to look twice to make sure it was really Micron.

Overall Revenue Growth:

Micron reported record FQ4 revenue of $11.32 billion. Revenue growth accelerated 9.4 percentage points sequentially to 46% YoY, and on a sequential basis, growth was 21.7% QoQ, a solid 6.2-point acceleration.

AI Segment Growth:

FQ4 DRAM revenue grew by 69% YoY and 27% QoQ to $8.98 billion, a second consecutive quarter of strong sequential growth.

Earnings:

In Q4, Micron reported adjusted EPS of $3.03, up 157% YoY and beating estimates by 5.9%.

For Q1, Micron guided for adjusted EPS to be $3.75, +/- $0.15, more than 23% ahead of consensus and corresponding to YoY growth of 110%. Earnings growth is expected to reaccelerate to 155% in Q2 but then decelerate to 126% in Q3 (but still growing handsomely).

Margins:

Micron’s margin turnaround story has been impressive, with gross margin up more than 55 points over the last two years and operating margin up more than 66 points.

Adjusted gross margin in Q4 was 45.7%, up 6.7 points QoQ and 9.2 points YoY, aided by strong growth in CMBU which carried a 59% gross margin in the quarter, DRAM pricing, favorable product mix, and cost controls. For Q1, adjusted gross margin was guided to be 51.5% at midpoint, a 5.8 points sequential expansion and up by a solid 12 points YoY.

FQ4 adjusted operating margin was 35%, up 8.2 points QoQ and 12.5 points YoY, driven by operating leverage.

Cash:

FQ4 adjusted free cash flow grew by 149% YoY to $803 million or 7.1% of revenue, an improvement of 2.9 percentage points YoY. Management expects adjusted free cash flow to strengthen in FQ1 and to be significantly higher in FY2026.

Valuation:

Micron trades at an attractive valuation of 4.2 forward PS. The stock has traded as low as 2 forward PS and as high as 7 forward PS.

Micron trades at 12 forward PE ratio. The stock has traded as low as 7 yet as high as 124 due to the lumpy bottom line from the previous cyclical low in 2023 timeframe.

This goes back to the debate on if MU is a cyclical stock that deserves a lower valuation or is it emerging as a major, secular AI player. Should it be the latter, there is quite a bit of room in the valuation.

Notable Risks:

If Micron announces set pricing like they did in 2024, the stock could plateau. There are fierce competitors in the space, such as SK Hynix and Samsung. If pricing proves cyclical, the current valuation will not hold. If the pricing proves more of a secular trend, there is ample room in valuation – how the market will view the stock 2026-2027 is not clear although with technicals, some of the risk can be mitigated.

#5: TSM Report Provides 5-Quarter Runway

Financials: 5/10 (HPC declining QoQ)
Thematic: 10/10
Valuation: 4/10

TSM is typically off cycle from AI semiconductors, meaning, we will see a boom in the high-performance computing segment about 5-6 quarters before we see a boom in the AI chip market.

It would be easy to assume TSM is a quarter or two ahead of shipment times when, in fact, it’s more like three quarters when factoring in HBM and CoWoS packaging. From there, it takes an additional two quarters for system integration and assembly from companies like Dell, Foxconn, and Supermicro before the servers are shipped.

Perhaps second to capex, TSM can be used as a strong proxy for the health of the AI market as the common denominator across AI chips. The HPC segment is communicating that we have a few quarters of strong growth in the pipeline. From there, we will need to monitor how long the QoQ decline in HPC lasts as a couple of quarters is typical; anything longer would be a concern to monitor further.

On the topic of timing, the chart below helps to illustrate that even though AI is a secular trend, due to shipping cycles, TSM and even MU can still see cyclical results. When a new generation is ramping, TSM will naturally see the results first as will Micron before the systems are shipped. If we draw a similar parallel to the last QoQ decline in TSM’s shipping cycle, we can see that putting our money in the AI Chips companies makes more sense right now.

Pictured Above: When TSM’s HPC segment declined for three quarters in the past, the stock underperformed compared to a stock like Nvidia, which was reaping the benefits of the new generation finally shipping in volume (Hopper).

Overall Revenue Growth:

Q3 revenue grew by 40.8% YoY and 10.1% QoQ to $33.10 billion, beating the guidance midpoint by 2.2%. TSMC boosted the full year revenue guidance by 5 percentage points for the second consecutive quarter to mid-30% on continued strong AI demand. This is up from the 30% growth provided in Q2.

For Q4, TSMC guided revenue of $32.2 billion to $33.4 billion. At midpoint of $32.8 billion, this represents a YoY growth of 22% and down (0.9%) sequentially.

AI Segment Growth:

TSMC stated that HPC revenue was flat QoQ in NT$ in Q3, though there was more pronounced increase on a US$ basis due to FX. TSMC’s revenue is recognized in US$, so every 1% appreciation of the NT$ adversely impacts NT$ reported revenue by ~1%. Management sounded very optimistic during the Q3 earnings call about long-term AI growth opportunities.

Earnings:

The company’s Q3 EPS grew by 50.5% YoY to $2.92, beating estimates by an impressive 12.3% with the strongest beat in the last two years. Analysts expect Q4 EPS to grow 26.8% YoY to $2.84 in Q4 and grow 25.5% in Q1. Looking forward, they expect EPS to grow 19.8% YoY to $12.34 in 2026 and 24.6% YoY to $15.48 in 2027.

Margins:

Margins continue to expand due to cost controls, higher capacity utilization rates, economies of scale, and better price negotiation with customers and suppliers.

The company’s gross margins improved 170 basis points YoY and 90 basis points sequentially to 59.5%. Cost improvements, better capacity utilization, and better price negotiation with customers and suppliers primarily drove the strong margins.

Q3 operating profits grew by 50% YoY to $16.74 billion, with an operating margin of 50.6%, an improvement of 310 basis points YoY and 100 basis points sequentially, primarily driven by higher gross profits and operating leverage.

Cash:

Despite higher capex, cash was also strong with operating cash flow at 43.9% compared to 51.6% in the same period last year. Q3 free cash flows were down (16.1%) YoY to $4.8 billion or 14.6% of revenue compared to 24.4% in the same period last year. The free cash flows were down due to higher capex which grew by 51.6% YoY to $9.7 billion to support strong further growth.

Valuation:

Forward PS Ratio:

TSM is trading at 13 forward PS ratio compared to 6 at the April low and 6 at the start of the year. Regarding the current PS ratio of 17 – I cannot find a higher valuation going back 10 years.

Forward PE Ratio:

TSM is trading at 31 forward PE ratio, the highest it’s been going back to early 2023 during the AI boom. The current PE ratio of 35 is the highest its been going back to ten years except on rare exception briefly at the 2021 top.

Notable Risks:

Similar to Broadcom, the predominant risk is valuation.

AI Networking Stocks:

My number one ranked trend is AI networking. As discussed in the AI Chips section, stocks such as Nvidia and Broadcom are also the networking leaders. However, the below stocks are networking pureplays, with many on a tear since the April lows.

As you have likely noticed recently, the networking ecosystem is nuanced as recent announcements from Oracle/AMD and Nvidia/Intel have caused some networking stocks to plunge. To provide the bigger picture, I am revisiting the thesis and rankings for our networking stocks.

Tied for #1: Astera Labs: Increased ASPs from Scorpio

Financials: 10/10
Thematic: 10/10
Valuation: 4/10

When Astera is asked why they stand apart within a crowded networking market, management responds that the drive for low latency PCIe is the primary contributor to the beat/raise across both the Aries and Scorpio products.

Last March, Astera announced further collaboration with Nvidia by offering NVLink solutions for PCIe/CXL within servers (scale up): “Most recently, Astera Labs demonstrated the industry’s first end-to-end PCIe 6 interoperability with Scorpio P-Series Fabric Switches, Aries 6 Retimers and a NVIDIA Blackwell GPU at NVIDIA GTC 2025. Scorpio P-Series Fabric Switches have also been integrated with the NVIDIA MGX platform for PCIe 6-ready modular designs.”

Launched only this year, Scorpio now exceeds 10% of total revenue “making it the fastest-ramping product line in Astera Labs’ history.” Keep an eye specifically on Scorpio as a GPU-to-GPU scale-out and scale-up product line.

On the custom silicon side, it’s widely understood that Astera supplies Amazon as there were disclosures around Amazon having a warrant to buy shares in exchange for guaranteeing $650 million in orders in the SEC filing. As of mid-2025, GuruFocus confirmed Amazon still holds shares in Astera Labs.

Astera’s agile ability to compete head-on with Broadcom goes beyond only Amazon and Nvidia (though certainly, those two are enough). Management stated they had design wins with ten customers including merchant GPUs and ASICs, plus a line of sight to further sales growth from their many product lines in H2 2025 and 2026, and the upcoming UALink consortium in 2027.

It takes some time for a company like Astera to become a qualified supplier. I would need at a minimum an earnings report to state otherwise or a QoQ decline of some kind to be convinced this has changed. Instead, what I’m seeing is quite the opposite.

Revenue:

Astera Labs reported revenue of $191.9 million, beating consensus of $172.5 million for growth of 150% YoY and 20% QoQ. About eight months ago in November, analyst consensus for the June quarter was for 85% growth — thus the company has nearly doubled these expectations in less than a year.

AI Segment:

Same as revenue growth (pureplay) – up 150% YoY and 20% QoQ.

Earnings:

Adjusted EPS of $0.44 beat by 36%. Consensus is $0.39 for 69% growth. GAAP EPS was $0.29

Margins:

Astera delivered in that regard with a GAAP operating margin of 20.7% compared to 7.9% expected. This operating margin is a major win for ALAB investors as the company is now comfortably GAAP profitable despite stock-based compensation being around 20% of revenue.

Cash:

Astera’s cash from operations increased significantly with an operating cash flow margin of 70.5%, up from 38.7% last year. This totaled operating cash flow of $135.4M with $1.07B in cash on the balance sheet and no debt.

Valuation:

Astera’s valuation of 35 forward PS is in the mid-range as the company has seen as low as 11 forward PS and as high as 60 forward PS.

The stock’s forward PE ratio of 103 is steep, yet the company is recently GAAP profitable, thus it’s hard to go by this ratio.

Typically we use technicals in a situation where a hypergrowth stock is surging on revenue and has strong bottom line results, causing the valuation to send mixed signals. On one hand, stocks like this should be highly valued. On the other hand, how rich of a valuation are buyers willing to pay? Rather than get too stuck in the weeds, technicals can help us participate in the upside while protecting the downside.

Notable Risks:

Every stock has risks yet Astera less so than others on my Top 15 list. I can see a scenario where the market softens on AI valuations (temporarily) and a scenario where there are strong earnings and valuations march onward.

Tied for #1 Credo: Active Electric Cables (AECs) for Miles

Financials: 10/10
Thematic: 10/10
Valuation: 4/10

The saying “I can see for miles” implies visibility into the future. The saying makes me think of Credo as there is over two miles of copper cabling for each NVL72 system. We can literally see Credo’s AECs for miles, and figuratively, there is more visibility than usual for this particular stock given the inflection of 274% YoY and 31% QoQ growth last quarter helps to confirm its positioning in Nvidia’s Blackwell systems.

Credo’s new 800G HiWire ZeroFlap AECs are designed to reach 7 meters with full host-to-switch connectivity, and are especially designed for liquid cooled servers. The over 7 meter distance helps to enable large AI clusters sized into hundreds of thousands of GPUs.

Credo competes with 800G OSFPs AOCs, yet these are particularly troublesome due to physical constraints that cause the connectors to break. There is also link lapse with AOCs, which are “momentary disruptions in network links.” Credo’s AECs aim to solve these issues, and the results speak for themselves.

For distances between two meters and seven meters (or about six to 24 feet), active electric cables (AECs) are also seeing heightened demand as servers scale up to eight GPUs to now 36 GPU to 72 GPU per rack-scale AI system.

In a nutshell, this is why Credo is reporting surging growth in a highly competitive market: “Reliability and power efficiency [leads] to choosing AECs over optical solutions as they are up to 1,000x more reliable and consume half the power. AECs virtually eliminate link fabs, which are intermittent losses of connection, boosting cluster reliability and productivity while reducing power consumption.”

Regarding “consume half the power” … Credo’s proprietary serializer/deserialzer (Ser/Des) technology, active electric cables and digital signal processing (DSPs) give the company a significant competitive advantage as it enables power-efficient connectivity that is reasonably priced.

Revenue:

The company reported growth of 274% YoY and 31% QoQ for revenue of $223.1 million. This beat estimates on the top line by 17% with management raising full-year revenue growth outlook by 35 points, from 85% YoY to 120% YoY.

AI Segment:

Product Revenue came in at $217.1 million, up 279% YoY and 31% QoQ.

Earnings:

The bottom line also shined with adjusted EPS beating estimates by 44.4%. This represents growth of 1,200% YoY from a thin $0.04 in the prior-year quarter. Triple-digit growth of 425% on the bottom line is expected to follow although flat QoQ.

Margins:

GAAP Operating Margin was 27.2%, up from 19.9% in the last quarter and up from (24.2%) in prior-year quarter.

Adjusted Operating Margin was 43.1%, up from 36.8% last quarter and up from 3.7% in prior-year quarter.

This is the standout – massive operating leverage as opex grew only ~11% QoQ vs. the 31% pick up in revenue.

Cash:

FCF Margin of 23.8%, down from 31.9% last quarter but up more than 45 points from (21.9%) in the prior-year quarter. Debt free.

Valuation:

The forward PS ratio is 24 and on the higher range of where Credo trades with the upper region being 33 earlier this year yet has traded as low as 8 at the April low.

Credo trades at a 65 forward PE Ratio yet similar to Astera Labs, this is hard to put much weight into as the company is newly profitable.

Notable Risks:

Every stock has risks yet Credo less so than others on my Top 15 list. I can see a scenario where the market softens on AI valuations (temporarily) and a scenario where there are strong earnings and valuations march onward.

#3: Small Cap Networking Stock with Strong QoQ 400G Growth and Incoming 800G/1.6T Growth

This past quarter, the I/O Fund was on the hunt for networking stocks that reported an inflection. Given Nvidia is reporting 46% QoQ growth at scale on their networking segment, we figured there would be some breadcrumbs to follow in the supply chain as to companies that are beneficiaries of the incoming AI networking boom.

The stock we identified for our Discovery members reported 40% QoQ growth last quarter and is forecasting 17% QoQ growth in the upcoming quarter – some of the highest we’ve seen in the supply chain landscape. Management discussed the ability to grow capacity 8.5X this year before doubling this by mid-2026.

To learn more, sign up for our Discovery tier here.

#4 Lumentum: EML Lasers in High Demand

Financials: 6/10 (not a pureplay)
Thematic: 7/10
Valuation: 7/10

Lumentum has been on our radar for more than one year, as the company supplies components for datacom transceivers and optical interconnects with tech that has caught the attention of heavyweight Nvidia. We’ve been closely monitoring Lumentum and waiting patiently for their EML lasers for 200G to ship, enabling 800G and 1.6T bandwidths.

As discussed in the past, optical interconnects help data centers accelerate data throughput between data centers and inside the data center between servers or racks, while reducing latency and power consumption. AI is driving cloud demand higher from the hyperscalers, leading to more data being created and processed, thus helping drive a need for these interconnects to meet demand for high-speed, low power data transmission in data centers.

Specifically, Q4’s report provided confirmation of the EML laser ramp, as EMLs achieved an all-time high for shipments with revenue more than doubling versus its June 2024 baseline. Management also cited a “substantial” 200G EML order to be fulfilled in the December quarter, although offered little additional clarity on the size of the order.

Revenue:

Lumentum reported Q4 revenue of $480.7 million, beating analyst estimates by a modest 2.29%. This was a notable uptick on the top-line, with growth of 13.1% QoQ, accelerating 7 points, and 55.9% YoY, accelerating 42 points.

AI Segment:

Cloud & Networking Q4 revenue came in at $424.1 million, representing 66.5% YoY growth. Additionally, the segment’s QoQ growth of 16.1% accelerated sharply from 7.6% QoQ in Q3, coming in much stronger than Coherent, where growth decelerated from 10% QoQ to 5%.

Earnings:

Lumentum reported adjusted EPS of $0.88 in Q4, beating estimates of $0.81 and improving against the $0.57 reported in Q3 and $0.06 reported in the year ago quarter.

Q4’s adjusted net income margin of 13.1% reflects continued operational improvements and the fourth consecutive quarter of sequential improvement (from 9.6% in Q3, 7.5% in Q2, and 3.6% in Q1).

Margins:

Q4’s GAAP operating loss of ($8.4 million) represents a (1.7%) operating margin, compared to (8.9%) in Q3 FY25 and (43.3%) in Q4 FY24.

Non-GAAP operating margin of 15.0% expanded nicely compared to prior quarter of 10.8% and prior year quarter of (5.1%).

Cash:

For FY25, operating cash flow was up ~5x to $126.4 million, for a 7.7% margin, improving from a 1.8% margin in FY24.

Valuation:

Lumentum’s Forward PS ratio is above what it typically trades at 5 forward PS. It’s previous top this year was 4 forward PS and it failed to hold that valuation twice.

The company’s forward PE Ratio is 33 and is within a reasonable range as the company has traded as high as 50-60 and as low as 18 over the past 12 months.

Notable Risks:

Lumentum has many competitors and its supplier agreements are not as clear to our firm as Credo and Astera Labs. However, the fundamentals are communicating that Lumentum’s management commentary is reliable, which is that their EML lasers are in high demand.

AI Software and AI Data Layer

As it stands today, there are a handful of AI software companies and AI data layer companies that have set themselves apart in fundamental strength. As the introduction pointed out, the noise in stock investing is often quite loud and the rate at which stock tickers are exuberantly discussed is detached from reality. We do a fairly comprehensive scan and find the list of software stocks that offer concrete proof of participating in the AI trend is far fewer than one would originally imagine.

I’ve stated below that AI hardware companies will also be some of the best AI software companies (incoming tangent here):

To illustrate this, Broadcom is preparing to displace a few of the FAANGs at a $1.6T valuation compared to Meta at $1.8T valuation and Amazon at $2.3T valuation. This is on the cusp of Broadcom stating their serviceable addressable market will be $60B to $90B in revenue by fiscal 2027, which is in two years from today as their fiscal year ends in October (roughly 200% at the midpoint given the current $25B run rate).

One has to wonder, why do the AI software juggernauts not discuss their revenue as openly as the AI hardware companies, especially given software tends to be recurring and easier to model? On the other end of the spectrum, we see up to 100X forward sales valuations in this category.

Yet, if we look at Nvidia AI systems as an example, it’s easy to see that software is what will accelerate AI over the next few years. There are four layers to Nvidia’s full-stack accelerated computing: hardware, system software, platform software, and applications. When you consider Blackwell, for example, there are transformer engine libraries, integrated with CUDA and cuDNN that determine when to use FP8 versus FP4 during training or inference to maximize speed yet also maintain accuracy. Software determines which precision to use for every layer and every tensor, which helps to deliver a 2X to 4X improvement in training and inference. There are additional revenue segments, such as automotive and robotics, where Nvidia will be able to license its software and gradually add this high-margin revenue to its already profound stock market performance.

If you look below, you’ll also notice that I’ve put Oracle in the software/data layer category for two quarters now. Although it's Oracle Cloud Infrastructure (OCI) driving growth of 55% and expected to accelerate to 77%+ growth and also strong RPO of 359%, it’s the software and data layer that separates Oracle from other cloud infrastructure providers. For example, software-defined remote direct memory access (RDMA) helps to lower latency and increase bandwidth by bypassing the CPU during training and inference tasks. Oracle says it “consistently charges less than Amazon Web Services (AWS) for the equivalent compute capacity.” But we have to look closely at why that is.

Vectorized data is another area where Oracle sets itself apart using the data layer as it allows both structured and unstructured data to be understood by AI models, which helps to increase the use of private data alongside public data.

As we approach the AI software/AI data list now and into the future, the following should be kept in mind:

Flexibility in what defines an AI software winner (wait until you see my #2 below)
It can’t rank until we see real, tangible evidence of a stock participating in the AI trend. Why pre-emptively invest in a company that is not reporting strong AI revenue when there are so many choices on the market? (Looking at you Tesla Optimus fans).

I believe the stocks listed below fit this criteria.

#1: Reddit is an AI Data Layer Frontrunner

Financials: 10/10
Thematic: 7/10
Valuation: 4/10

If you had asked me a few years back to describe Reddit’s value proposition, descriptions like “front page of the internet,” “world’s largest forum,” “best place to query the crowd” may have come to mind. Yet, there is something far more valuable that Reddit provides in the AI era, which is a continuous supply of human-generated conversations. To some extent, Reddit is transforming into a human data farm for AI models as it provides continuous, conversational data. What was once a forum is now a wealth of opinions and loads of sentiment that AI models desperately need to produce more natural and sentient-sounding responses.

Therefore, Reddit ranks higher than you might originally guess going into an AI software discussion. The reason for the high-ranking is that Reddit’s forum-based, real-world discussions are at the top of the list of data sets that can help advance AI models. Therefore, this is less about forum users and more about the licensing of data (and what Reddit gets in exchange).

Google clearly agrees as the company is licensing data from Reddit, and what’s interesting about this partnership is that it’s easy to see Google lacks highly contextual, human sentiment type data that social platforms provide. Meta, for example, has something similar to Reddit – whereas Google does not have this social aspect from search. In exchange, Google is boosting Reddit in search results.

Although the world’s leading forum site has only 416 million weekly active users compared to Facebook’s 2 billion, it ranks fifth behind Facebook as the most visited site in the United States. In addition, due to a few changes in how Google surfaces content with AI overviews, Reddit is now the second most visible site in the United States – ranking above Facebook for example – and the top line results show the company is reaping the rewards of being in the search giant’s good favor.

Over the last two years, Reddit has seen an explosion in SEO visibility on Google, with data from Sistrix placing growth from July 2023 to April 2024 at a whopping 1,328%. This moved Reddit from 85th most visible site to the 7th most visible.

Now, as of October 2025, Reddit has moved to the 3rd most visible site in the US, per Sistrix, behind Wikipedia and YouTube, and ahead of popular sites such as Facebook in 7th and Amazon in 4th. This major improvement in SEO ranking may be a potential contributor to Reddit’s accelerating growth over the past five quarters – yet as stated, the surge in growth is out of Reddit’s control and relies on Google SEO placement, which could change at anytime.

In terms of user engagement, Reddit notched 3.8 billion visits as of September 2025, according to data from Similarweb, compared to 11.4 billion for Facebook, 6.5 billion for Instagram, and 4.3 billion for X. Users visited an average of 4.77 pages per visit with an average visit duration of nearly 6 minutes, compared to 12.18 pages per visit and an average duration of 10 minutes for Facebook. Similarweb places Reddit as the fifth-most visited site in the US, behind Facebook in fourth place.

This rise in search ranking has created a fundamentals profile that is hard to ignore.

Revenue:

Reddit delivered a rather impressive Q2 on July 31st with revenue beating estimates by more than 17%.

Q2 marked Reddit’s fastest growth since the start of 2022, and a significant improvement over the past two years from just 12% growth at the start of 2023. What’s even more impressive is that Reddit delivered this 77.7% growth on top of a rather difficult 53.6% comp, yet this may shape up to be the peak growth quarter for the year as comps get tougher.

AI Segment:

Behind the substantial revenue beat in Q2 was 84% growth in advertising revenue to $465 million. This marked a sharp 23 point acceleration from 61% growth in Q1. Sequentially, advertising revenue grew almost 30%, with growth of more $106 million QoQ, outpacing Q4 2024’s $79 million sequential increase.

There was 50% YoY growth in active advertisers as it continued to acquire new advertisers. Additionally, performance ads and brand ads both increased more than 80% YoY, reflecting strong engagement from advertisers on the platform.

This past quarter marked the highest sequential growth in ARPU in more than three years at 25%, outpacing even Q4 24’s 18% growth. Management believes global ARPU is “still low on an absolute basis and remains an opportunity” for long-term improvement – for example, Meta’s global ARPU is around 3x of Reddit’s at $13.65 as of Q2, and though Meta hasn’t updated regional metrics since the end of 2023, it’s possible that US ARPU is 10x that of Reddit’s.

Earnings:

Over the past month, consensus EPS estimates through Q4 2026, or the next six quarters, have been revised 23% to 66% higher; over the past six months, estimates have moved 20% to 57% higher, as margins strengthen. For example, Q2 2026 has seen its estimate move from $0.42 to $0.70 over the past month, and Q3 2026 from $0.55 to $0.83. This now projects three consecutive quarters of triple-digit YoY growth followed by three consecutive quarters of >50% growth.

Margins:

Gross margin was 90.8% in Q2, up 1.3 points YoY and marginally higher QoQ.

Operating margin was 13.6%, up nearly 25 points YoY and 12.6 points QoQ. Notably, this also exceeded Q4 2024’s operating margin of 12.4%.

Cash:

Operating cash flow was $111.3 million in Q2, up 292% YoY. OCF margin was 22.3%, down 10 points QoQ but up more than 12 points YoY. Free cash flow and operating cash flow are correlated nearly 1:1. Free cash flow was $110.8 million in Q2 for a 22.2% margin.

Valuation:

Reddit has some room at 19 forward PS but not a ton of room before it will test its previous top at 24. After about a 25% move from here, Reddit will be testing a level it has not held two times in the past year. The stock has traded as low as 8.3.

The bottom line valuation is harder to identify a trend as the company was not GAAP profitable when it went public, although is firmly GAAP profitable now. The stock trades at 52 forward PE yet has traded as high as 70 forward PE and as low as 25 in recent quarters.

Risks:

Reddit’s primary risk is the surge in traffic relies on a third-party relationship with Google that could be terminated at anytime. It may not be terminated given the emphasis on contextual data for models, yet the recent success hinges on this data licensing deal.

#2: CoreWeave: Beating the Big 3 on Utilization Rates

Financials: 1/10
Thematic: 11/10 (higher than our highest rank)
Valuation: 3/10

CoreWeave is perhaps the first stock in the history of the market to have short sellers before it was a public listing. While it’s risky and novel to collaterize GPUs, we want to remain open-minded as CoreWeave’s software-defined infrastructure is one of the most advanced in the industry for AI workloads.

Please note, CoreWeave carries outsized risk as there is high debt leverage, negative free cash flow and is not profitable. The stock’s thematic ranking is quite high, yet we would only approach this stock using technicals for risk management.

The company’s software stack is specifically designed to maximize GPU utilization, elasticity, and cost efficiency to the point of booking out GPUs like it’s a leading hyperscaler. Remarkably, it’s the first company in almost twenty years to meaningfully disrupt the dominance of the Big Three in cloud infrastructure.

By focusing only on GPUs and software optimizations, CoreWeave offers bare metal servers at a cost that is up to 20% to 50% cheaper than hyperscalers. Its value proposition is best summarized in its utilization rates for GPUs. CoreWeave has published its MFU rate of 35% to 45%, stating it is 20% higher than competitors, which means other AI data centers have MFU rates more in the 30% range. Due to FLOPs performing an astronomical number of calculations, small percentages translate to an important advantage.

The company is able to scale quickly with new GPUs due to the Mission Control automation layer that provides automated deployments of systems like the GB300 NVL72s. The company stated: “Mission Control continues to be the cornerstone of CoreWeave's ability to scale at breakneck speed, building a fully automated and rigorous process for cluster life cycle management with unmatched visibility for our customers.”

CoreWeave also offers a Virtual Private Cloud for a private network space. By combining an isolated virtual private cloud with Nvidia’s Quantum InfiniBand, customers get ultra-low latency with enhanced security.

The company's Kubernetes Service is an AI-optimized Kubernetes environment for scheduling AI workloads and scaling up/down for the right mix of CPU, GPU, memory and storage (known as elasticity). SUNK, known as Slurm on Kubernetes, combines container orchestration with a job scheduler to manage large batch jobs. AI labs use this service to combine scheduling for high performance computing with a cloud-native environment.

Local Object Transport Accelerator (LOTA) for AI object storage is another feature that is optimized for AI workloads by focusing on performance and cost efficiency. The company recently added archive tier object storage, which allows data to move between hot and cold storage based on access patterns, which optimizes costs. In the recent earnings call, the company stated they are seeing customers “shifting petabytes of their core storage to CoreWeave in the form of multiyear contracts.”

CoreWeave recently completed its acquisition of Weights & Biases in May to add observability, which means engineers can quickly diagnose a failure or inefficiency in the software layer and infrastructure layer. For example, if a model is training slowly, the observability platform will help an AI engineer identify and resolve this quickly.

More recently, CoreWeave integrated W&B for a joint launch of its Inference-as-a-service feature, which allows developers to use APIs to tap into AI models from OpenAI, Meta, DeepSeek, etcetera. Inference is key for CoreWeave to fully monetize its investments in capex-heavy infrastructure. For example, these popular LLMs combined with chain of reasoning inference, which means generating step-by-step reasoning, will become compute-intensive especially at scale. This will lead to CoreWeave monetizing every chatbot response, API calls and applications to easily payback their initial investments plus some (in time).

The paragraph above is quite important and worth summarizing – essentially, CoreWeave’s path to monetization will become clearer as the inference market takes off in the coming quarters/years. What you see is not what you get, rather what you see could surge should CoreWeave execute well – and find financing.

This stock comes with outsized risk. Please note the cash/debt section below. Despite being in the Pro tier’s Top 15 due to a strong thematic, this is one we will hold only with close risk management.

Revenue:

CoreWeave reached a new milestone of over $1.0 billion in revenue in Q2 2025, growing 206.7% YoY to $1.21 billion. On a sequential basis, the Q2 revenue grew by 23.6%. The company beat analyst consensus estimates by 12.2%, driven by strong demand for the company’s AI cloud infrastructure services.

Looking forward, revenue is expected to grow by 174% YoY to $5.26 billion in the year 2025 and 129.6% YoY to $12.08 billion in 2026 and 48.3% growth in 2027. Most importantly, management has increased the full-year revenue guidance for the second quarter in a row due to the strong customer demand. Management increased guidance by $250 million at the midpoint to a new range of $5.15 billion to $5.35 billion for the year 2025.

AI Segment:

The company’s backlog was $30.1 billion at the end of Q2, up 86% YoY driven by the company’s strategic deal with OpenAI in March 2025 and the signing of subsequent expansion deals with the company.

The company derived 77% of 2024 revenue from its two largest customers, i.e., Microsoft and Nvidia. While in the recent quarter, Microsoft accounted for 71% of the total revenue. Goldman Sachs estimates that Microsoft’s share is expected to drop to 38% in 2026, followed by OpenAI at 21%, Nvidia at 6%, and the remaining 35% to be attributed to other customers.

Earnings:

The company reported GAAP loss per share of (-$0.60) in Q2 compared to the analyst consensus estimate of (-$0.49), missing estimates by –21.7% due to the higher operating expenses, particularly the technology and infrastructure expenses.

Analysts expect GAAP loss per share of (-$2.67) for this year, followed by (-$0.90) for 2026. They expect a positive GAAP EPS of $1.59 in 2027.

Margins:

Q2 gross margin was 74%, up 200 basis points YoY and up 100 basis points QoQ. The company is investing heavily in data center and server infrastructure to meet very strong AI demand from its customers. The operating margin was 2%, compared to 20% in the same period last year and (3%) in Q1. Operating expenses increased by 276% YoY, driven by high technology and infrastructure expenses. The management tried to explain in the Q2 earnings call that expenses are front-loaded and have a short-term impact on the margins.

Cash:

CoreWeave’s business model is based on aggressive capacity expansion, currently fueled primarily by debt. As a result, cash is rather thin and gets spent quickly, and free cash flow is widely negative.

CoreWeave reported $1.15 billion in cash and equivalents (excluding $0.56 billion in restricted cash and equivalents), though CoreWeave updated in an 8-K related to its now upsized $1.75 billion raise that total cash will be closer to $5 billion.

Operating cash flow was ($251.3 million) for a (21%) margin in Q2, widening from ($117.8 million) in the year ago quarter. Free cash flow was ($2.7 billion) for a (223%) margin, widening slightly from ($2.36 billion) in the year ago quarter.

Debt was reported at $11.05 billion in Q2, with $3.62 billion being current. Current debt is likely closer to $12 billion now, with a majority (~$6.7 billion) tied to its two existing delayed draw term loan facilities; if the new DDTL is drawn upon, debt could rise to $14.6 billion. On the other hand, the company is trying to reduce its cost of capital by raising cash through secured debt, using its highly valuable GPUs as collateral, which is positive.

As discussed above, capex for the second half of the year is expected to be >$15 billion, with cash on hand only covering one-third of that at maximum. This will place the emphasis on finding alternative funding to finance this spending.

Valuation:

CoreWeave’s valuation of 12.4 forward PS is at the higher range for where the stock has traded this year. The stock traded as high as 15 forward PS and as low as 3.4 during April.

The company is not profitable for a bottom line valuation and is the only stock on our list that is not profitable.

Risks:

Cash/Debt is a very high risk with debt at $12 billion and growing with only $1.15 billion in cash and negative free cash flow.

#3: Oracle Inflecting with 8% QoQ Growth, RPO of 359% Soars and The Future is Bright

Financials: 7/10 (other segments weigh on AI segment)
Thematic: 7/10 (not a pureplay)
Valuation: 2/10

As stated in the intro, even though bare metal servers are a large part of the story for both CoreWeave and Oracle, it’s also the software-defined optimizations that set these cloud infrastructure players apart from the Big 3. For Oracle, it’s also RDMA, which is a networking fabric that increases performance and density, plus the data layer (of course) as Oracle is able to leverage its deep roots in relational databases. Inference will need a mix of private data sets to augment public data sets to fine-tune reasoning tasks in an effective way for enterprises to use the models internally, and Oracle is positioned to capture this opportunity.

Oracle offers the widest range of bare metal GPU instances among major cloud providers, and scalability at any size up to 65,536 Hopper GPU clusters and 131,072 B200 GPU clusters, which are expected to come online in 2025. Oracle also offers very flexible VM instances, letting customers pay for only the capacity they need as they need it for any size workload, rather than offering fixed instance sizes.

With less overhead and fewer CPU cycles, RDMA helps Oracle offer its AI clusters at a lower cost: Oracle says it “consistently charges less than Amazon Web Services (AWS) for the equivalent compute capacity.”

Oracle says that it can offer less than 10 microseconds of latency between nodes, improving efficiency. In the most recent earnings call, Oracle emphasized how cheap they are compared to the Big 3, stating: “We have gotten the entire Oracle Cloud, the whole thing, every feature, every function of the Oracle Cloud down to something we can put into a handful of racks, 3 racks, we call it Butterfly that costs $6 million. So we can give you a private version of the Oracle Cloud with every feature, every security feature, every function, everything we do for $6 million. I think the cost for the other hyperscalers is more than 100x that.”

Oracle’s AI vector capabilities also stand out given Oracle’s database roots, offering native AI vector search capabilities with seamless integration to leading AI models from OpenAI, xAI, Meta, Cohere and more. AI vector search lets enterprises search both structured and unstructured data in a variety of manners, enabling intelligent, relevant and accurate AI responses utilizing their data.

The announcement of Oracle’s AI database is particularly interesting in terms of ways the stock can extend its run. As explained in the earnings call, the combination of vectorizing data to where it can be understood by AI models with the ability to connect private databases to AI reasoning models will result in enterprises unlocking higher value from AI.

Oracle is teasing a more beefed-up AI database, which management stated will officially launch at Oracle World Cloud, describing a combination of private enterprise data, large reasoning models and automated agents: “Who's offering that to customers? We'll be the first when we deliver it and demonstrate it at AI World next month.”

Oracle has already made major headway with AI embedded databases with 23ai, which converts vector data into contextual information. By connecting a database to Chat-GPT, there is more reasoning layered into the results.

The inference market will define by size and quality of data for reasoning purposes, and Oracle sits on arguably the world’s largest enterprise data sets. Although we have grown used to compute driving the AI training market, there will be an important shift toward the data layer driving the inference market.

With Oracle embedding the AI database, inference will happen inside the database where the data resides. This is distinct from pulling data out of the database into the large language model, which is inefficient. Oracle’s move to embed the database supports a sustained, upward trajectory in the stock price.

Revenue:

Oracle delivered Q1 revenue of $14.9 billion, growing 12% YoY but slipping 6% sequentially, coming in just shy of the Street’s $15.0 billion estimate.

AI Segment:

Remaining performance obligations (RPO) grew 359% YoY with cloud RPO growing “nearly 500%” on top of 83% growth last year. This compares to RPO growth of 41% YoY last quarter and cloud RPO growth of 83% last year.

Oracle Cloud Infrastructure (OCI) was forecast to “grow 77% to $18 billion this fiscal year and then increase to $32 billion, $73 billion, $114 billion and $144 billion over the following 4 years.”

You can think of this as an acceleration from roughly 50% growth on IaaS in recent quarters to up to 128% growth in future years, specifically from the $32B to $73B in the medium-term of two years out.

OCI (IaaS) revenue grew 55% YoY to $3.3 billion, faster than hyperscaler peers.

This led to multi-cloud database revenue with Amazon, Google, and Microsoft surging 1,529% YoY.

Earnings:

GAAP EPS of $1.01, down (15%) QoQ from $1.19 in Q4’25 and flat YoY vs. $1.03 in Q1’FY25. This figure was also lower than the analyst estimates of $1.04.

Non-GAAP EPS of $1.37, up 6% YoY from $1.39 in Q1’25 but down (14%) QoQ from $1.70 in Q4’25.

Margins:

Q1 figures represent a 29% operating margin, down from 32% in the prior quarter and 30% in the prior year quarter.

Cash:

(39%) FCF and 55% OCF. Highly leveraged cash to debt ratio

Valuation:

Oracle’s valuation is at the top range of where the stock has traded this year at 12 forward PS. The stock briefly touched 13 before selling off, and otherwise, has not traded higher than 12 this year (or for decades really, but is transforming into an AI stock)

The forward PE Ratio of 42 is the highest it’s ever traded this year or in previous years.

Risks:

Highly leveraged cash to debt ratio is the predominant risk.

#4: AppLovin Has the Best Operating Margins Sector-Wide

Financials: 10/10
Thematic: 7/10
Valuation: 3/10

APP has many aspects to focus on for the bull story, yet the margins are truly one-of-a-kind. It is hard to take the title of “most impressive margins” in a software category as AppLovin is up against the most operationally efficient, cash loaded companies worldwide.

Regarding its segments, management has repeatedly stated that gaming ads alone can sustain growth of 20% to 30% YoY. Therefore, the catalyst for the next few years is securing additional supply, such as e-commerce, as well as opening up the AXON ad platform to more advertisers.

The AXON ads manager recently became self-service, which means it can scale at levels not previously seen by offering self-service interface for AppLovin’s 1 billion reach. As of now, AppLovin is limited in the number of advertisers it can manually onboard. According to the opening remarks: “With the rollout going smoothly, we are ready to widen access. On October 1, 2025, we plan to open the AXON ads manager on a referral basis, perfectly timed for the holiday season. Feedback from these partners will guide our global public launch in the first half of 2026. To date, web advertising campaigns have been limited to the United States. On October 1, we plan to open our platform to most major international markets.”

Management also hinted these improvements will lead to “a lot of upside in the numbers we’re able to report.”

Here is the full quote:

“We expect that will increase the advertiser count quite quickly and also allow us to go through live examples of advertisers coming in self-service all the way to scale on our product. Assuming all that goes well, then we talked about opening up the platform entirely to the world in first half of next year. We think as advertiser count grows on our business, especially in categories outside of gaming, you're going to see a lot of upside in the numbers that we're able to report”.

The last earnings report was stellar with all fundamental boxes ticked, a team that has proven to execute, and incoming catalysts that are quite well-timed to where we maybe have two quarters (or less) to wait for an inflection.

And check out those margins!

Revenue:

AppLovin reported revenue of $1.26 billion compared to consensus of $1.28 billion according to some sources yet others reflect the consensus we had of $1.22 billion, thereby it’s debatable if the top line beat. Overall revenue last quarter was $1.48B versus this quarter at $1.26B. As we covered in the past, this is due to AppLovin divesting its mobile gaming “Apps” business, with the sale completed on June 30th. Therefore, if you adjust for this sale, revenue for the ads business in Q1 was $1.15B for QoQ growth of 8.7%.

AI Segment:

Same as revenue (AXON ad engine is powered by AI).

Earnings:

On the bottom line, the company had a large beat with EPS of $2.39 compared to $1.99 EPS expected, representing growth of 169%. This was a 45 point beat on growth rate for the bottom line. Adjusted EBITDA doubled to $1.02 billion, up from $943 million last quarter. This represents an adjusted EBITDA margin of 81%.

Margins:

Operating margin of 76% expanded from 44.7% last quarter and more than doubled from the year ago quarter at 36.2%. Wow!

Cash:

As management alluded to on the earnings call, the company “prints cash” with a 61.3% operating cash flow margin and a 61% free cash flow margin.

Valuation:

The company is trading at a PS ratio of 40.3 and a forward PS ratio of 37.6. The company’s forward PS ratio peaked at 46.7 on September 30 and is currently trading about 20% below its peak. While the forward PS ratio above 30 is considered high, the market is giving the company a premium valuation due to a remarkable turnaround in margins.

Another key catalyst is that the company completed the divestment of its low margin mobile gaming business in Q2 2025. The company’s adjusted EBITDA margin has swiftly moved higher from 68% in Q1 to 80.9% in the recent quarter. It would also make more sense to look at the EV/EBITDA ratio for AppLovin. It currently trades at an EV/EBITDA ratio of 63.4 and a forward EV/EBITDA ratio of 49.1. The company has traded at a peak EV/EBITDA ratio of 110 during June 2021 and around 88 during the tech market bubble in November 2021. With profitability improving post-divestiture, there could be further room for valuation expansion.

Risks:

APP is the subject of short reports and has a business model the SEC, short sellers and others find suspicious. However, we think the management team, AI-powered ads business model and strong market presence is worth a shot especially when using technicals alongside any entries or exits.

#5: Cloudflare is Locked and Loaded for AI Inference Market

The Workers Platform, known as Act 3, is positioned to take advantage of the massive inference trend. The I/O Fund team recently dug up a stat that inference is expected to account for 60% to 70% of AI workloads by 2030. In particular, Cloudflare emphasizes their position is what will help the company win this market: “The fact that we sit in front of so much of the web and that more than half of our dynamic traffic is already between APIs means that we are strategically positioned to deliver the agentic web of the future.”

Revenue:

Cloudflare reported its largest revenue beat in the last six quarters at 2.1% above consensus, with Q2 revenue up 27.8% YoY to $512.3 million. This also marked a slight 1.3 point acceleration on the top-line from 26.5% growth in Q1.

For Q3, Cloudflare guided for revenue of $543.5 to $544.5 million, ahead of estimates at the time for $538.9 million. This corresponds to a slight deceleration to the mid-to-high 26% YoY growth range, where Cloudflare is expected to remain through Q4. This provides no clear indication yet that the company is able to drive a sustained revenue acceleration aided by AI.

Current RPO accounted for 66% of total RPO, or ~$1.30 billion, increasing 33% YoY in Q2, a four point acceleration from 29% growth in Q1. This is also a notable uplift from 26% growth in the year ago quarter.

AI Segment:

There is no official AI segment yet.

Earnings:

Cloudflare topped estimates in Q2 driven by the revenue beat and stronger adjusted margins, and boosted its FY25 adjusted EPS outlook as a result.

GAAP EPS was ($0.15), missing estimates for ($0.08) as GAAP margins drifted lower.

Adjusted EPS was $0.21, beating estimates for $0.18, fueled the outperformance in adjusted operating margin in the quarter.

Margins:

GAAP gross margin was 74.9% in Q2, down nearly 3 points YoY and 1 point QoQ. Adjusted gross margin was 76.3%, down 2.7 points YoY and 0.8 points QoQ.

GAAP operating margin was (13.1%), down 4.4 points YoY and 2 points QoQ. Adjusted operating margin was 14.1%, approximately flat YoY and up 2.4 points QoQ; this was also ahead of guidance for 12.6%.

For Q3, Cloudflare guided for adjusted operating income of $75-76 million, pointing to adjusted operating margin of 13.9%, down nearly 1 point YoY and moderating slightly QoQ.

Cash:

Operating cash flow was $99.8 million for a 19% margin, flat YoY but down from a 30% margin in Q1.

Free cash flow was $33.3 million for a 6% margin, down 4 points YoY and 5 points QoQ.

Network capex was 11% of revenue in Q2, down from 17% of revenue in Q2. Cloudflare stuck to its guidance for network capex to be 12-13% of revenue for the year, suggesting slight moderation in 2H.

Valuation:

Cloudflare is officially trading at its highest forward since the tech bubble popped in late 2021-early 2022. The current PS of 40 and forward PS of 36 does not offer much support in terms of the stock holding well at these levels.

Cloudflare is trading at a wild forward PE ratio of 255, which is far above any forward PE ratio over the past year (the previous highest forward earnings ratio was 205 where it sharply reversed twice).

Risks:

Valuation is the predominant risk coupled with little evidence of real AI revenue right now (more of a future winner that we want a placeholder for).

AI Energy

#1: Right Place, Right Time for Bloom Energy

Bloom Energy provides on-site 24/7 power generation using their proprietary solid oxide fuel cells (SOFCs). The SOFCs are stacked up by the hundreds to thousands in Bloom Energy Servers (BES), which enable the conversion of fuels like natural gas, biogas and hydrogen to electricity.

Bloom Energy is securing data center deals due to fast deployment of about three months. Here is what management described as the competitive advantages regarding time to power for fuel cells: “A big shift in our business today is time to power. We are providing solutions to meet the urgent needs of our customers who cannot fulfill their power needs from the grid. In these cases, we rapidly book, build, ship, install and power sites for our customers in a matter of months, a much faster timeline than a grid connection. Such rapid drill activities will necessarily come with timeline variances, both pull-ins and delays, and will affect our quarterly revenue line. You are seeing this in our Q3 numbers.”

Although we expect Bloom to be a very volatile stock, the fact is that very few alternative energy companies can move as quickly as BE in what our firm has dubbed an energy crisis in getting power to data centers.

As the CEO stated on the call, to wait 5-7 years is “untenable.” To compare, Bloom will power Oracle with on-site power solutions in as soon as 90 days. Additional key customers for BE include American Electric Power (AEP), Quanta and Equinix. Notably, Amazon and Cologix are customers of Bloom through AEP in Ohio.

Perhaps the most important statement on the earnings call was when the CEO stated: “We expect new orders from other AI hardware ecosystem players soon, complementing demand we see from our more traditional commercial and industrial customers.”

Revenue:

Bloom reported a nearly 6% beat to estimates in Q2, reporting $401.2 million in revenue versus estimates for $378.9 million. Revenue grew 19.5% YoY, slowing from 38.6% growth in Q1.

AI Segment:

Product revenue increased 31.1% YoY to $296.6 million, slowing from 38% growth in Q1. As the CEO stated on the call, to wait 5-7 years is “untenable.” To compare, Bloom will power Oracle with on-site power solutions in as soon as 90 days.

Earnings:

Adjusted EPS of $0.10 beat estimates for $0.02, and represented a notable $0.16 improvement YoY.

GAAP EPS was ($0.18), missing estimates for ($0.10) as GAAP net margin declined sequentially.

Margins:

GAAP operating margin is approaching positive territory at (0.9%) in Q2, up nearly 5 points QoQ and 6 points YoY.

Adjusted operating margin was 7.1%, up more than 3 points QoQ and 8 points YoY. Adjusted EBITDA was $41.2 million

Cash:

Free cash flow was ($220.4 million) in Q2 for a (54.9%) margin. For the first half, FCF was ($345.3 million), just over a 1% improvement YoY.

Unrestricted cash and equivalents totaled $574.8 million, down from $794.8 million in Q1. This raises the risk that Bloom will turn to financing methods as Bloom likely awaits cash flows meaningfully improving in Q4.

Valuation:

If you want to see what AI can do for a valuation, look no further than BE. The stock used to trade in the range of 1.5 forward PS for many years and is now trading at a 14.5 forward PS. I can’t offer much in terms of where the valuation trends as it’s far beyond anything BE has traded at historically.

However, the forward PE ratio offers a bit more data as the forward PE of 219 is an area the stock has traded at consistently over the past year. With that said, the stock has traded as low as 33 forward PE, as well.

Risks:

The valuation is a risk yet we are less concerned with what BE does as an individual stock and would see any selloff being more of a broader catalyst.

#2: GEV: All Roads Lead to GEV

GE Vernova is the world’s largest gas turbine supplier at 25% ahead of Schneider at 24%. Even still, GEV nearly tripled its gas turbine equipment in the second quarter – a statement that has us sitting up in our seats. Per the earnings call: “Power orders grew 44%, led by Gas Power equipment nearly tripling year-over-year.”

Also, consider that we have been covering Bitcoin miners and other energy sources that can quickly help hyperscalers secure powered shells in the 1GW to 3GW range – yet GEV has 62 GW in backlog for gas equipment contracts, already surpassing expectations of reaching 60 GW by the end of this year. In other words, the chances that GEV is not a significant player in supplying energy to data centers for many years to come is nil.

This year, the company is expected to report $37 billion in revenue with strong earnings growth of 45.3%. The stock is not a hypergrowth profile, rather, it is a quality, defensible position that could do well during any periods of doubt in the broader AI trend.

The defensibility is particularly attractive when you consider that gas turbines is the crux of the issue for expanding gas power plants. According to Bloomberg’s calculations, more than “$400 billion worth of gas-fired power plants through the end of the decade are in jeopardy of delay or cancellation because of the lack of capacity to meet future turbine orders.” The same article points toward GE Vernova filling orders as far out as 2030.

Revenue:

The company’s Q3 revenue grew by 12% to $9.97 billion, beating estimates by 8.8%. Organically, revenue grew by 10% YoY to $9.83 billion, driven by strong electrification and power. Analysts expect revenue to decline (2.3%) YoY in Q4 but rise 3% QoQ, before rebounding to 8.7% in Q1 2026.

On the back of strong demand for power and equipment, management reiterated full-year revenue guidance and expects 2025 organic revenue to come at the high end of the guidance of $36 billion to $37 billion. The power segment organic revenue guide was maintained at 6-7%, and electrification segment was raised to ~25%, up from 20% previously in Q2. On a side note, the wind segment is expected to be down high-single digits, lowered from down mid-single digits due to the more challenging market conditions.

Revenue growth is set to accelerate over the next three years. Analysts expect a 6.6% increase in 2025, bringing the total revenue to $37.2 billion. Momentum is projected to build further, with revenue climbing to $41.0 billion in 2026, up 10.2% and to $46.7 billion in 2027, up 13.9% YoY.

AI Segment:

In Q3, GEV signed just over 12GW of new gas equipment contracts with ~1GW going directly to orders and ~12GW going into what’s called a slot reservation agreement. During the quarter, the company also converted 7GW of SRAs into orders and shipped 4GW of equipment.

Management had previously stated they would exit the year with 60GW “at better margins with significant momentum into ‘26.” Here is the breakdown from that comment:

33GW are in the backlog, up 4GW sequentially.

Slot Reservation Agreements (SRA) grew from 25GW to 29GW.

Total backlog including SRAs is 62GW, up from 55GW last quarter.

There was a discussion in Q2’s call that this represents about 3 years of backlog: “And we've talked about the fact that we'll get to at least 60 gigawatts by the end of the year. So that's directionally 3 years of backlog.” There was mention of eventually seeing 80GW to 100GW in the backlog but no date or other details were discussed, other than that’s the goal over time.

Earnings:

Q3 GAAP EPS came at $1.64, missing estimates by a (18.6%) but up from ($0.35) in the year-ago quarter. Despite the miss in Q3, earnings growth is projected to be strong over the next few quarters, with GAAP EPS up 87.3% to $3.24 in Q4 and accelerating to 128.6% to $2.08 in Q1 2026.

Analysts continue to expect strong EPS growth in the coming years. For 2025, analysts expect GAAP EPS to grow 40.9% YoY to $7.86, and 62.8% and 44.8% YoY in the subsequent two years, reaching $18.53 in 2027.

Margins:

Q3 adjusted EBITDA grew by 234% YoY to $811 million, driven by strong growth in the electrification and power segments, and a strong rebound in wind. Adjusted EBITDA margin improved 540 basis points YoY to 8.1% driven by profitable volume, better pricing, and productivity gains. The company is witnessing an annual EBITDA margin expansion, increasing from 2.4% in 2023 to 5.8% in 2024, and management has further guided expansion in the range of 8-9% for 2025.

Q3 operating margin was 3.7%, down slightly from 4.2% in Q2 but up from (4.0%) in the year ago quarter.

Cash:

Most importantly, management has maintained its FY free cash flow guidance from Q2, where it was raised from a range of $2.0 billion to $2.5 billion to a new range of $3.0 billion to $3.5 billion. This was primarily driven by a higher profit outlook and increased down payments due to rising orders. Through Q3, the company has generated $1.9 billion in free cash flow, implying a strong Q4 to finish the year inside its guided range.

The company generated free cash flows of $732 million in Q3 compared to $968 million in the same quarter last year. On a sequential basis, this was a sharp increase from $194 million in Q2.

Valuation:

Similar to other names in this group, GEV’s valuation has reset higher as the company demonstrates clear AI product–market fit. The stock is trading at 4.2 forward PS despite trading as low as 1 earlier this year.

The forward PE ratio offers room in the valuation. The stock is trading at 83 forward PE ratio yet has traded as high as 130 in the past.

Risks:

Of the companies featured here, GEV offers less risk as the sheer GWs it can provide are desperately needed for AI data center buildouts. However, it’s not a hypergrowth stock like the others. It’s included here to say – we are eyeing the stock as one that could outpace the legacy FAANGs for example, as it’s a leader within one of our largest and most timely thematic trends.

#3 Bitcoin Miners

Bitcoin Miners offer an exceptional risk/reward as these companies are pivoting from unprofitable Bitcoin mining operations to the high margin business of supplying powered shells for AI data centers. According to CoreWeave, powered shells are the biggest constraint in the AI build out, marking a critical shift to where Nvidia’s GPUs are no longer the primary constraint. With existing power, cooling, and network infrastructure, miners can deploy AI-ready capacity faster than new construction—offering Big Tech a critical shortcut in the race to scale.

Our Discovery Tier highlights a Bitcoin miner that is expected to report 325% YoY growth in the upcoming quarter with a positive operating margin. Knox sees significant upside and is ranking this Bitcoin miner as his #1 among all Bitcoin Miners.

Learn more about Discovery here.

Conclusion:

The best way to train for a marathon is to run a marathon. You can consider this report a training exercise while the real test is portfolio returns. Hopefully after reading this 43-page report, a few things are evident – we have a strong grasp of where the AI market plans to go next, that our process is nimble enough to capture winners in niche micro-trends, and we are capable of offering a level of conviction rare among AI investors. Consider that Nvidia is not one of our top performers this year (so far) – yet it’s been one of our strongest years to date.

With one quarter left, we look forward to making it our best of 2025.

Want to know what the I/O Fund is eyeing next for a new entry? Our Discovery tier surfaces new ideas in an effort to provide a significant edge to AI investors. Last week, we published our Top 10 New Ideas List for our Discovery members that pinpoints the stocks we are most likely to add to our portfolio next. Discovery was first to discover Bloom Energy, Core Scientific and Oklo to our portfolio, and these new additions became some of our biggest wins (thus far) in 2025. Current Pro and Advanced Members: To subscribe to Discovery with 30% off, click here to email us or email premium@io-fund.com and mention code DISCOVERY30.click here to email us or email premium@io-fund.com and mention code DISCOVERY30.

Advanced Members – stay tuned! This week, you will be receiving technical setups from Knox in his Quarterly Positions Report offering a complete picture of how we plan to enter or layer into the stocks listed above. These setups will also be covered in Knox’s upcoming webinar this Thursday at 4:30 PM Eastern. If you’re a Pro Member wanting information on Advanced or Discovery tiers, please email us at premium@io-fund.compremium@io-fund.com

Damien Robbins and Royston Roche, Equity Analysts at I/O Fund contributed to this analysis.

Recommended Reading:

The I/O Fund’s Top 15 Stocks for Q3 2025

Posted on July 23, 2025June 30, 2026 by io-fund

This quarter, I’d like to try something new by providing Members with something more actionable than a 1-hour webinar on key trends. Trends are important to cover, yet I also realize one of my main roles is to provide our Members with stock picks. The stock picks below represent the trends that are in play, and thus, the list answers quite a bit of the questions around how we plan to position and why.

The analysis tops out at 42 pages and 16,300 words and it took about three weeks to write; there was no stone unturned to come up with this list.

As you know, we are a portfolio that is managed in real-time. This means that we are constantly evaluating how our content informs a portfolio. Ultimately, we believe taking time to produce the analysis below will make the I/O Fund portfolio stronger, and we hope it does the same for you.

A few disclaimers:

This is determined by lagging indicators and incorporates last quarter’s financials. There are many risks each of the stocks face below, and the analysis below is not a substitute for using technicals to guide an entry. For example, it’s very common for great tech stocks to selloff 40% or more about roughly every 12 to 24 months – each investor will need to determine how they plan to handle the tech sector’s inevitable volatility.

In addition, the broad market is currently at all-time highs; with this comes stretched valuations particularly from any stocks that are popular or well-known. We’ve strived to bring you an objective analysis which includes some stocks with admittedly stretched valuations that we hope to buy lower, as well as those that are lesser-known and sitting at lower valuations despite having a 10/10 thematic profile.

We have divided 15 stocks into three sections:

Quality AI for longer-term holds: four stocks ranked
AI Hardware plays (medium-term hold): six stocks ranked, two honorable mentions
AI software: six stocks ranked, two honorable mentions

Combined, we believe these stocks will represent about 60-65% of the I/O Fund portfolio. The remaining 35% to 40% will be allocated to crypto, energy and momentum stocks of any tech sector. These are general guidelines. If crypto were to lead in a meaningful way, we’d allocate more to this sector or if crypto tops, we will lower this allocation and rotate into quality AI, etcetera.

Please also note, the stocks are ranked for their respective categories. It would be nearly impossible to rank these perfectly as market forces are unpredictable. Most importantly, the true rank of stocks is found in our portfolio positioning.

The goal of this exercise is to more closely align our portfolio with trends in play and with fundamentals that are on fire. As you can see, this is one of the lengthiest reports I have ever compiled weighing in at over 16,000 words – but yet, there’s more. In addition to this fundamentals-driven report, Advanced Members have a lengthy incoming Quarterly Positions Report coming in from Knox where he matches the stocks listed below with technical setups.

Major themes:

Nvidia Blackwell: we’ve covered the importance of the upcoming generation of GPUs thoroughly beginning a year ago in the analysis “Blackwell and the $200B Data Center” plus “Here’s Why Nvidia Stock Will Reach $10 Trillion Market Cap.” We’ve then helped to clarify timing around Blackwell arriving with an analysis in February pointing to signals the premiere SKU was delayed and then further analysis in May stating we believe those signals have cleared and Blackwell is now ramping on the premium side.
Regardless of when the delay finally clears (August call or November call), I continue to believe that Nvidia and related suppliers are the best way to position into the second half of the year. We can see ample evidence that Blackwell is ramping, and what will catch the market off guard, is that Blackwell Ultra is preparing to ramp quickly after over about a 6-month to 9-month time frame. It isn’t confirmed yet when Blackwell Ultra will ship in volume but we do know that CoreWeave was first to market with a Blackwell Ultra deployment in early July. What's important here is the clock has started – while simultaneously Blackwell is ramping in volume.

You can think of this as a one-two punch that includes the supply chain in terms of Nvidia saying to the doubters: “you haven’t seen anything yet.” Blackwell’s strength against AMD and custom silicon lies in the demand for Nvidia’s NVL72 systems, which combine 72 GPUs using NVLink and NVSwitch to function like one massive accelerator. These systems are particularly attractive to hyperscalers looking for an edge in model training and high-throughput inference.

As of now, competitors like AMD and custom ASIC providers do not yet offer a comparable system that scales to this degree. Such capabilities may emerge around 2026–2027, but Nvidia currently holds a clear lead in large-scale, multi-GPU system integration. This is key to why 2025 belongs to Nvidia, with the second half backloadedwith the second half backloaded.
AI is diversifying: As we look further out into 2026, we’ve been preparing our Members for the inference market to cause capex to diversify away from Nvidia toward cheaper GPUs and custom silicon. Yet we also published on why it won’t matter for Nvidia in the long run. Briefly, there is plenty of money pouring into AI use cases for Nvidia to do quite well with a lower percentage of the AI accelerator market. The company has mid-90% of the market today, I believe Nvidia will end the decade in the mid-70% or low-80% of the market based on what we see in other markets such as gaming. Nvidia will make up for the lower market share with AI software and automotive, for example, which has been forecast to be a bigger market than AI hardware once the market matures.
Quality fundamentals but stretched valuations: Look for many popular stocks to struggle at these valuations to push to the next level. We are looking more broadly at stocks (listed below) that present lower valuations to help offset this risk. There are stocks we plan to aggressively buy while there are others we prefer to wait for a lower valuation. Regardless of valuation, we are listing our Top 15 with the understanding some have buy plans at lower levels while others are entering a buy zone very soon.
Delayed market reaction to tariffs: we continue to believe tariffs pose a risk to the market and although anything could cause incoming volatility for the tech sector (pick a headline), the fact remains that it’s a tall order for earnings to overcome margin pressures and potentially slowing demand. The first quarter had the benefit of a pull forward; the upcoming quarter will likely show some sectors reporting compressed margins.

Section 1: Quality AI Stocks (Long-term buy and hold)

There are four stocks in this section ranked from #1 to #4

1. Nvidia: The AI Leader on the Precipice of Round Two

Thematic: 10/10
Fundamentals: 10/10
Valuation: 5/10

Brief Overview:

You can view an interview on Fox where I discussed the puts and takes going into last quarter’s earnings report plus the new price target I/O Fund published here. The major takeaway is that Blackwell has enough ammo to push the stock into the mid-to-high $200s or a $6+ trillion market cap.

The second most important update on Nvidia this quarter is the commentary around Blackwell shipping in volume. According to our previous analysis: “On average, major hyperscalers are each deploying nearly 1,000 NVL72 racks or 72,000 Blackwell GPUs per week and are on track to further ramp output this quarter.” The rough math here implies hyperscalers are deploying $3 billion every week right now since each rack goes for $3 million. Furthermore, the run rate of this comment implies data center revenue will be above and beyond analyst consensus for Q2, Q3 and Q4 – thus, either analyst consensus comes up or these systems will become further supply constrained somewhere down the line and analysts are being conservative for now.”

Third, Jensen Huang is calling for exponential growth in inference. You will hear our firm discuss why this market opens up an opportunity for other players such as AMD and Broadcom, yet I want to make sure that comment is not lost in interpretation as its also quite bullish for Nvidia.

During the earnings call, Huang stated inference is reaching an inflection point, stating “we've reached an extraordinary milestone with AIs that are reasoning, are thinking, what people call inference time scaling. Of course, it created a whole new — we've entered an era where inference is going to be a significant part of the compute workload.”

He later also stated:

“Yeah, thanks. Thanks, Ben. I would say compared to the beginning of the year, compared to GTC timeframe, there are four positive surprises. The first positive surprise is the step function demand increase of reasoning AI, I think it is fairly clear now that AI is going through an exponential growth, and reasoning AI really busted through […] So, number one is inference reasoning and the exponential growth there, demand growth.”

Overall Revenue Growth:

Last quarter was mired by the loss of China revenue, yet the company still managed to report a slight revenue beat in Q1, reporting 69.2% YoY growth to $44.06 billion in revenue, just ahead of the $43.25 billion consensus.

AI Segment Revenue Growth:

Nvidia reported 73.3% growth in data center revenue to $39.11 billion in Q1, marginally higher than analyst expectations from Visible Alpha of $39.08 billion. This marked the end of Nvidia’s seven-quarter streak of $1 billion-plus beats in the segment – based on the Visible Alpha estimate, Nvidia beat by just $33 million, its lowest in the past nine quarters. This makes sense considering they are in-between GPU generations.

Compute revenue rose 76% YoY but just 5% QoQ to $34.16 billion, impacted by the H20 ban, while Networking revenue rebounded swiftly, rising 56% YoY and 65% QoQ to $4.96 billion. Nvidia said Networking’s performance was “driven by the growth of NVLink compute fabric in our GB200 systems and continued adoption of Ethernet for AI solutions at cloud service providers and consumer internet companies.”

Earnings:

Nvidia reported a slight EPS beat despite the margin contractions, with adjusted EPS of $0.81 coming in ahead of the $0.75 estimate. GAAP EPS of $0.76 missed estimates for $0.81.

Adjusted EPS growth slowed quite dramatically, decelerating more than 38 points sequentially, in part due to the H20 ban; Nvidia noted that excluding the ban, adjusted EPS would be $0.96. This would represent YoY growth of 57.4% versus the 32.8% reported.

Looking ahead, adjusted EPS growth is expected to rebound and remain in the low to mid-40% range as margins recover. However, given that Q1’s EPS excluding the ban showed growth in the high-50% range, estimates may move higher as Q2’s margin outlook shows almost no persisting impact.

Margins:

GAAP gross margin was 60.5% and adjusted gross margin was 61%, around 10 points below management’s initial guidance for 70.6% and 71% due to the $4.54 billion charge related to the H20 ban. For Q2, management guided for 71.8% GAAP gross margins and 72% adjusted gross margins, a rebound of approx. 11 points sequentially.
GAAP operating margin was 49.1%, well below guidance for 58.5% and a sequential contraction of 12 points. Adjusted gross margin was 52.8%, nearly 10 points below the guide for 62.6% and a sequential contraction of more than 12 points.
For Q2, management’s guidance implies operating margins will rebound with gross margins, projecting approximately a 10 point sequential expansion to a 59.1% GAAP and 63.1% adjusted operating margin.
GAAP net margin was 42.6%, while adjusted net margin was 45.2%. The broad-based margin recovery in Q2 is expected to mostly transfer through to the bottom line, with management guiding for a 7.6 point recovery to a 50.2% GAAP net margin.

Cash:

Cash flows were surprisingly strong as Nvidia’s cash flow margins expanded approximately 20 points sequentially, while it added more than $10 billion in cash to its balance sheet.

Operating cash flow was $27.41 billion, up nearly 79% YoY on higher revenue. OCF margin was 62.2%, up 20 points QoQ and more than 3 points YoY.

Free cash flow was $26.14 billion, up 75% YoY. FCF margin was 59.3%, up nearly 20 points QoQ and just 2 points YoY.

Valuation:

Nvidia trades at a 20 forward PS with its minimum sales ratio at 10 and maximum around 30. Therefore, the stock is in the mid-range. The stock trades at a 38 forward PE ratio, which is also right in the middle of its trading history, seeing a minimum of 20 and a maximum of 48 in recent years.

Where the edge in Nvidia’s valuation lies is the sudden release of Blackwell Ultra following Blackwell. This should create a new, upward trajectory in revenue growth (if we assume supply chains cooperate) since there will be a historic, back-to-back release in two monumental GPU generations. To put it another way, Blackwell’s delay caused a year of flat price action but given Nvidia continued to develop its next generation Blackwell Ultra during that delay, probability favors us seeing a $6 trillion market cap sometime next year.

Notable Risks:

Perhaps a $6 trillion market cap sounds fancy yet there will be higher returns in choice Nvidia suppliers as the stock is already at $4 trillion. The risks to Nvidia are low, yet there is opportunity with a quality stock especially when there are many beneficiaries a bit further down the supply chain that will see hypergrowth for Blackwell and Blackwell Ultra.

2. TSM: The Stock with More Pricing Power than Even Nvidia

I try to not use the word “moat” too loosely, yet TSM is deserving of this recognition for its deep IP and market lead. TSMC continues to deepen its moat with advanced nodes, such as N2 and A16. The company already powers tens of trillions in market cap on the stock market when you consider Apple, Nvidia, Broadcom, Amazon, AMD and Google are customers of TSMC. Essentially, all mega cap stocks have an AI strategy spanning merchant GPUs and custom silicon, and of course, software – yet the common denominator to these strategies is they all funnel into TSMC.

The most advanced node shipping today is the 3nm, offering 15% better performance than the 5nm process when power level and transistors are equal. The die sizes are an estimated 42% smaller than the 5nm and TSMC also states the 3nm process can lower power consumption by as much as 30%.

Power efficiency is a major advantage, helping to deepen TSMC’s moat. Samsung was first to introduce 3nm process chips in 2022 yet has not been as competitive on yield and power efficiency at a roughly 10% to 20% difference compared to TSMC. The moat is visibly seen in TSM’s pricing power with the dominant foundry charging 25% more for its 3nm process compared to its 5nm process, and customers are willing to forego Samsung to pay the higher pricing.

Last year, companies such as Apple, Nvidia, AMD and Intel committed to working with TSMC for its 3nm process, and eventually Google and Qualcomm left Samsung “after careful consideration” to also secure a partnership with TSMC.

This was an important moment for TSMC to complete its near-monopoly in advanced nodes as Google had been outsourcing its Tensor processors to Samsung’s foundry for four generations, before moving to TSMC for the fifth generation. Qualcomm also switched to TSMC from Samsung for the Snapdragon 8 Gen 4 series.

To attract these large customers with different end markets, TSMC offers a few 3nm processes, such as the N3E, N3P and N3X. This allows a company like Apple to customize the 3nm chips differently than AI chips for hyperscalers. N3E is the baseline for IP design with 18% increased performance and 34% power reduction, N3P has higher performance and lower power consumption, whereas the N3X will offer high-performance computing very high performance but with higher power leakage.

To illustrate the near monopoly that TSMC has over other foundries, consider that its market share stands at 67.1%, up 2.4% QoQ in Q4. Meanwhile, second-place Samsung was at 8.1% down from 9.1% for a lead of 59 points.

When comparing revenue, TSMC reported $26.85 billion in Q4 for a 14.1% increase compared to Samsung’s $3.26 billion, which declined 100 basis points to 8.1%. The most recent quarter, TSMC furthered the lead with $30.7 billion in revenue.

Overall Revenue Growth:

TSMC offers monthly revenue reports, providing a high level of visibility into the chipmaker’s growth. For example, May revenue rose 39.6% YoY to NT$320.52 billion (~US$10.7 billion), while June revenue rose 26.9% YoY to NT$263.71 billion (~US$9.0 billion). For the first half of the year, revenue rose nearly 40% YoY to NT$1,773.05 billion (~US$55.6 billion).

Q2 revenue also outperformed the company’s guidance of $28.4 – $29.2 billion, rising 44.4% YoY to $30.07 billion, driven by AI and HPC products with some FX tailwinds. Q3 is expected to remain strong with 37.8% YoY growth to $32.4 billion at midpoint.

Regardless of which way you dice it, TSMC is guiding for above industry growth, updating its 2025 guidance in the most recent quarter from mid-20% YoY growth to close to 30% YoY growth.

Of this, AI accelerator revenue is expected to double in 2025 and management also forecasts AI to grow at a mid-40% CAGR for five years from 2024: “Based on our planning framework, we are confident that our revenue growth from AI accelerators will approach a mid-40s percentage CAGR for the next five years period starting from 2024.”

AI Segment Revenue Growth:

TSMC continues to ride AI accelerator tailwinds, evident in its rising HPC revenue and mix. HPC revenue continued to accelerate in Q2, now reaching $18 billion, marking its largest QoQ increase of nearly $3 billion. HPC accounted for 60% of TSMC’s revenue, expanding slightly from 59% of revenue last quarter. Management stated that they are continuing to observe robust AI-related demand from customers with no change in behavior, despite lingering tariff-related concerns.

In the latest quarter, advanced nodes below 7nm drove 74% of wafer revenue with 3nm contributing 24% of revenue and 5nm representing 36% of revenue. Nvidia is not on the 3nm process yet for its Blackwell shipments, thus 5nm is outsized in terms of its market share.

Earnings:

TSMC delivered record profit in Q2, rising 61% YoY to NT$398.3 billion, or ~$12.8 billion. Adjusted EPS of $2.47 beat estimates for $2.31 and increased nearly 67% YoY, accelerating from recent growth in the 50% range. This EPS growth also reflects TSMC’s operating leverage, outpacing revenue growth by 23 points.

For Q3, EPS growth is expected to increase 27% to $2.46, before decelerating rather sharply to barely in the double-digits by Q4 as it begins to lap these more difficult 50% growth comps.

For 2025, adjusted EPS is expected to increase 35.2% YoY to $9.52, up from 31.5% growth two months ago. Growth is forecast to decelerate to 14.4% in FY26 to $10.89.

Margins:

Similar to Nvidia and Broadcom, TSM has excellent margins:

Gross margin was 58.6% in Q2, at the high end of the guided range for 57% to 59%. Gross margin declined sequentially from 58.8%, with a 2.2 point headwind from FX and a 1 point headwind ramping overseas fabs offset by higher capacity utilization.
Operating margin was 49.6%, increasing 1.1 points sequentially from operating leverage, and above guidance for 47% to 49%. Operating margin was up more than 7 points YoY.
Net margin was 42.7%, down slightly from 43.1% in the prior quarter but up nearly 6 points YoY.

Over the next five years, management sees the dilutive impact from ramping its overseas fabs widening, projecting it to start at 2-3% each year in the early ramp stages before widening to 3-4% each year. Despite this, TSMC remains confident in its ability to keep long-term gross margins at 53% or higher.

Cash:

Free cash flow was $6.5 billion in Q2 for a 21.7% margin, down from a 35.1% margin in Q1 and a 25.5% margin in the year ago quarter. This is at the lower end of the typical range for TSMC, which tends to track between 20% to 30%.

Valuation:

TSM is trading at the high end of the range on the bottom line at 24 forward PE ratio, with its highest being 30 over the past year before it saw a sharp adjustment to 15 forward PE Ratio, which marked a bottom. Forward PE Ratio of 20 is mid-range and more comfortable for this stock.

On the top line, TSM is trading at 10 forward PS with 12 marking a top over the past year and 6 marking a bottom. This leaves very limited upside.

Risks:

Valuation tops the list as the primary risk given the stock is rather insulated from competition, and is also insulated from any tariff drama as it has the best pricing power in the industry. Onshoring its fabs with continued stimulus helps to create a more durable stock.

3. Broadcom: Quietly Reached $1 Trillion, Will Displace the FAANGs

Thematic: 10/10
Fundamentals: 10/10
Valuation: 1/10

Similar to Nvidia and TSM, Broadcom will likely remain on the Top 15 list for years to come and will at times outrank Nvidia.

Broadcom stock joined Nvidia, Alphabet and Microsoft in calling out surging AI inference demand, noting that this rapid growth could drive increased demand for custom silicon in the second half of 2026, and with it, higher AI revenue.

Despite an in-line print and guide, Broadcom’s AI revenue is tracking above Street estimates for next year towards the $30 billion mark, up nearly 150% in two years, with growing tailwinds from inference and networking as clusters increase in size. AI revenue growth is also tracking Broadcom’s addressable market forecast of a 60% CAGR.

Broadcom is cementing itself as the clear second in AI with key ingredients for success as inference demand rises. However, its premium valuation to Nvidia looks to be pricing in above-expected AI revenue growth into 2027, likely closer to a 70%+ CAGR, as there exists a $160 billion gap in AI-driven revenue between the two.

HSBC estimates that Broadcom’s ASIC revenue could rise as much as 128% YoY next year to $28.3 billion, fueled by Google’s TPU ramp driving a 92% YoY increase in ASIC ASPs. – xAI Beth_Kindig xAI Beth_Kindig

Overall Revenue Growth:

Broadcom reported $15 billion in revenue versus $14.99 billion expected, up 20%. Management expects about $15.8 billion in third-quarter revenue, versus $15.7 billion.

AI’s strength is masking persisting softness in non-AI revenue, which could continue to be pressured due to Broadcom’s high consumer exposure. Broadcom noted that non-AI revenue “is close to the bottom” but it “has been relatively slow to recover” with revenue down (5%) YoY to $4 billion in Q2.

AI Segment Growth:

Broadcom has cemented itself in second place in AI revenue as it closes in on $20 billion this fiscal year in AI revenue — with a line of sight toward $30 billion by the end of fiscal 2026. AI revenue accounted for more than 50% of Semiconductor revenue for two quarters in a row and nearly 32% of total revenue in Q2.

AI semiconductor revenue rose 46% YoY to $4.4 billion, in line with management’s guidance. Although this was a deceleration from 77% YoY growth in Q1, Broadcom forecast $5.1 billion in AI revenue in Q3, pointing to a rebound to 60% YoY growth – marking ten consecutive quarters of growth.

In the current quarter, the 46% AI semiconductor growth was driven by networking, which was up 170% YoY and represented 40% of AI revenue. In the opening remarks, the CEO stated the following regarding this outsized growth: “As a standard-based open protocol, Ethernet enables one single fabric for both scale out and scale up and remains the preferred choice by our hyperscale customers. Our networking portfolio of Tomahawk switches, Jericho routers and NICs is what's driving our success within AI clusters in hyperscalers.”

CEO Hock Tan said that Broadcom’s hyperscale clients are “doubling down on inference in order to monetize their platforms,” and as a result, he expects Broadcom could “actually see an acceleration of XPU demand into the back half of 2026 to meet urgent demand for inference on top of the demand we have indicated from training.” This new dynamic is what is driving Tan’s confidence in stronger growth in FY26, saying that he now anticipates the “fiscal 2025 growth rate of AI semiconductor revenue to sustain into fiscal 2026.”

This commentary plus potential demand acceleration in 2H 26 suggests that Broadcom has visibility into $30 billion AI revenue potential next year. Broadcom has not provided a full FY25 AI revenue guide yet, but it is on track to deliver approximately $19 to $20 billion in AI revenue in FY25, up ~60% YoY assuming 60% growth to $5.9 billion in Q4.

Maintaining 60% growth through FY26 would project AI revenue to $30 to $32 billion. This trajectory indicates Broadcom is likely driving AI revenue ahead of expectations over the next four to six quarters, with Morgan Stanley saying that $26 to $30 billion in AI revenue is “higher than what is in Street models.” Evercore is modeling 58% AI revenue growth in FY25 and 50% in FY26, implying $28.9 billion.

Earnings:

Broadcom reported $1.58 adjusted versus $1.56 expected.

Margins:

Broadcom has excellent margins especially given its scale as primarily a hardware company:

GAAP Gross Margin: 68% and adjusted gross margin of 79.4%

GAAP Operating Margin of 38.8% and Adjusted operating margin of 65.3%

Net Margin of 33% and Adjusted net margin of 51.9% for adjusted net profit of $7.8 billion.

Cash:

Broadcom has seen expanding cash flows with operating cash flow margin of 43.7% up from 36.7% last year. Free cash flow of 42.7% compares to 36.7% last year for free cash flow of $6.4 billion. The company had $9.48  billion at quarter-end

Valuation:

Broadcom has a cringe-worthy valuation at 42 forward PE ratio and 21 forward PS. You can argue it’s worth as much as Nvidia given its AI growth, yet there is a whopping $160B delta between Nvidia and Broadcom’s AI sales. Broadcom is traditionally a 6 forward PS company and a 2 current PS ratio. Keep in mind, Broadcom supplied Apple during the mobile boom and outperformed most FAANGs, therefore, even with being in the center of a microtrend the stock is overvalued according to most standards.

Notable Risks:

The valuation on Broadcom stands out as one of the most egregious on our list, second only to Palantir and perhaps tied with Cloudflare. Some investors buy stretched stocks successfully for a period of time and believe they’ve outsmarted the market; however, I do not see these valuations sustaining, and in fact, these three point more toward a bubble of sorts.

You can read more in the analysis: “This AI Stock is Set to Surge from Inference Demand” on the free side including a follow-up with information on the premium side.

4. AMD: The Dark Horse in our Stable; Patience is a Virtue

Last month, AMD introduced its Instinct MI350 series GPUs, including MI355X with up to 4X performance over the previous MI300X generation and up to 40% more tokens per dollar compared to Nvidia’s B200 accelerators. The company also previewed its Helios rack-scale server architecture featuring the MI400s for 2026 deployments.

According to Tom's Hardware AMD is claiming the eight-GPU MI355X system is 1.3X faster than Nvidia’s DGX GB200s systems with Llama 3.1 and up to 1.2X faster than the B200 HGX systems in inference for DeepSeek R1 with equivalent performance as Llama 3.1 when tested at FP4.

Perhaps what matters most to investors is what the GPUs will cost. The team has been digging around and found the following this week:

HSBC last week upgraded AMD to Buy and doubled its price target to $200, saying that it expects the MI355 GPUs [and MI400s] to command a $25K ASP, up materially from prior assumptions for $15K, potentially driving upside to FY26 AI revenue – xAI Beth_Kindig xAI Beth_Kindig

Overall Revenue Growth:

AMD reported a double beat in Q1 with revenue of 36% and data center growth of 57%, with the beat filtering down to the bottom line with EPS growth of 55% — ahead of revenue.

AMD reported Q1 revenue of $7.44 billion, solidly ahead of the $7.12 billion estimate and above the upper range of its guidance for $7.1 billion, +/- $300 million. Revenue growth accelerated to 35.9% YoY, led by data center and client, although as of now, this is expected to be the peak growth quarter for the year.

On one hand, it is quite impressive AMD can overcome the impact from China last quarter and meet consensus for next quarter. On the other hand, analysts have been lowering estimates as AMD was supposed to see revenue of $7.77 billion for growth of 33% as of last October rather than the 26.7% in the current quarter.

Arguably, the news that Nvidia can resume sales of H20s may be bigger news from AMD if we assume the $1.5B impact is removed from AI revenue, as it's 30% of AI revenue as it stands for this company versus less than 10% for Nvidia (at $15B versus somewhere around $150B for rest of year in AI revenue).

However, if we look at the facts on the table, AMD is a weaker stock overall than Nvidia, TSM and Broadcom as it stands today. It is my speculation this changes and AMD shows its full potential in 2026-2027 aligned with the inference market and the shift in priority where Big Tech becomes more cost conscious.

AI Segment Growth:

Data Center revenue grew 57% YoY but declined (5%) QoQ to $3.67 billion, driven by sales of EPYC CPUs and Instinct GPUs, accounting for over 49% of AMD’s revenue in the quarter.

While growth decelerated from 69% in Q4, it’s coming against a much tougher comp at 80% YoY whereas Q4 of last year offered a lower comp of 38% in Q4 2023.

Regarding GPUs, management stated their AI revenue increased by a “significant double-digit percentage year-over-year.” The MI325X is shipping in volume while the next-gen Instinct MI350-series chips are on track for “accelerated production by mid-2025.”

We discussed last quarter that AMD was pushing up their delivery on the MI350s to mid-year for relative competitiveness. For Q2, data center will decline due to the MI308 revenue being excluded.

When asked about future quarters, the CEO Lisa Su stated the DC segment would resume growth after Q2: “in Q2, it's not going to grow year-over-year just given what we've said about the $700 million coming out of Q2 and how we had previously talked about the evolution. But we do believe that we'll grow year-over-year going forward, in Q3 and Q4 certainly, for us to do the full year with strong double-digit growth.”

To put it plainly, on the AI accelerator front, this will be the first time that AMD will overlap Nvidia in terms of benchmarks on GPUs. Please do note, the amount of time that AMD’s current generation of GPUs and Nvidia’s GPUs overlap will be brief – and will only be at the single GPU and 8-GPU system level. AMD was originally expected to ship the MI350s at the end of this year yet are moving the shipments up – which fits with AMD’s tradition of underpromising and overdelivering.

However, the accomplishment is noteworthy as it’s setting the tone as the inference market begins to ramp. In other words, AMD ceded the training market to Nvidia – but I do not expect that to be the case with the inference market.

When Blackwell Ultra ships, the B300s will offer FP4 TFLOP/s that is 1.3X faster than AMD’s current MI350X and MI355X. With that said, because AMD has prioritized competing on memory — its bandwidth and capacity is expected to be on par with Blackwell Ultra.

The market is forward-looking, which means investors should be too. AMD is closing the gap on single GPUs and 8-GPU systems, yet the MI400s will mark a pivotal moment as AMD will attempt to compete on rack-scale systems with Helios, its 72-GPU systems. If things go as planned, AMD will be competitive with Nvidia on GPU, memory and interconnect performance — while potentially taking the lead on memory capacity and bandwidth.

Earnings:

AMD reported adjusted EPS of $0.96 in Q1, slightly ahead of estimates for $0.93. This represented YoY growth of 54.8%, accelerating from nearly 42% growth last quarter. Similar to revenue, Q1 is currently expected to be peak growth for EPS, with Q2 estimated to record 27.8% growth before slowing to the low 20% level by Q4.

However, management commented that EPS growth is expected to grow much faster than revenue in Q2: “Looking at Q2, at the middle point of our guidance, revenue will be increasing 27%, and we do expect the earnings per share growing much faster than the top line revenue growth.”

Margins:

AMD’s margins are not nearly as strong as Nvidia or Broadcom’s, and this is ultimately reflected in the valuation. However, should the HSBC analyst quoted above be correct (and general consensus that AMD has some kind of pricing power), the margins will improve over time as GPU sales ramp at higher ASPs.

Q1 GAAP gross margin was 50%, up 3 points YoY, while adjusted gross margin was 54%, up 2 points YoY.
GAAP operating margin was 11%, a strong expansion of 10 points YoY, and adjusted operating margin was 24%, up 3 points YoY.
GAAP net margin as 9%, up 7 points YoY, and adjusted net margin was 21%, up 2 points YoY.

Cash:

Operating cash flow was $939 million for a 13% margin, expanding from a 10% margin in the year ago quarter.

Free cash flow was $727 million for a 10% margin, expanding from a 7% margin a year ago.

Expect these to improve once the AI story ramps.

Valuation:

AMD is trading mid-range at forward PS of 7. The stock can trade as low as 4 or high as 12. The stock is trading at a 40 forward PE Ratio, which is also mid-range given it’s traded as low as 25 and as high as 55 in the past year.

Notable Risks:

The risk to AMD is primarily in Q2’s data center growth decline, and how quickly can the company ramp its MI355s and subsequent MI400s while in the midst of Nvidia’s large shadow – will we see a solid surprise arrive in Q3, Q4 or even into next year? My best guess is the most meaningful AMD moment is not likely to occur during Blackwell’s NVL72s release – I think 2025 belongs to Nvidia and somewhere between 2026-2027 we switch it up.

My current prediction is that AMD will offer higher stock returns than Nvidia by 2028, which you can read more about here in the analysis: AMD vs Nvidia: The AI Stock that Could Win by 2028.

Section 2: AI Hardware Plays (Medium-term hold)

This section has six stocks ranked #1 to #6 with two honorable mentions

1. Astera Labs: AI Networking Pureplay Serving Two Enormous TAMs (total addressable markets)

Thematic: 10/10
Fundamentals: 10/10
Valuation: 5/10

Astera Labs reported an impressive beat and raise in Q1, with GAAP margins strengthening as revenue continues to grow at a triple-digit rate. On top of this impressive beat, the growth story for Astera Labs is only beginning. The commentary regarding their product diversification and higher dollar content going into the second half of the year was quite clear as to the growing opportunity this company is poised to capture.

Primarily, Astera offers unique positioning that allows them to capture both the merchant GPU market and custom silicon market across its three products lines Astera, Taurus and Scorpio. This widens the TAM and allows for steady revenue growth despite hiccups or delays from a single AI system (which we’ve seen plenty of disruption recently across those with high customer concentration with Nvidia).

In addition to being a strong custom silicon vendor for hyperscalers, Astera will participate in Blackwell once it (finally) ships in volume as the company offers PCIe scale-out and Ethernet scale-up. Their new products Scorpio P-Series and Scorpio X-Series are fabric switches that are particularly well-suited for the immense demand that is expected for customization of racks as architectures scale-up in the second half of the year and beyond.

Notably, Aries PCIe retimers and Taurus Ethernet smart cable modules are driving the revenue today with the Scorpio P-Series beginning to ramp. However, there are many catalysts on the horizon for Astera which adds to the trifecta of a strong growth story:

Serving both ASICs and GPUs greatly increases TAM and diversifies revenue; rare in the AI systems ecosystem
Preparing to serve the scale-out demand with increasing higher dollar content; specifically on Scorpio but also on Aries
Offering strong cross-sell opportunities as it aims to be the first to solve unique challenges for both GPU and custom silicon utilization – and is solving these issues in a way that avoids vendor lock-in for the large hyperscalers who want a mix of both custom silicon and merchant GPUs (Nvidia or AMD).

Astera Labs Fundamentals Update:

Overall Revenue Growth:

Astera Labs reported an impressive 144.3% YoY revenue growth in Q1 to $159.4 million, topping analyst estimates for $151.5 million in the quarter.

For Q2, Astera delivered a solid raise at $170 to $175 million, more than 7% ahead of the $160 million estimate. This points to YoY growth of 124.5% at midpoint, ahead of estimates for just 108% YoY. What’s impressive about this ramp is that Astera is guiding to deliver this 125% growth in Q2 against its 619% YoY comp (against a small base), for its seventh-straight triple-digit growth quarter.

Astera has seen revenue growth decelerate over the past few quarters, with growth expected to continue decelerating as Astera laps its rapid ramp quarters. What’s impressive about this ramp is that Astera is guiding to deliver this 125% growth in Q2 against its 619% YoY comp (against a small base), for its seventh-straight triple-digit growth quarter.

For the full-year, Astera did not provide a guide, though estimates heading into Q1’s report were pointing to 70.4% YoY growth to $675.2 million in revenue. However, given that Q1 and Q2 have combined for a $20 million beat compared to current estimates, it’s likely that full-year revenue estimates will likely move closer to (or above) $700 million in the coming days. This would correspond to YoY growth of nearly 77%.

Key AI Segment:

The Scorpio P-Series is shipping this quarter and are qualified for Nvidia systems, yet the X-Series will ship in H2 with a bigger opportunity for custom silicon clusters. The Scorpio P-Series is a small chip that connects the CPU, GPU, NIC and NVMe storage. Rather than building a large switch, the company built a smaller device that is more efficient for high-speed signals to help feed GPUs with data. The fewer ports and smaller switch decrease complexity in a bid to compete against Broadcom with twice the lane count.

Inventories rose 18.2% QoQ to $51.1 million, likely driven by the ramp of Astera’s Aries 6 and Scorpio P-series products.
Accounts receivable surged 100.5% QoQ to $69.8 million, driven by Astera’s largest customers.
Astera’s receivable balance from its top customer in the quarter rose 363% QoQ to $20.9 million, while its balances from its second and third largest customers rose 75% and 90% QoQ to $14.7 million each.
Days sales outstanding also increased from 20-ish days in the past to 40 days this quarter. This is likely foreshadowing Astera is preparing for larger shipments in the next 1-2 quarters

Latest report can be found here: Astera Labs: Product Differentiation is Set to Soar in H2 and Beyond

Earnings:

Astera delivered an impressive 350% beat to GAAP EPS estimates in Q1, driven by its operating margin expansion, while forecasting EPS above estimates for Q2.

Adjusted EPS of $0.33 beat estimates by $0.05, representing YoY growth of 230%.

GAAP EPS of $0.18 beat estimates by $0.14, improving from $0.14 in Q4 and marking its second straight quarter of GAAP profitability on the bottom line.

For Q3, Astera guided for adjusted EPS between $0.32 and $0.33, approximately flat QoQ but up 150% YoY at midpoint.

Margins:

Gross Margin = 75%
GAAP operating margin = 7%
Net margin = 20%

Astera is guiding for margins to remain strong in Q2, with GAAP operating margin expanding. Gross margin was guided at 74% once again, while GAAP operating margin is forecast at 7.9%, up 0.8 points sequentially. Adjusted operating margin is forecast to contract 2.6 points QoQ to 31.1%.

Cash:

Operating cash flow was $10.5 million for a 6.6% margin, expanding slightly from a 5.6% margin in the year ago quarter.

Free cash flow was $6.0 million, for a 3.7% margin, improving from a 0.3% margin in the year ago quarter.

Valuation:

Astera’s valuation is trading mid-range of its historic trends at 21 forward PS and could trade as low as 40% lower from here or could have up to a 200% upward move from the current valuation. There is no guidance from valuation on where the stock will go next whereas others are more visibly overstretched.

Notable Risks:

Coming up on tough comps, high SBC weighs on operating margin but gross margin is one of the highest in AI semis. Cash has a weak margin, but scale will likely resolve any cash flow margin issues

2. Credo: AEC Networking Tailwinds

Thematic: 10/10
Fundamentals: 10/10
Valuation: 5/10

Credo continues to report outstanding revenue growth, up 180% YoY in Q4 and guided to accelerate further in Q1 as management touted growing traction with hyperscalers, new design wins in qualification and strong customer forecasts driving sustained AEC growth.

GAAP margins have expanded significantly down the line with operating margin quickly approaching 20% as signs of operating leverage emerge. Cash flow margins were robust in Q4 on strong collections, while inventories surged over the past two quarters, indicating that Credo’s hypergrowth phase will likely continue for a few quarters.

Management hinted that a new DSP deal with a hyperscaler represents its largest revenue opportunity to date, with two new hyperscaler customers ramping up in FY26. Backed by these arising revenue streams, Credo guided for revenue growth of 85%+ next year, or over $800 million.

Latest report can be found here: Credo Reports 180% YoY Growth and 20% GAAP Operating Margin.

Overall Revenue Growth:

Note: Upcoming earnings is Q1 Fiscal Year 2026

Credo reported 179.7% YoY and 25.9% QoQ growth to $170.0 million in revenue in Q4, beating the consensus estimate for $159.6 million. Revenue growth has sharply accelerated throughout the fiscal year, up from the 60% to 70% level in 1H to high triple digits in 2H.

For Q1, Credo guided to $185 million to $195 million in revenue, pointing to a nearly 40 point sequential acceleration to 218% YoY growth at midpoint. This was also 17% above consensus estimates for $162.4 million heading into the report. Revenue growth estimates have moved sharply higher since February. Q1’s growth estimate just four months ago was 133.4%, and is now nearly 85 points higher, while Q2’s growth estimate has risen 74 points from 100.9%.

For fiscal 2025, Credo reported a 122 point acceleration to 126.3% YoY growth, with revenue of $436.8 million. For fiscal 2026, Credo guided for revenue to exceed $800 million, for growth in excess of 85% YoY, while analysts are now expecting $804.1 million.

Key AI Segment:

Credo reported a significant 80-point sequential acceleration in product revenue growth to 303.3% YoY in Q4, with revenue of $164.5 million. Credo said AEC products are gaining traction in rack-to-rack distances up to 7 meters, with xAI being the most successful customer at that distance with a second customer ramping this year.

For optics, Credo noted that it reached its revenue targets and ended FY on strong momentum with an expanding customer base. As previously mentioned, Credo is targeting 100%+ optics revenue growth in FY26. Moving forward, Credo expects to diversify its customer base, eyeing up to five >10% customers in FY26, up from three in FY25. Credo’s largest customer, rumored to be Microsoft, accounted for 61% of revenue in Q4.

Earnings:

Credo’s fiscal 2025 adjusted EPS of $0.70 increased from $0.08 in the prior year. Credo generated the bulk of this EPS in H2 as revenue and margins surged.

Adjusted EPS of $0.35 in Q4 beat estimates by 29.6%, representing growth of 400% YoY. Growth is forecast to accelerate to 782% in Q1 to $0.35 on a low comp, before slowing to 17% YoY by Q4 FY26 against a much tougher comp.

Margins:

Credo is GAAP Profitable.

Gross Margin = 60%
GAAP OM = 8.5%
GAAP Net Margin = 12%

Cash:

The company has expanding cash flows.

OCF margin was 34% in the quarter, compared to 3.1% last quarter and 6.8% a year ago. Operating cash flow was $57.8 million up from $53 million QoQ.
Free cash flow was $54.2 million in Q4, for a 31.9% margin.
For FY25, free cash flow was $29 million, for a 6.6% margin, down from an 8.9% margin last year on higher capex.

Valuation:

Credo’s valuation is trading mid-range of its historic trends at 21 forward PS and could trade as low as 40% lower from here or has another 50% upward move. There is no guidance from valuation on where the stock will go next whereas others are more visibly overstretched.

Notable Risks:

Coming up on tough comps, 75% exposure to Hong Kong, copper recently undercame new tariff laws and where Credo sources copper is unlikely to be of public record. GAAP OM could be better but gross margin is impressive for AI semi

3. Supermicro: Key Nvidia Supplier Sitting in Plain Sight

Thematic: 10/10
Fundamentals: 4/10
Valuation: 10/10

Super Micro, also known as Supermicro, is sandwiched in the AI trend between hyperscalers and major chip design companies. The company is a server maker that started off by making motherboards and other components before it began making complete systems. The company is unique in that it sits between being an equipment manufacturer (Dell, HP) and being a design manufacturer (Foxconn).

To give you an idea as to the company’s sudden ascent off the Hopper generation of GPUs from Nvidia, consider that SMCI had revenue of $2.5B in 2021 and reported $22 billion in the fiscal year ending in June – or about 9X in four years. Given AI servers are increasing in complexity, and will require thermal management including direct liquid cooling, this is a baseline of what SMCI will be capable of over the next few years. There may not be the sudden 9X trajectory we saw off small numbers, but there will likely be ample growth.

The company is not without risks. There was a high-profile accounting issues recently, and Supermicro also struggles with cash (potentially diluting shareholders down the line) and has slim operating margins.

I’m calling this one “sitting in plain sight” because its valuation is low relative to the opportunity. It's also apparent the market has overlooked not only Supermicro but is overlooking Nvidia’s Blackwell since it took much longer to arrive than originally anticipated.

Overall Revenue Growth:

Fiscal Q3 net sales were $4.6 billion, up ~19% year over year. However, this was 19% lower than the prior quarter and below management’s forecast due to delayed customer commitments (some clients postponed orders while awaiting new AI platforms)

AI Segment Revenue Growth:

AI-focused products drove the majority of sales. Management noted that AI GPU platforms accounted for over 70% of Q3 revenue. Supermicro achieved volume shipments of new AI server platforms.

Earnings:

Super Micro's EPS for the most recent quarter (Q3 FY2025) was $0.31. This figure represents the non-GAAP diluted net income per share. The company also reported a GAAP EPS of $0.17

Margins:

Profitability declined sharply. Gross margin fell to ~9.6% (versus ~15.5% in Q3 last year). Pressured by higher inventory reserves and lower volumes

Gross Margin (GAAP): 9.6%, down from 11.8% in the prior quarter and 15.5% year-over-year
GAAP operating expenses were $293 million, generating GAAP operating income of approximately $147 million (net income before taxes and interest), which equates to roughly 3.2% operating margin on $4.60 billion revenue
Net income of $109 million on $4.60 billion in sales yields a 2.4% net margin

Cash:

The company generated $627 million in operating cash flow during the quarter. It ended Q3 with $2.54 billion in cash (against $2.49 billion in debt), yielding a slight net cash position of about $44 million

Valuation:

Valuation is what makes this stock attractive. I believe the last earnings report was a “red herring” of sorts, meaning it does not represent the bull story, which is the incoming shipments from Blackwell. This means the fundamentals were depressed last quarter, further depressing the valuation.

Trading at 1 fwd PS is worth the risk, in my opinion. This stock should always have a trailing stop due to weak margins and weak cash (overall weak FA profile). However, the growth story should also not be ignored. Look for this stock to comfortably go to 2-3 fwd PS on the upper end, and as low as 0.5 fwd PS which would be a layered buy in addition to 1 fwd PS. Overall, I expect fundamentals and valuation to resume Hopper-generation status sometime in the next 6 months – which means max’ing out between 2-3 fwd PS and GAAP operating margins that are in the 10%+ range up from 3% operating margin now.

Notable Risks:

Supermicro has very poor fundamentals as it must raise cash to scale. Being a commoditized AI server/hardware company, the margins are slim to none. It’s not clear if domesticating supply chains will help SMCI’s margins (it could). SMCI offered a red herring type earnings report as the company’s results got slammed by previous generation GPUs (Hopper, Chinese servers) yet will likely do quite well from incoming Blackwell.

Note: there is no recent analysis on Supermicro as we are looking to add this stock to our portfolio after taking a pause for about a year on the stock. You can find our previous thesis from 2023 on Supermicro here.on Supermicro here.

4. Dell: Strong Initial Sales from Blackwell with 612% Growth in Backlog

Thematic: 8/10
Fundamentals: 7/10
Valuation: 5/10

There are a few key catalysts to keep an eye on for Dell’s growth story. First off, will Dell move from primarily enterprise servers to also supply hyperscalers with AI servers? The current margin profile suggests this may already be happening as Tier 1 hyperscalers demand lower margins than enterprise servers. Meta, xAI and Coreweave are confirmed customers; the question is if the Big 3 follow.

AI factories are a major growth story for Dell – defined as complete systems that bundle PowerEdge AI servers, high-performance storage, intelligent networking, and integrated software/services. There is higher dollar content and higher margins on the storage and networking side for Dell as NVIDIA’s Blackwell GPUs and Dell’s cooling and integration expertise are combined to offer on-site (on-premise) AI servers.

Dell shows a lower thematic rating than peer Supermicro because it has a large Client segment. Dell has a higher rating on fundamentals due to its strong cash flows (a pain point for SMCI) and for its reliable management team, who are experienced at running a profitable company at scale.

Overall Revenue:

Dell reported $23.38 billion in revenue in Q1, a slight <1% beat to estimates as all of its core businesses grew in the quarter.

Revenue growth decelerated to 5.1% YoY in the quarter with Dell forecasting a sharp acceleration in Q2 as it is now rapidly ramping AI server shipments after orders surged in Q1.

For Q2, Dell guided $28.5 to $29.5 billion in revenue, or 15.9% YoY growth at the $29 billion midpoint, which marks a nearly 11-point sequential acceleration. Interestingly, while Q2’s guidance was nearly $4 billion ahead of the consensus estimate for 0.9% growth to $25.26 billion in revenue, Dell opted to maintain its FY26 revenue forecast at $101 to 105 billion.

AI Segment Revenue:

Dell reported surging demand in AI optimized servers in Q1 with orders of $12.1 billion. This outpaces the entirety of last year while representing a 612% sequential increase from $1.7B last quarter. To further compare, the peak quarter for orders last year was $3.6B.

This surge in orders brought Dell’s AI server backlog up to $14.4 billion, up from $4.1 billion in Q4. However, Q1’s AI server shipments were just $1.8 billion, up just 6% YoY and down more than (14%) QoQ. This likely boils down to the timing of Blackwell’s ramp, as Dell projected more than $7 billion in shipments in Q2

This strong AI server shipment forecast contributed to a nearly $4 billion beat for Q2’s guidance. Notably, Dell did not raise its revenue forecast for the year, suggesting that tariff-related impacts may still bite in H2, or that AI server shipments will be lumpy and not be linear from here out.

Earnings:

For Q2, Dell guided for $2.15 to $2.35 in adjusted EPS for growth of 15% at midpoint, marking a slight deceleration from the 17.4% growth reported in Q1.

Q3 and Q4 are expected to see EPS growth decelerate a bit further, with growth of just 10.7% in Q4.

For the full year, Dell slightly raised its FY26 adjusted EPS guidance to $9.40 for 15% growth, up from its prior view for $9.30 for 14% growth.

Dell also slightly hiked its GAAP EPS view for FY26, now seeing $7.99 for 25% growth versus its prior view of $7.85 for 23% growth.

Margins:

GM = 21.1%
GAAP Operating Margin = 5%
Net Margin = 4.1%

Margins are decel'ing which is an issue since AI servers weigh on margins. However, management expects to see ISG improve by $0.5 billion in operating income this quarter on an additional $5.3 billion in revenue – meaning management is sensitive to the importance of operating efficiency.

Cash flow:

Dell is reporting strong cash flow growth – setting itself apart from Supermicro:

Operating cash flow rose 168% YoY to $2.80 billion. OCF margin was 12.0%, up more than 7 points from 4.7% a year ago and more than 9.5 points higher than Q4’ s 2.4% margin.

Free cash flow rose 388% YoY to $2.23 billion, while adjusted free cash flow rose 258% YoY to $2.23 billion. FCF and adjusted FCF margin was 9.5%, a significant improvement from 2.1% and 2.8% a year ago.

Cash, equivalents and investments totaled $9.29 billion, up more than $4 billion QoQ. Debt also rose more than $4 billion QoQ to $28.78 billion.

Valuation:

Dell trades at 0.82 fwd PS and 13.4 fwd PE Ratio. This is at the medium-range of the company’s recent stock history since the AI boom began.

Notable Risks:

Dell is exposed to lower-performing Client markets, which equal higher revenue than its AI segment (ISG). Notably, ISG will likely overtake Client sometime this year in total revenue. Dell’s margins are very low

5. Amphenol: Leading AI Supplier with 134% Growth

Amphenol plays an important role in Nvidia’s NVL72 racks that are shipping now, as the company supplies high-speed copper cables and interconnects. Nvidia’s choice to use copper cabling over optical transceivers resulted in both lower costs and power savings for the NVL72, providing a growth opportunity for Amphenol. Specifically, Amphenol's 12VHPWR PCIe 5.0 power connector was able to eliminate the need for three power connectors with a single power connector.

Unlike other GPU-agnostic players who can realize growth and tailwinds as long as AI capex remains strong, Amphenol is more closely correlated to Nvidia’s NVL72, and its opportunity thus arises squarely from the ramp of the platform and overall shipment volumes. Signs that Nvidia is now quickly ramping NVL72 shipments far ahead of analyst expectations support more growth ahead for Amphenol in the upcoming quarters.

Amphenol’s dollar content per NVL72 rack is expected to be quite high — Evercore ISI estimated last year that Amphenol’s BOM content was in the range of $100,000 to $120,000 per NVL72, or around 3-4% of the server’s value. This represents a fairly large opportunity for Amphenol, especially if Nvidia is scaling shipments to a much larger degree than currently anticipated.

However, Amphenol remains quite highly exposed to slower-moving sectors such as the industrial and automotive sectors, and cash to debt is upside-down due to its focus on M&A to complement growth.

Overall Revenue:

Accelerating AI demand drove Q1’s outperformance, with revenue coming in “much stronger than expected” at 47.7% YoY to $4.81 billion in revenue, accelerating 18 points sequentially.

Organic revenue growth was 33%, accelerating 13 points sequentially. Q2’s growth is now expected to be 38.8%, more than 21 points higher than January’s 17.5% estimate.

Q3’s growth is expected to be 27.0%, approximately 16.5 points higher than in January.

Q4’s growth is expected to be 21.5%, nearly 10 points higher than in January.

AI Related Revenue:

134% in Datacom IT. Amphenol’s orders have grown at 58% YoY for a second consecutive quarter, with growth accelerating sharply over the last few quarters. Putting this together, the nature of Q1’s beat and the strength in datacom at 134% YoY has driven estimates for the next three quarters up by more than $2 billion combined.

Earnings:

Amphenol reported a quite large 21.2% beat on adjusted EPS in Q1, posting $0.63 versus the $0.52 estimate. This represented growth of 57.5% YoY, accelerating from 34.1% growth last quarter.

However, similar to revenue, growth is currently expected to peak in Q1 and decelerate after, though remaining quite strong. For 2025, Amphenol is expected to report 40.8% growth to $2.66 in adjusted EPS, with growth forecast to slow dramatically to the 9% range for both 2026 and 2027, in an indication that 2025 is expected to be the sole strong growth year for the company due to Blackwell’s initial ramp phase

Margins:

Gross Margin = 34%
Operating margin = 21.3%
Net Margin of 15.3%

Amphenol’s margins have been relatively stable over the past four quarters, but the strong growth and increasing contribution from Communications, which is accretive to operating margin, provides some margin tailwinds.

Cash:

Operating cash flow was $764.9 million for a 15.9% margin, down from 18.4% margin in the year ago quarter. OCF margin over the past three years has hovered between the 17% to 20% range, with Q1’s cash flow slightly weaker.

Free cash flow was $580.4 million for a 12.1% margin, down from a 15.5% margin in the year ago quarter. Management expects to have elevated capex again in Q2 to support datacom growth, weighing on FCF.

Valuation:

Amphenol’s valuation is stretched at 6 forward PS and 37 forward PE Ratio, some of the highest in the company’s history.

Risks:

Valuation is the primary risk as the company has a strong AI story yet overall revenue is low given the other, low-growth segments.

Read more in our analysis Amphenol Reports 134% Growth in Datacom IT SegmentAmphenol Reports 134% Growth in Datacom IT Segment

6. Coherent: Lesser-Known Supplier Reporting Inflection in AI-Related Revenue

Coherent is reporting Q4 fiscal year 2025 this quarter

Coherent reported a double beat in Q3 with revenue growth of 24% and EPS growth of 141% YoY. The top line beat was driven by Data Center and Communications revenue growing 46% YoY. While this growth moderated slightly from the prior quarter, Nvidia suppliers should see a meaningful acceleration in the second half of the year.

Analysts have yet to fully factor in this acceleration, but as NVIDIA ramps Blackwell-based systems and scales out its Spectrum-X Ethernet and Quantum-X Infiniband platforms, suppliers of high-speed optical interconnects are likely to see an increase in demand. Coherent, as a key ecosystem partner to NVIDIA in silicon photonics and co-packaged optics (CPO), is well positioned to benefit as hyperscalers upgrade to 800G, 1.6T, and eventually 3.2T.

To refresh your memory, Coherent has many products that participate in the AI-driven datacom transceiver and optical interconnects market. Primarily, the growth story centers around supplying Nvidia with pluggable optical transceivers (400G, 800G, 1.6T) including EML lasers, VSCEL lasers and CW lasers, and emerging CPO technologies for next-generation switches and interconnects.

Coherent is certainly not without competitors, and this is the main risk the company faces. Management is tasked with executing flawlessly in an environment where components may see supply disruptions and must also move quickly to make sure they are first to market to support higher bandwidths. Optical transceivers are at risk of being commoditized as reflected in Coherent’s low margins.

Overall Revenue:

Coherent reported a double beat in Q3 with revenue growth of 24% and EPS growth of 141% YoY. Coherent delivered another quarter of record revenue driven by strong AI data center demand, with revenue rising 4.4% QoQ and 23.9% YoY to $1.50 billion.

This beat the consensus estimate for $1.44 billion by more than 4%, and marks a third straight quarter of >20% revenue growth. For Q4, management guided a wide range for revenue, forecasting $1.425 to $1.575 billion.

At the $1.5 billion midpoint, this represents flat QoQ and 14.5% YoY growth, slightly ahead of estimates for 12.1% growth. Revenue growth estimates for the next two quarters have moved higher since our last Q2 report, from the mid-9% range to double-digit growth through FQ1 2026.

AI Segment Revenue Growth:

The top line beat was driven by Data Center and Communications revenue growing 46% YoY. Networking revenue increased 46% YoY and 10% QoQ to $897 million, or ~60% of revenue.

Notably, growth continues to decelerate from Q1’s 61% print, yet the segment’s growth is much stronger this year compared to last. For the first nine months, networking revenue was $2.48 billion, up 53% YoY.

According to a press release in March, Coherent was the first to release a 400G per lane EML for 1.6T, showing Coherent is working hard to remain a supplier of choice in a highly competitive market. To some extent, indium phosphide capacity is the limiting factor for these technologies, with Coherent stating they expanded capacity rapidly in the current quarter: “In Q3, we once again expanded our capacity both sequentially and year-over-year with year-over-year capacity growing by over 3x.”

Earnings:

Coherent reported a 5.8% EPS beat in Q3 as it benefited from strong margins down the line, reporting $0.91 in EPS. This represented growth of 141% YoY, decelerating from 256% YoY growth in Q1.

For Q4, management offered a wide range for $0.81 to $1.01 in adjusted EPS, with the $0.91 midpoint in-line with estimates. For FY25, Coherent is currently expected to record more than 107% YoY growth to $3.46, though growth is expected to slow to 26.2% YoY to $4.37 in FY26.

Margins:

Q3 GAAP gross margin was 35.2%, expanding nearly 5 points YoY.
GAAP operating margin was 4.8%, up 3 points YoY.

For Q4, management is holding adjusted gross margin guidance steady at 37-39%, while guiding for an 18% adjusted operating margin. Coherent is beginning to close in on its long-term gross margin targets of 40% over the last two quarters, though it still needs to make some considerable progress or drive faster growth in higher-margin products to reach this threshold in fiscal 2026.

Note: Coherent is expected to divest low-margin segments soon which would quickly change its margin profile.

Per our previous writeup:

“The company recently restructured the business to divest the silicon carbide portion, which is also contributing to better margins for next quarter: “So I think you're referring to some of the restructuring that we've taken and the portfolio actions associated with it. And so what I would say is that the actions that were taken in terms of an underutilized assets or underutilized businesses, that benefit is — certainly will contribute to our financials from a gross margin and OpEx perspective, depending on the nature of the actual divestiture.”

Cash:

Operating cash flow was $162.9 million for a 10.9% margin, expanding from a 9.7% margin a year ago. This was the fourth consecutive quarter of a double-digit OCF margin.

Free cash flow was $51.1 million for a 3.4% margin, expanding from a 2% margin a year ago

Valuation:

Similar to Lumentum, Coherent shows room in its bottom line valuation whereas there is less room in the top line valuation. At 21 forward PE ratio, the company is trading at its lowest in two years. At a 2.3 forward PS ratio, it’s closer to the top valuation its traded at in two years at 3 – which seems to be a firm ceiling unless there is a re-rating on the AI story.

Notable Risks:

There are a few competitors Coherent must contend with, its lower-growth segments weigh on the stock. The margins leave a lot to be desired.

Honorable Mentions:

Lesser-known supplier at inflection point, covered on Discovery tier April 29th

We covered a lesser-known supplier that offers components for datacom transceivers and optical interconnects on April 29th. This small-cap company offers differentiated technology that has caught the attention of heavyweight NVIDIA. We’ve been patiently waiting for this company’s EML lasers for 200G to ship, enabling 800G and 1.6T bandwidths. Any progress here will continue into 2026-2027 for 400G data lanes and 3.2T bandwidths.

Read more about our Discovery tier here.

Thermal Management Solutions Provider, covered on Discovery on May 15th

We recently covered a supplier whose importance is expected to increase with each new generation of GPUs and AI accelerators. The company provides thermal management solutions, such as cold plate cooling and immersion cooling to lower the power requirements to AI systems. They also offer high density solutions such as rear door heat exchangers and coolant distribution units (CDUs).

Direct liquid cooling systems, including hybrid versions that combine air and DLC, can result in 40% less power management space and 20% lower cooling costs. When you’re spending nearly $100 billion per year on capex like many Big Tech companies, this matters quite a bit. In addition to thermal management, this company's power solutions include uninterruptable power systems and lithium-ion battery cabinets that supply up to 1500KW and 263KW in a single cabinet.

Read more about our Discovery tier here.

Section 3: AI Software – Strong Fundamentals Yet Valuations are Stretched

There are six stocks in this section ranked #1 to #6 and two honorable mentions

AI software valuations are pointing toward a bubble within a larger, quality trend. We are simply too early for AI software to carry the valuations some are commanding and the evidence is quite clear in the financials when you compare valuations to AI hardware.

AI hardware segments are often growing triple-digits+ and are likely to continue to do so for some time
AI software segments have either dipped below 100% (with major hurdles to resume this growth) or have not surpassed 100% — and yet the valuations are in some cases Covid-era like.

The stocks below make the list but will only make the final cut (added to the portfolio) if we can get the stocks at a reasonable valuation – which is true for the entire list, but there is nothing quite like getting a solid software stock at a reasonable valuation. That is the trade that rules all trades in the tech sector.

1. AppLovin has a Rule of 140 (not a typo)

Thematic: 10/10
Fundamentals: 10/10
Valuation: 2/10

AppLovin easily topped revenue and EPS estimates in Q1, but more importantly, the company is setting up for an additional under-reported catalyst with its web-based ad platform expected to launch its self-serve feature and scale with a wider pool of advertisers as the year progresses.

In addition, the company divested its App segment, which is the gaming assets portfolio, and is now a pureplay ad-tech stock. The high-growth and high-margin advertising business that ignited AppLovin’s strong returns over the past few years is now the company’s sole focus.

You’d be hard pressed to find a stronger stock in terms of fundamentals on the market today. There is plenty of runway left for this stock should the growth of 30%+ coupled with 80%+ gross margins and nearly 40% net margin continue. Consider that EPS grew triple digits this quarter and FY2026 EPS estimates are being revised higher by an astonishing $3.50 in incremental EPS.

Overall Revenue Growth:

AppLovin reported 40.3% YoY revenue growth to $1.48 billion in the first quarter, beating consensus estimates by $100 million. This was AppLovin’s sixth consecutive quarter with revenue growth >35% YoY.

Given the Apps business is being divested, AppLovin will be reporting headline growth in the 60% range that is aligned with its Ads business rather than a mix of both. Consensus revenue growth estimates are much lower and show a sharp deceleration, as these comps still take into account revenue from the Apps segment. Thus, growth rates such as 20% in Q3 do not reflect the true performance of the business.

AI Segment Growth:

Advertising revenue increased 70.9% YoY to $1.16 billion, slowing slightly from 91% in the year-ago quarter. Management said growth was driven by continued enhancements in its AI ad engine, as well as the full quarter impact of its web-based ad solution even coming off the seasonally high e-commerce quarter in Q4.

For Q2, management guided Advertising revenue of $1.195 to $1.215 billion, pointing to 69.5% YoY growth at midpoint, maintaining its hypergrowth phase.

Earnings:

AppLovin’s business model sees a high percentage of its operating income flow through to the bottom line, driving tremendous EPS growth as margins expand.

AppLovin reported massive 149% YoY growth in GAAP EPS to $1.67, outpacing revenue growth by more than 3x.

Q2 EPS is now seen growing 125% YoY to $2.00, before rising to $2.16 in Q3 and exiting the year at $2.46. For FY25, analysts estimate AppLovin will generate $7.80 in EPS, up 72.3% YoY, with FY26 EPS rising 42% to $11.80. This is more than a $3.50 increase for FY26 since February’s $8.27 estimate.

Margins:

Though AppLovin’s top-line growth is quite impressive, margins are where it shines, with gross margin surpassing 80% and operating margin reaching a new high. This combination of strong revenue growth and strong margins is driving exceptional operating leverage with triple-digit earnings growth.

Gross margin expanded 5 points sequentially and more than 9 points YoY to 81.7%. Notably, AppLovin cut its cost of revenue by nearly (9%) YoY, from $294.1 million to $272.2 million, while still driving 40% total revenue growth and 70% advertising growth.
Operating margin remained above 44% for a third straight quarter at 44.7%. To put in perspective how strong these margins are, AppLovin would have a Rule of 40 score of 85% based on Palantir’s definition of revenue growth + operating margin, while Palantir had a score of 83%.
Net margin in Q1 was 38.8%, up more than 16 points YoY.

However, now that the Apps business is divested, the operating margin will skyrocket to 70% range for a Rule of 140 if you assume 70% revenue growth on the Ads business and 70% operating margin. This is unheard of; I do not think we’ve seen this combination before of such high growth and such high profitability. Typically, software startups and public companies are seeking a Rule of 40 and yet AppLovin offers 100-points higher following divesture of the Apps segment.

Cash:

AppLovin’s cash flows are exceptional, with operating and free cash flow margins expanding to new records in Q1. Per the opening remarks: “In the first quarter, we generated $826 million in free cash flow, up a staggering 113% year-over-year. Quarter-over-quarter, our free cash flow grew 19%, representing an impressive 82% flow-through from adjusted EBITDA to free cash flow.”

Operating cash flow rose 112% YoY to $831.7 million for a 56% margin, expanding from a 51.1% margin in Q4 and nearly 19 points higher than 37.1% in the year ago quarter.
Free cash flow rose 113% YoY to $825.7 million for a 55.6% margin, expanding from 50.6% in Q4 and 36.6% in the year ago quarter.

Valuation:

Applovin is trading at 22 forward PS which is at the upper range for this stock, topping at 30 two times (briefly) in the past before retreating as low as 15. The PE Ratio of 40 is similar as it’s well above 3-year and 5-year medians while seeing a brief top at 60-70 before quickly retreating to a low of 27.

Risks:

Of the software stocks, Applovin has fewer risks than the other stocks given its valuation is in typical range. The divesting of the Apps business is bullish but results in tough comps for headline numbers. Investors will want to focus on organic growth the ads business.

You can read more about Applovin in the analysis: “AppLovin Q1: Web-Based Catalyst 2025-2026; App Segment Divested is a Major Plus”AppLovin Q1: Web-Based Catalyst 2025-2026; App Segment Divested is a Major Plus”

2. Oracle: The AI Software Stock No One Saw Coming

Oracle laid out some impressive growth forecasts for fiscal 2026 earlier in June, setting the stage for a significant acceleration in its cloud segment backed by robust AI demand. The recent 4.5 gigawatt agreement with OpenAI for expanded Stargate capacity is a testament to Oracle's aggressive push in the AI cloud market, strengthened by its focus on low-latency, high performance AI.

This massive deal, requiring significant data center expansion, underscores just how elevated demand is for high-performance infrastructure to power advanced AI models. Analysts are closely watching how this mega-deal impacts Oracle's capex strategy and its overall AI growth outlook for the coming fiscal years.

Notably, Cloud IaaS (OCI) growth was guided to accelerate to >70% in FY26 from 50% in FY25. Oracle said this acceleration was supported by “exceptional demand infrastructure services” and non-cancelable RPO bookings.

Overall Revenue Growth:

As a result of the strong forecasted growth in cloud and in RPO, Oracle slightly raised its FY26 revenue target, while management stated they have increased confidence in meeting and possibly exceeding FY27 and FY29 targets.

For FY26, Oracle now expects revenue to be $67 billion for YoY growth of 16.7%, up just $1 billion from its prior guidance for $66 billion. This slight raise corresponds to a 1.7 point topline acceleration, from barely 15% YoY in its original forecast to 16.7% now with the potential for cloud-driven upside now that GPUs are no longer a constraint.

However, the small increase raises some questions about the durability of Oracle’s non-cloud growth given the magnitude of acceleration management sees in the cloud.

Put it this way – if cloud was previously expected to accelerate nine points to 33% YoY ($32.4 billion) in FY26, the new 16 point-plus acceleration guide would raise cloud revenue $1.8 billion higher to $34.2 billion. Thus, the $1 billion full-year hike suggests that Oracle’s non-cloud segments may be flat at best, or decline low-single digits YoY.

AI Revenue Growth:

One of the more impressive forecasts Oracle stated in Q4 was its RPO growth target for FY26. Management stated that RPO was expected to increase more than 100% in the upcoming fiscal year, which would place RPO at well over one-quarter trillion.

During its Q4 report in early June, Oracle projected substantial acceleration in its cloud business in fiscal 2026, fueled by strong AI demand and cloud consumption:

Total cloud growth (IaaS & SaaS) guided to accelerate to >40% in FY26 from 24% in FY25.
Cloud IaaS (OCI) growth guided to accelerate to >70% in FY26 from 50% in FY25. Oracle said this acceleration was supported by “exceptional demand infrastructure services” and non-cancelable RPO bookings.
Oracle Cloud Infrastructure consumption revenue to grow faster than the 62% YoY increase reported in Q4.

In terms of revenue, these growth rates project total cloud revenue rising to at least $34.2 billion, up from $24.4 billion in FY25. Cloud IaaS is projected to rise to at least $17.5 billion increasing from $10.2 billion in FY25. In terms of revenue mix, IaaS would see its share rise quite sharply, from 41% of cloud revenue in FY25 to >50% in FY26.

Oracle’s IaaS growth segment is expected to increase 4.5x by FY28, with the $30 billion deal then kicking in.

As stated above, consensus currently models in $46 billion in IaaS revenue in FY28. For the IaaS segment to increase 4.5x from FY25’s $10.2 billion in revenue, this requires growth at a 65.2% CAGR, or a slight deceleration from >70% YoY in FY26 to >60% YoY in both FY27 and FY28.

Though Oracle is growing off a much smaller cloud base than, say Azure, this represents potentially a 30 point faster growth rate than its hyperscaler peers over the next few years. It’s also representative of a significant reshaping of Oracle’s business model, as this implies IaaS will grow its share of cloud revenue from <18% to nearly 50% in just three years.

The $30 billion annual revenue deal unlocks further upside in FY28 and into FY29, depending on how capacity and revenue ramp. It’s likely to take a couple years for Oracle to scale into the full run rate of the deal, but an additional $5B+ by FY29 could help Oracle easily exceed its targets on persistent cloud momentum.

Earnings:

Oracle reported a nearly 4% beat on the bottom-line, reporting $1.70 in adjusted EPS, rising just 5% YoY. For fiscal 2025, adjusted EPS rose 8% YoY to $6.03.

Adjusted EPS growth is projected to accelerate in fiscal 2026, driven by the top-line acceleration. Q1 EPS is estimated to increase 6.3% YoY and gradually accelerate to 17% YoY by Q4. However, full-year EPS growth estimates of 12.3% lag revenue growth by nearly 4 points, suggesting some margin headwinds may be present throughout the year.

Margins:

Oracle’s margins are solid and have remained quite steady, with only marginal expansion down the line.

FY25 GAAP gross margin was 71%, flat YoY, though gross margin in Q4 was down 3 points YoY to 70%.
FY25 GAAP operating margin expanded 2 points YoY to 41%, strengthening slightly throughout the year from 30% in Q1 to 32% by Q4.
FY25 adjusted operating margin was flat YoY at 44%.
FY25 GAAP net margin followed operating margin, expanding 2 points YoY to 22%.
FY25 adjusted net margin was flat YoY at 30%.

Cash:

Oracle’s liquidity profile suggests that funding aggressive expansion plans, notably for Stargate, will pressure free cash flow through 2026 and potentially into 2027 as well. Capex outpaced operating cash flow for the first time in FY25, sending FCF negative.

Cash, equivalents and short-term investments totaled $10.2 billion, though debt was 9x this at $92.6 billion.
Operating cash flow in Q4 was nearly $6.2 billion for a 39% margin, though free cash flow was more than ($2.9 billion), or an (18%) margin. This is because capex rose 55% QoQ to $9.1 billion.
For FY25, operating cash flow was $20.8 billion for a 36% margin, up 1 point YoY. Free cash flow was ($0.4 billion), for a (1%) margin, down from a 22% margin in FY24 due to Oracle spending $21.2 billion in capex.
For FY26, Oracle guided for capex of >$25 billion, and hinted that actual requirements could be higher, suggesting FCF may be negative again unless operating cash flow growth accelerates from 12% to >25%.

Valuation:

Oracle is trading at 10 forward PS, which is not a valuation we’ve seen from this stock. Typically, it trades in the 5X forward range. It’s anyone’s guess if the company will join AI peers at higher valuations or retreat back to its typical valuation.

The PE Ratio is the same – its 2X higher compared to historic levels at 35 forward PE and we will need more AI-related trading history to determine where the stock eventually settles.

Risks:

No major risks. Valuation could go either way therefore less of a risk and more of a trial period.

You can read more about Oracle in the analysis: “Can Oracle Become the Next $1 Trillion AI Stock?”Can Oracle Become the Next $1 Trillion AI Stock?”

3. Palantir is the AI Bubble Stock

Thematic: 7/10
Fundamentals: 10/10
Valuation: 0/10

Palantir is at an eye-watering valuation – causing many investors with no risk management to come out of the woodwork and cheer the stock at these levels. That may work in many sectors, but it does not work in the tech sector. It would take a significant selloff for our firm to buy Palantir right now as we simply refuse to gamble with our hard-earned money. Don’t hate me, but I actually like Oracle better here than I do Palantir.

If you give me Palantir at a drastically better valuation that matches what best-of-breed cloud stocks can sustain, then I’d happily buy. Until then, we have our attention on other stocks for now.

Overall Revenue Growth:

In Q1, the company reported $884 million in revenue for growth of 39%, up from growth of 36% last quarter and 21% last year. This represents QoQ growth of 7%.

Palantir reported $883.9 million in revenue in Q1, beating estimates by more than $21 million. As stated above, this represents growth of 39%, up from growth of 36% last quarter and up from 21% last year.

On a QoQ basis, Q1 accelerated 7% from Q4. This is an impressive performance given Q1 is typically one of the slowest quarters seasonally.

AI Related Revenue Growth:

Perhaps most importantly, US commercial revenue drove the results, with 71% YoY growth and QoQ growth of 19% for the segment’s first-ever $1 billion annual run rate.

US commercial revenue accelerated from 64% last quarter to 71% YoY this quarter to $255 million, surpassing a $1 billion annualized run rate for the first time on elevated AI demand.

However, the guide for next quarter does indicate Q1 could be the peak with fiscal year growth of 68% guided. Palantir raised its FY25 US commercial growth guidance from 54% YoY to 68% YoY, projecting revenue of $1.178 billion, compared to $457 million in 2023. The raise represents about $100M more than previously expected.

Earnings:

Despite the top-line beat, Palantir met adjusted EPS estimates in the quarter at $0.13, up 68% YoY. GAAP EPS was $0.08, up 100% YoY.

Looking ahead through the rest of FY25, adjusted EPS growth is expected to decelerate, from Q1’s 68% YoY to 20% YoY by Q4. However, estimates have risen over the past three months – Q2’s growth rate has come up 11 points and Q3’s up by 9 points.

For FY25, Palantir is expected to see adjusted EPS growth of nearly 43% YoY to $0.58, before decelerating to 25% growth to $0.73 in FY26.

Margins:

Across the board, Palantir has been expanding its margins. Adjusted EBITDA margin was 45% — which is one of the highest in the tech universe.

GAAP gross margin was 80.4% in Q1, down 1.3 points YoY.
Adjusted gross margin was 82.1%, down more than 1 point YoY.
GAAP operating margin expanded to 19.9%, up more than 7 points YoY.
Adjusted operating margin was 44.2%, up 8.5 points YoY. For Q2, Palantir guided its adjusted operating margin to 43.1%, which would represent a third consecutive quarter above 40% and up nearly 6 points YoY.
GAAP net margin was 24.2%, up more than 7.5 points YoY.
Adjusted net margin was 37.8%, up nearly 8 points YoY.

Cash:

Palantir stands out for its ridiculously strong cash flows, though operating and free cash flow margins moderated quite substantially in Q1 relative to 2H 2024.

Operating cash flow was $310.3 million in Q1 for a margin of 35%, down from 56% in Q4.
Adjusted free cash flow was $370.4 million for a 42% margin, down from a 63% margin in Q4. Palantir raised its adjusted FCF guidance for FY25 from $1.5-1.7 billion to $1.6-1.8 billion, implying an FCF margin of 43.7%.

Cash and equivalents totaled $5.43 billion, while debt was zero.

Valuation:

90 forward PS is a valuation we have not seen since Snowflake traded after its IPO. Today, Snowflake trades at 15 forward PS. Yes, AI deserves a premium. However, at 90X sales means Palantir will not pay back the valuation in revenue in this lifetime as you’re paying a valuation worth 90 years of revenue – and that’s assuming Palantir maintains its current growth rate.

Notable risks:

Valuation, valuation, valuation

You can read more about Palantir in the analysis: “Palantir Stock: Strong Sequential Growth and Strong Underlying Key Metrics.”Palantir Stock: Strong Sequential Growth and Strong Underlying Key Metrics.”

4. Cloudflare: The Upcoming AI Inference Darling

Act 3 refers to the Workers platform, which is the company’s attempt to compete with hyperscalers – but most importantly, it sets up the company well for AI inference at the edge.

When it comes to AI inference-driven revenue, it’s still relatively early in the growth curve. Hyperscalers and model providers only recently began to disclose rapid AI token growth over the last three to four months. However, Q1’s earnings report shows signs of surging AI inference demand filtering into Cloudflare’s platform. For example, Q1 witnessed nearly 4,000% YoY growth in Workers AI inference requests, and more than 1,200% YoY growth in AI Gateway requests.

These growth numbers are off a small base (which is true for all inference statistics for now), yet when you take a company with product-market like Cloudflare and combine it with a massive trend on the verge of taking off – what you get is an irresistible stock that the I/O Fund has a high probability of entering and holding for an extended period of time.

Overall Revenue Growth:

Cloudflare reported a 2% beat in Q1 with revenue increasing 26.5% YoY to $479.1 million. This growth was attributed to the strength of Cloudflare’s largest >$1M and >$5M ARR customer cohorts, which saw record customer additions in the quarter.

Looking ahead to Q2, Cloudflare guided for 24.8% YoY growth to $500 million to $501 million in revenue, representing a 1.7 point sequential deceleration. Analysts are much more optimistic on the quarter, projecting growth above the top end of the range at $501.8 million, or up 25.1% YoY.

Through the rest of fiscal 2025, growth is expected to be essentially flat around 25% YoY. However, management expressed confidence in driving a reacceleration through 2025, opening the door for potential upward surprises driven by AI inference.

However, by maintaining guidance despite the $10M beat in Q1, Cloudflare is essentially saying Q2 could be softer than expected. With that said, Cloudflare tends to be conservative during macro events such as what we saw in April, and thus it could also be a non-issue.

AI Segment Growth:

Cloudflare does not break out its AI segment too closely, rather they share initial growth numbers on the Workers platform. Per our intro: “Q1’s earnings report shows signs of surging AI inference demand filtering into Cloudflare’s platform. For example, Q1 witnessed nearly 4,000% YoY growth in Workers AI inference requests, and more than 1,200% YoY growth in AI Gateway requests.”

Additionally, there are some key metrics that seem to have bottomed and are finding a tiny inflection point:

In Q1, paid customer growth accelerated 2 points sequentially to over 27% YoY, with Cloudflare reporting 250,819 paid customers. Growth has doubled from 13% two years ago, an impressive acceleration given the scale is now reaching a quarter-million paid customers.

Cloudflare also noted it had driven record customer additions in its >$1M and >$5M ARR cohorts in Q1, with growth in both metrics up 48% and 54% YoY, respectively.

Billings growth also accelerated 1 point to 32.8% YoY in Q1, recovering from the 20% range in 2024. Billings activity likely benefitted from QoQ improvements in sales cycles as noted in Q1, as well as stronger deal activity and larger contracts.

Cloudflare’s DBNRR stabilized at 111%, though it has yet to see a strong acceleration like Palantir. Compared to last year, DBNRR is 4 points lower.

RPO also reaccelerated in Q1 to nearly 39% YoY to $1.86 billion, though there has been consistent quarterly variability in growth over the last two years. Current RPO accounted for 66% of total RPO, down from 70% in Q4.

Earnings:

Cloudflare reported adjusted EPS in line with estimates at $0.16 in Q1, for flat YoY growth. Q2 is expected to see adjusted EPS decline mid-single digits YoY, with the full-year on track for just mid-single digit growth with an acceleration expected in Q4.

For Q2, Cloudflare guided for adjusted EPS of $0.18, down from $0.20 in the year ago quarter. Adjusted EPS growth is expected to resume in 2H, with EPS seen exiting the year at $0.23, up 22.6% YoY.

For FY25, Cloudflare maintained its guidance for $0.79 to $0.80, corresponding to growth of approximately 6% YoY. For FY26, analysts are projecting EPS growth to accelerate sharply to 30.3% YoY to $1.04, which likely would require solid improvement in adjusted margins given the topline acceleration is minimal.

Margins:

Margins are the one real blemish for Cloudflare, as the company has regressed on its path to reach GAAP profitability in Q1. Gross margins have been compressing slightly, due to an increase in paid versus free traffic, while operating margins slipped sequentially in Q1.

GAAP gross margin was 75.9% in Q1, down 0.5 points sequentially and 1.6 points YoY. Adjusted gross margin was 77.1%, down 0.5 points sequentially and 2.4 points YoY.
GAAP operating margin was (11.1%) in Q1, down 3.6 points sequentially and a setback from three consecutive quarters of progress towards profitability in the (7%) to (8%) range.
Adjusted operating margin was 11.7%, marginally above guidance for 11.6% and down 2.9 points sequentially. For Q2, Cloudflare guided for adjusted operating margin to improve one point to 12.6%.
GAAP net margin was (8.0%) in Q1, a rather substantial decline from (2.8%) last quarter, driven by the QoQ decline in operating margin. Adjusted net margin was 12.2%, the lowest reported level since Q2 2023.

There is nearly a 23 point gap between GAAP and operating margins. This is driven primarily by high SBC at ~20% of revenue, and it highlights that either SBC would need to move much lower, or costs much lower, in order to drive Cloudflare to a sustainable path to GAAP profitability.

Cash:

Operating cash flow continues to improve, touching a 30% margin in Q1, though free cash flows remain pressured by heightened network capex at 17% of revenue. Cloudflare also raised a substantial amount of capital on June 13, an interesting move given the company still has nearly $2 billion in cash on hand.

Operating cash flow rose more than 98% YoY to $145.8 million, for a 30% margin. This marked a substantial 11 point improvement from a 19% margin a year ago and a 2 point sequential improvement.
However, free cash flow rose 48.6% YoY to $52.6 million, for an 11% margin, up only 2 points YoY.
Cash and investments totaled $1.92 billion, while Cloudflare reported $1.29 billion in convertible debt still outstanding, due in 2026

Valuation:

Cloudflare’s Forward PE ratio is wild at 234 compared and its forward PS ratio of 31 is also a bit steep.

Notable Risks:

GAAP operating margin is weak. Keep an eye on capex costs.

This stock also carries execution risk in both directions as trying to time Cloudflare’s big moment will take immense skill. An investor could buy now and wait … or put that money to work elsewhere and return when there’s more indication that startups, SMBs and enterprises are willing to pay for edge inference. With what we know today, the AI market is primarily driven by Big Tech (i.e., not customers of Cloudflare). Palantir is a great example, it’s finally at a $1B annual run rate and is considered by many the leading AI software stock. Therefore, paying 31 forward PS and risking Cloudflare returns to 15 forward PS (it’s typical range) is not only a valuation risk, but also an execution risk in terms of how long you’d have to hold the stock to return to previous levels, as unlike Palantir, Cloudflare is not showing material AI revenue (yet).

For more information on connecting the dots for Cloudflare’s AI inference thesis, reference our analysis: “Cloudflare: Entering Act 3 to Become A Leader in AI Inference at the Edge.”Cloudflare: Entering Act 3 to Become A Leader in AI Inference at the Edge.”

5. Small Cap Stock with up to 135% Growth, Undervalued Relative to Opportunity

Our team has recently covered a small cap stock on the Discovery tier that we believe could ultimately become a sizable winner. Find more details on our Discovery tier here.

Our team works hard to dig up new ideas, which we publish on the Discovery tier, and this is one of the team’s favorites over the past 2-3 months. Knox has two setups outlined, and they both indicate this stock will see a drop before (potentially) becoming one of our highest performers. Our plan is to enter on any weakness or on a meaningful breakout.

General Synopsis:

Complex reasoning models require an expanded data set, such as dozens of foreign languages or multi-step problems within math and chemistry, for example. This is in contrast to a static data set, which often produces too many hallucinations and can be inaccurate at times. For example, if a Big Tech company only used its proprietary social data to train LLMs, this may not be broad enough to prevent hallucinations since social data is limited in its context and scope. In many cases, additional data points are sought out to improve the accuracy of the model.

In order to move toward general artificial intelligence (AGI), which is defined as AI models that think for themselves similar to a human, companies like Innodata are also tapped for their ability to augment accuracy through reinforcement learning and direct preference optimization, which utilizes subject matter experts to annotate data and to also stress-test the models for accuracy.

This company's competitor is valued at $29 billion compared to the I/O Fund's stock pick having a market cap at $1.5 billion on last year’s reported revenue of $870 million last year. If we assume the competitor is at $1 billion revenue now, that would be a 29X compared to our pick's 6X forward sales.

Speaking of said competitor, there is a potential exodus from the competitor as they received a large funding round from a Big Tech company and this is seen as potential IP risk by other Big Tech companies that previously used the competitor for labeling data sets. This could become a windfall for the I/O Fund’s stock pick. Sign up for Discovery to get our stock trades on this small cap in addition to ongoing coverage.

Current Pro and Advanced Members: To subscribe to Discovery with 30% off, please click here to email usclick here to email us or email premium@io-fund.com and mention code DISCOVERY30.

Discovery is aimed at surfacing new ideas. Rather than being confined to the I/O Fund’s portfolio coverage, Discovery unleashes new ideas to be early with the goal of providing significant edge to tech investors.

Honorable Mentions:

I’m calling these two honorable mentions not for lack of a strong thesis but because it’s a bit lame to include very well-known Mag 7 and FAANG stocks in a Top 15 list. You know these names well, and from here, we will do what we can to help you get a good entry. As of now, valuations are pretty stretched with Meta at the highest levels in the stock’s history.

Microsoft: The Undeniable AI Enterprise Juggernaut
If Nvidia holds the crown in the AI hardware arena, then Microsoft holds the crown in the AI enterprise arena.

Last quarter, Microsoft Azure was the only cloud provider of the three platforms to see growth accelerate, highlighting Microsoft’s impressive earnings for Q3 2025. Not only did Azure separate itself with this 4-point sequential growth acceleration, but it also grew at more than 2x the rate of AWS and 7 points faster than Google Cloud, reaffirming the company’s momentum in the Azure vs AWS vs Google Cloud battle.

Azure benefited as Microsoft brought capacity online faster than expected last quarter, to meet high demand for AI services. AI contributed 16 points of growth in the quarter, compared to 13 points last quarter and 10 points of growth a year ago. Microsoft did not provide an update on AI’s run rate yet said last quarter it had surpassed $13 billion, up 175% YoY.

Valuation:

After Microsoft’s fiscal year adjustment on July 1st, the stock is now trading at 33 forward PE implying at most a 10% move and its forward PS ratio is at 12. The stock typically tops at 13.5 max on Fwd PS and Fwd PE of 37 is a brief top before the stock retreats backward to as low as 23 to 27.

To read more about Microsoft’s recent quarter, including a few key points that are overlooked in terms of how the AI Enterprise juggernaut can extend its lead, reference our free article “What Separates Azure from AWS from Google Cloud” that is then continued on the premium side here.

Meta: Bottom Line Shines; Top Line Taking a Breather
Meta is supposedly no longer in the year of efficiency and is now in the year of AI, according to management. However, the efficiency was remarkable yet again last quarter. Although the company is decelerating from high growth in the past, the company has a big year ahead with ad improvements resulting in higher ad pricing, Meta AI standalone app recently launched (to be monetized next year), and its Llama 4 models, which are open source yet driving important productivity gains internally. Undoubtedly, the company has a lot of data for personalization and a highly engaged audience, marking two competitive advantages over other AI chatbots.

With that said, advertising key metrics decelerated sequentially, supporting further revenue growth deceleration for Q2. Ad impressions increased just 5% YoY, slowing considerably from 2023’s peaks and facing a tougher comp at 20% YoY last Q1. Ad pricing increased 10% YoY, a 4 point acceleration from 6% a year ago.

Valuation:

Meta is flashing warning signals with a Fwd PE ratio of 28 and a Fwd PS Ratio of 9.5. Two years ago, the stock traded at a forward PS ratio of 3 and a forward PE Ratio of 10. On a trailing twelve months basis, the stock is in line with historic trends, yet when a forward is decoupled from historic trends, it means investors are paying dearly for a stock with slowing growth.

Conclusion:

If you made it this far, congratulations! You must take your portfolio as seriously as we do. We have been heads-down attempting to squeak out higher returns this year and every inch of progress can make a big difference when it comes to positioning correctly.

Next up, Advanced Members will get technical setups from Knox in his Quarterly Positions Report with a complete picture of how we plan to enter the stocks listed above. Discovery Members will exclusively get updated technical setups on the three Discovery stocks that made the list.

Our results speak for themselves in terms of how we stack up, yet we continue to strive to move the needle on presenting to you the world’s best AI portfolio. Given the sheer ease in which the market moved off the April lows, we do foresee some volatility in the upcoming quarter. It’s nothing our team won’t be able to handle. Tech earnings officially kick off tomorrow – to say we are ready is an understatement. Let’s go!

Recommended Reading:

2025 Market Outlook: Why Stocks and Bonds Are Signaling More Volatility

Posted on May 2, 2025June 30, 2026 by io-fund

Just three weeks ago, we published the report The Fed Can’t Save This One: Why Bonds May Break The Stock Market. Here we asserted that the next move for the market was likely a bounce.

“While we see the potential for another leg lower in this bear market, we should see a sizable bounce first.”

Since the April 7th low, the S&P 500 is currently +16% higher, and in our target zone of 5600 – 6050. Now that we have reached our target zone for this bounce, we are shifting back into a defensive posture, using this bounce to raise more cash and layer back into our hedges.

U.S. Government bonds are suggesting something is broken as there are no meaningful buyers right now. When growth and inflation decelerate, the safety of a fixed yield in treasury bonds is historically where investors have flocked for 30 years. However, they are not getting bought, which is keeping yields high. Most concerning is that this is happening at the same time we are seeing an alarming deceleration in growth and inflation projections, led by a struggling consumer.  This is not normal behavior, and will continue to put pressure on the economy, as the U.S. still must refinance $9 Trillion of debt this year.

There are two things we are watching closely right now. The first is that if the bond market refuses to go higher, we will remain in a defensive posture, especially if growth and inflation continue to decelerate. The second is the technical setups in the broad markets, which we outline in detail in this report. These technical setups help us to not only manage risk but to also capture the upside. Our 210% cumulative return and 27.6% annualized return has been partly achieved through accurate broad market analysis, such as detailed below.

The 60/40 Stock Portfolio Isn’t Working – Why That’s a Problem

Due to advancements in technology, globalization and demographics, the last thirty years have been marked by a low inflationary environment. This backdrop led to a 30-year bull market in bonds. Bonds thrive when inflation is going down or only going up a small amount. A fixed yield is desirable in this environment and has been for a very long time. This type of secular environment also is the reason investors sought the safety of a fixed yield when prices were dropping sharply, creating the inverse correlation we are all so familiar with between bonds and stocks.

This is clearly shown in the chart below. Note as the PMI for Manufacturing began to drop, signaling a slowdown in economic activity, stocks soon followed, leading to drawdowns between 15% – 57% in the S&P 500. During these periods, you can see how government bonds moved inversely to these drops in both economic activity and stocks.

When growth decelerates, as shown by PMI manufacturing, stocks tend to correct. This pattern has led to bonds going higher every time since the year 2000, as investors seek a safe fixed yield. However, since 2022, this correlation broke and remains broken through early 2025.

This relationship was considered an axiom in portfolio management and even led to the 60/40 portfolio concept for long-term buy and hold investors that many still adhere to. However, something changed in 2021, which has persisted into today, which is also shown in the above chart.

For the first time in over 30 years, growth, stocks and bonds went down together. In 2022, inflation, as measured by the YoY increase in the CPI, rose to levels we had not seen since 1981. An inflationary environment like this, where prices are sharply moving higher, erodes the value of a fixed yield. Investors tend to sell bonds when inflation is high or expected to move higher.

U.S. Inflation, as measured by the YoY CPI, peaked at 9.1% in June of 2022, the highest reading since 1981. Since then, inflation has subsided, which should be beneficial to bonds.

The current narrative is that what happened in 2022 was a one-off issue, due to a meaningful disruption of the supply chains, as well as excess money pumped directly into global economies as a reaction to the disastrous COVID lockdown policies due to and everything should return to normal. This is reflected in the sharp drop in the CPI, which just posted a 2.4% reading, down significantly from the 9.1% peak in June of 2022.

While still off from the FED’s 2% target, the sharp decrease in inflation should support the long-bond trade. However, as stated before, bonds continue to test critical support, unable to get a meaningful bid.

Signs the Consumer is Under Pressure

The other element that dictates bond yields is economic growth. As shown above, when growth starts to fade and the economy weakens, a safe, fixed yield tends to be what investors flock to. Recent data suggests that the economy is fading, which is being led by a struggling consumer.

The U.S. Index of Consumer Sentiment just posted a reading of 52.

Consumer Sentiment is worse today than in 2008 and 2009 and was barely surpassed by the COVID panic. Source: YChartsYCharts

For reference, this is the type of reading we tend to see when in a recession. This is lower than any period in 2008 – 2009 and was surpassed at the COVID low with a reading of 50. The consumer feels horrible about the economy and their prospects in it, more so than some of the worst moments in modern markets.

One of the best pieces of data to show how tough it is for the average consumer can be found in recent Buy-Now-Pay-Later (BNPL) loans. These loans were typically designed for discretionary spending; however, according to LendingTree, 25% of all BNPL loans are being used to buy groceries. Furthermore, 41% of respondents have been late on their BNPL loans in the last year, up from 34% last year.

Keep in mind, the interest on some of these BNPL loans can be as high as 36%, depending on the creditworthiness of the borrower. These are not loans one wants to take on, especially for groceries, which signals the levels of desperation in pockets of the economy.

The same can be seen with credit cards. There is an alarming rise in delinquency payments that are 90 days or more past due, which recently reached a 14-year high and are still climbing.

With the potential of tariffs looming, we could see more pressure being put on the consumer in the near future. The Yale University Budget Lab recently announced that they estimate the cost of increased tariffs to the average American household will be an additional $3,800 this year, which is the equivalent of a 2.3% rise in prices.

What This Should Mean for Bonds

Consumers continue to exhibit signs of struggle, which are starting to show up in key earnings reports. For example, Walmart sees per share profit over the next year coming in as much as 27 cents below analyst projections. This realization sent company shares down more than 6% in midday trading. 

We are now seeing clear signals that growth is expected to slow down, as the consensus is expecting a recession. JPMorgan is now suggesting a 60% chance of recession in 2025 and that U.S. real GDP will likely decline in the second half of 2025.  This is all happening in a very tough to model environment with chaotic levels of uncertainty.

Yet, with inflation coming down, a struggling consumer, and increased expectations of a global recession, U.S. government bonds, the tried-and-true haven for this type of environment, are still not finding any buyers.

This is not normal market behavior. If we truly are seeing the correlation between bonds and stocks breaking, it will be a major inflection point in market dynamics. This will force proven risk models to be revised in real time. It is still too early to call, but since our last report, the correlation between stocks and bonds remains concerning, suggesting something larger is playing out

With $9 Trillion in debt to refinance, the lower bonds go, the higher yields will go until we find buyers. This means we will have to borrow just to service this debt. Considering that we now spend more on debt than defense, this would be a shock to both the economy and the stock market. If the bond market goes into a disorderly selloff, which is eventually what happens when it does not believe a country can pay off its debts without inflation, we could see the Federal Reserve have no choice but to step in to perform some type of yield curve control for the first time since 1941.

Levels and Technical Setups to Watch for the S&P 500

Anyone who has been following the I/O Fund’s broad market analysis over the last 6 months should not be losing sleep over the current bout of volatility. We offered consistent warnings as far back as October of last year in our report titled, Nvidia, Mag 7 Flash Warning Signs For Stocks.

“The warning signs are high, and my firm remains defensive until these signals reverse, or the market corrects.”

Following this analysis, we moved to 50% cash at the start of the year and even up to a 100% hedge position in February. Preparing our research members for this in weekly webinars was key as the market proceeded to retrace nearly all the bull market gains from 2024, officially entering bear market territory

However, in early April, we began removing our hedges and buying targeted A.I. stocks for the coming bounce. How the market corrects after this bounce is over will be telling on what is to follow. There are two scenarios that I am currently tracking:

Red: This is my primary expectation and what we are game planning around. This bounce is a correction within a larger downtrend. Once this bounce completes, the market should drop in a more direct 5-wave pattern. We would then see a retest of the April lows, and likely head toward the 4655 – 4335 region, which would set up a buyable low.
Green: This count would have us completing a larger correction within a bigger uptrend. If the coming drop is a messy/3-wave pattern that makes a higher low, we could be setting up for one more swing high into later this year, with targets between 6300 – 6500.

The most likely path for the S&P 500. The current bounce is coming to an end. How we correct from here will determine the rest of 2025.

If we zoom in, the bounce appears to have more room to run. The pattern is pointing to the 5700 – 5800 region, which should hit no later than mid-next week.

We are in the final swing of the April 2025 bounce, which is targeting the 5700 region.

Regarding the current bounce, there are warning signs that have us shifting into a more defensive posture. For one, several major indexes, which have a history of leading the broad market, are not joining the S&P 500 in this final move higher. Transportation stocks, Small Caps as well as my Financial Conditions index are all making lower highs while the S&P 500 pushed higher.

Key markets are not participating in the last swing of the April 2025 bounce. These markets tend to lead, suggesting that the bounce is running on fumes.

Seeing these divergences on a larger scale was one of several warnings the I/O Fund used to jump into a defensive posture early this year. We are now seeing the same patterns develop on a smaller time scale, which has us maintaining a cautious stance.

Levels and Technical Setups to Watch for the Bonds

If we look at TLT, the ETF that tracks long dated government bonds, it is flat to down since the S&P 500 topped in February. Furthermore, the pattern appears to be testing the $85 – $82 support region. If this region breaks, we should see TLT drop to $71 – $58, pushing yields well over 5% and past their 2022 high. If this does play out, it should be the last drop before a multi-month bounce takes place.

On the other hand, if TLT can hold the $95 – $82 support region, it will need to breakout over $97.50 to confirm that the low is in for bonds. This would set up a multi-month relief rally into the +$100 region. This would be the ideal scenario, as it would suggest that the correlation between bonds and stocks is realigning. It would also suggest that the bond market, in light of all the problems the U.S. treasury market is facing, is willing to look past this due to the growing concerns with economic growth.

The two most likely Elliott Wave counts for TLT. If we break below $82, then rates will spike to new highs. This will be a problem for equities.

Conclusion:

Uncertainty filtering into earnings, a weak consumer, growth slowing down, coupled with bonds not providing the much-needed counter relief they historically provide, are signs that this market has not found its footing yet.

Most certainly, the tech sector has many years of exciting developments ahead of it, especially in AI – an area where our firm has consistently been early and will continue to be. However, macro is in the driver’s seat and takes precedence for our investment strategy in the near-term. We will remain defensive until we get signs that a low is in, or we hit the targets outline in the next drop. When we do resume buying, it’s not unheard of to see a dozen or more trade alerts in one week.

If you went into this sell-off fully invested without any risk management plan, or if you are sitting on outsized losses and not sure what to do, we encourage you to attend our upcoming weekly webinar for premium members. Next Thursday, April 17th, at 4:30 ET. In this upcoming webinar, we will discuss our game plan regarding the remainder of 2025. We will list buy targets for great AI names as well as go over how we plan to raise cash and further hedge our portfolio if this bear market continues into 2026.

The I/O Fund is a leading tech portfolio with annualized return of 27.6% — which would rank us as #2 in the United States if we were a hedge fund. Learn more here.Learn more here.

Recommended Reading:

Essentials Report, April 2025

Posted on April 14, 2025June 30, 2026 by io-fund

We recently published a free article that outlines the major risks this market currently faces. We also provided broad market analysis on the two most likely paths this market might take. For those interested, we encourage you to read it herehere.

Regarding the broad market, in our last report, we stated that

“The line in the sand is 5400… If the market decides to break below 5400 in direct fashion without a bounce, I think it is reasonable to expect a more direct drop to 5200 – 4800.”The line in the sand is 5400… If the market decides to break below 5400 in direct fashion without a bounce, I think it is reasonable to expect a more direct drop to 5200 – 4800.”

We found a low, so far, in the 4800 region, as the market is now staging a bounce. With sentiment readings at historic lows, if the market is going to push lower in a bigger way, it will need to reset sentiment and bring investors back into the markets. This further supports a bounce, which we believe has already started. There are two basic paths I’m tracking over the short-term time frame:

Blue – We have started the expected bounce, which should take us to at least 5635 and potentially to the 6050 region. I think we will see some weakness this week that should hold over 4980 SPX. If this level holds, we should see the bounce continue to our targets.
Once we get to the target region overhead, risk will be elevated. How we correct from there will be crucial, which will determine if we are heading below 4000 SPX, or if we are setting up for a move to new all-time highs.
Red – Any further weakness breaks below 4980 SPX and continues lower. In this instance, I will be targeting the 4700 – 4546 to complete this leg of the drop. This should be the last swing lower that will set the stage for a multi-week bounce back into our overhead target zone.

As stated in the last report, we reserve regular broad market updates for our Advanced Members. However, during times of volatility, which could lead to a meaningful inflection point for investors, we want all our members to have the proper context so that they can risk manage their positions.

If you are interested in a day-by-day update on both broad market risk, and how the I/O Fund manages market volatility in real-time, please consider our Advanced Tier. We are offering a 30% discount to all Essentials Members – please contact support@io-fund.com for details.. We are offering a 30% discount to all Essentials Members – please contact support@io-fund.com for detailssupport@io-fund.com for details.

Nvidia (NVDA)

The bounce in NVDA looks a lot like the S&P 500 overhead – weakness into this week that makes a higher low, then a more direct push into the $116 – $127 region. The drop looks incomplete, and there are two scenarios I’m tracking on what could potentially happen after this bounce completes:

Blue – This bounce will fail to make a new high, and the final drop that follows will complete a very long correction in the $70 region. Once the coming bounce completes, the drop that follows needs to be a messy/3 wave move for confirmation. In other words, we do not want to see a direct drop with bounces.
Red – This scenario should look identical to the blue scenario – a bounce into the $116 – $127 region. However, once this bounce completes, we’ll see a more direct drop, signaling that we are setting up for a move to the $60 region.

Taiwan Semiconductor (TSM)

TSM has a similar setup as NVDA and the S&P 500 above, and is setting up for a big bounce, which has either already started or will start after one more slight low. We expect TSM to take us back to the $187 – $215 region on this bounce. Like with all the equity positions we track, once we get into the target zone, risk will be elevated.

We will not know if the coming bounce will be a lower high in an even larger correction, or a pause on our way to new highs. Based on the mounting risks, we may be looking to reduce risk in TSM and many other positions on this bounce.

Bitcoin (BTCUSD)

Bitcoin is moving in a different path than the equity markets. Bitcoin now has all waves in place to suggest this correction is over. However, I do believe that the pattern best fits with one more slight low to the $74,000 – $69,000 region. If this drop lower happens, it should be on less momentum and less volume than prior drops. This will signal the final 5th wave lower is in place, which should then complete the larger correction.

If instead, we can see price break over $88,500, then the odds will favor the correction being over. It will be a series of steps, but the larger swing, which we have been anticipating for many months, should take us into the $120,000, at minimum. If this plays out, we will greatly reduce our Bitcoin exposure and continue to log meaningful gains.

Recommended Reading:

Essentials Report, March 2025

Posted on March 31, 2025June 30, 2026 by io-fund

Broad Market

The I/O Fund uses many tools to manage risk in our all-tech portfolio. One of these methods is monitoring broad markets to gauge the health of a trend. For example, in early January and February, we kept beating the drum with our Advanced members that the S&P 500 is making a higher high without most of the Mag 7, the NASDAQ-100, Small Caps, and Semiconductors. Divergences like this tend to signal weakness ahead.

We used this type of analysis to warn our Advanced members that we were raising high levels of cash, as well as hedging our portfolio at the first sign of volatility. This allowed us to mitigate the drawdown over the last month, while having cash on hand to buy some great AI stocks at beaten down levels.

While we reserve regular broad market updates and webinars for the Advanced tier, we do at times open our broad market analysis to all tiers when we believe that we are at a potential inflection point.

Regarding the broad market, we think that we are due for a bounce over the coming weeks for a few reasons. The primary reason is sentiment. The AAII is a weekly survey that dates to the 1970s. Every week they ask retail investors where they think the market will be in the future. It has a remarkable record of gauging sentiment as a contrarian indicator.

Over the last 5 weeks, we have seen some of the most bearish consecutive readings in the survey’s history. The percentage of bearish readings were 100% or 99% for the first 4 weeks, with a 97% print this week. This level of consecutive, extreme bearish sentiment rivals the COVID lows, the 2022 lows and even the 2009 lows.

Furthermore, short interest on US stocks has risen to the highest level since the COVID panic. Not only is sentiment abysmal right now, but it appears that investors are now loading onto the short side of the market.

We are not making predications, only presenting sentiment extremes, which historically lead to an unwind. The market tends to move in the direction that will hurt the most people, and right now that level is up. This data supports higher level from here; however, we are also prepared in case this bounce does not materialize.

Regarding the S&P 500, the line in the sand is 5400. If any further weakness holds this level, I think it is reasonable to expect 5800 – 6050 in SPX over the coming weeks. If this bounce can break above 6050, then the odds increase that we can see 6300 in the coming weeks.

Our game plan is to continue to raise cash, and layer back into our hedges on any additional strength. Even if we see a push to 6300, we will follow this plan, as this will likely be the final swing before a relatively large bout of volatility is realized, if it hasn’t already started.

If the market decides to break below 5400 in direct fashion without a bounce, I think it is reasonable to expect a more direct drop to 5200 – 4800. So, while contrarian sentiment readings support a short covering rally in coming weeks, this does not mean that this will manifest. Hopefully, the above levels can help you manage risk as the market chooses a direction.

Nvidia (NVDA)

The evidence continues to mount that NVDA could see a move to sub-$100 in the coming weeks. While the next move will likely be a bounce to $128 – $135, this appears to be a correction in a larger move lower. My final target for NVDA is $95 – $83, at which we will start accumulating again.

For this to manifest, we need to see any further strength hold under $135 and then turn lower. If we are going to avoid a lower low, any further strength cannot exceed over $135. Over this level will start supporting a push to new highs in the coming months.

Let’s say we do not see a bigger bounce from here. Then a sustained break below $110.90 suggests that we are heading directly to the targets zone from here.

Taiwan Semiconductor (TSM)

TSM ‘s drop has gone lower than I wanted to see. This does not mean that we can’t see a push to new highs from here, but it does increase the risk that the next bounce will be a lower high within a larger correction.

Regarding the next bounce, note how TSM is making a new low with less volume and less momentum. This appears to be the final push in this leg of the correction. The coming bounce should get us into the $189 – $203 region. If we are going to break to new highs, we need to push over the $205 region.

The pattern that has unfolded since the August 2024 low is quite weak and overlapping. Because of this, if we do see a push to new highs, it would likely be the final swing higher before a larger correction unfolds. So, any additional strength from here should be properly risk managed, considering.

Bitcoin (BTCUSD)

We began accumulating Bitcoin in early 2023. Since then, we have offered 12 buy alerts ranging from $26,000 – $62,000. However, since November of last year, we announced that we are going to begin to take gains and sold more than half of our position between $80,500 – $104,000. We recently added some of this back to play the possible next swing higher.

Bitcoin’s pattern appears to be incomplete and suggests that one more swing to the $120,000+ region is the most likely. The current bounce that we are seeing should take us to $96,000 – $101,000. Once we get to this region, we will need to be on guard for a reversal. If we do reverse from this zone, we could see a larger drop into the $60,000 region before finding a low. If we are going to push to new highs, we must take out $101,000 with expanding volume.

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Essentials Key Articles: Three Stock Picks

Posted on March 4, 2025June 30, 2026 by io-fund

Our Essentials plan offers three stocks that are actively managed. For those who are new to tech investing, this plan offers an introductory level as mastering a few stocks before building a larger portfolio is a productive way to become acquainted with the world's most valuable and rewarding industry. As you know, tech can be volatile, and these stocks help to balance risk/reward in this volatile industry.

What is listed below is the most pertinent analysis for becoming acquainted with these three stocks.

This list will be updated and refreshed when positions are added or removed. Please check back often for updates!

Quarterly Updates

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Bitcoin: Setting Up for a Strong 2024

Bitcoin: Setting Up for a Strong 2024

Last updated on 05/20/2025Last updated on 05/20/2025

Nvidia and Bitcoin Update

Posted on December 18, 2024June 30, 2026 by io-fund

Nvidia is breaking support, while also strongly diverging from the broad market. If this level fails, the next level will be our first buy spot around $126.

Bitcoin is extending the 3rd wave of 5. We're not chasing this. Our game plan remains the same – buy the 4th wave drop and ride the 5th wave to new highs. Then sell most of it. The only thing that has changed is the 4th wave target – now, $90K – $80K.

Advanced Signals Members receive in-depth technical analysis from our Portfolio Manager, Knox Ridley. Learn more here.here.

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Positions Update: Nvidia, Broadcom, and Bitcoin

Posted on August 27, 2024June 30, 2026 by io-fund

Nvidia (NVDA)

We warned our readers about the coming volatility in Nvidia. We sold ¼ of our position at $129 in June, as a result. However, we also stated that the drop is likely only a 4th wave in an ongoing 5 wave uptrend. So, we sent out several buy alerts for NVDA between $118 – $105 in July – August. We are now over 25% higher from our last buy alert and may reduce risk again due to valuation concerns as well as NVDA being in a risky technical spot.

As long as NVDA holds over $118, we can see a continued push into the low $130s. However, below $118, and we should see volatility return. If this does happen, $103 is the line in the sand. If we can hold this and turn higher, we will be targeting between $155 – $176 into October. Below $103 and we will set up a new buy plan to get more NVDA below $100.

Broadcom (AVGO)

AVGO had a lower drawdown than most AI stocks, which shows its strength. The pattern, as you can see, is clearly a 3 wave move down from the recent high. This tends to suggest a correction within a larger uptrend. As long as we hold over $142, I’m expecting a push to the low $200s next.

Bitcoin (BTCUSD)

Bitcoin appears to have completed a correction within a larger uptrend. As long as we can hold over $56,000, I’m expecting us to push into the low $80,000 range next. This is where we will begin taking gains after nearly 2 years of buying at key corrections.

We recently discussed an emerging ad-tech AI leader in our Advanced Market Signals Tier. Our proprietary custom-built screeners identified this stock. The company witnessed a strong acceleration in growth and margins due to its AI-powered advertising engine. To read the article, upgrade here.here.

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