Taiwan Semiconductor (NYSE: TSM) recently announced fiscal Q3 earnings, stating its longer-term AI revenue outlook is stronger than anticipated. The company reported record Q3 revenue of $33.1 billion, which was up by a solid 40.8% YoY and 10.1% sequentially.  

Over the last few months, the stock has surged as it’s up 50% since early June. At the time, we covered the stock in the article “Taiwan Semiconductor Stock: AI Growth Amid Geopolitical Risk”, we provided a scenario that could take the stock toward the $300s: “If we see the next drop take the form of a 3-wave drop that holds over $146, then we could be setting up for a rally toward the $300s.” At time of writing, the stock was at $203 and touched $304 on October 15th.  

For Taiwan Semiconductor (TSMC), the outlook is two-fold. On one hand, TSMC is deepening 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. 

Yet, on the other hand, many pundits have been asking – are we in an AI bubble? While AI leaders, related suppliers and strong R&D teams march onward with exceptional earnings reports, ongoing deal announcements and provide strong commentary that AI demand greatly outstrips supply – investors are left wondering what the true value is for the outsized growth. They say a picture is worth a thousand words and TSMC’s valuation chart certainly fits that description: 

Source: YChartsYCharts

Although no risk management plan will be entirely error-free, our firm has an outstanding 5-year record of handling the tech sector’s inevitable volatility. Whether it’s the trade plan we provided for free on TSM to our stock newsletter subscribers or the weekly trade alerts and webinars we offer behind our paywall on dozens of lesser-known AI stocks – we always have a plan as we seek to maximize the upside, while protecting to the downside.  

Below, we discuss the key items to track whether TSMC’s moat is intact – even as Intel increasingly becomes a United States darling with $11B in funding – plus not-to-miss highlights from the most recent earnings report. Last, we won’t leave you hanging with a note on how we managed our position after the strong run-up in June. 

TSMC Reports Record Q3 Revenue Growth of 40.8% on Surging AI Chip Demand

• TSMC revenue beat management guidance by 2.2% primarily due to robust AI-related demand. 
• Riding strong AI chip demand, TSMC once again boosts its full-year revenue growth guidance by 5 percentage points. 

TSMC reported a record Q3 revenue of $33.1 billion, up 40.8% YoY and 10.1% sequentially. The growth was primarily driven by strong demand for its leading process technologies (including 3nm, 5nm, and 7nm process nodes) due to the continuing demand for AI and high-performance computing chips.

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TSMC guided Q4 revenue of $32.2 billion to $33.4 billion, representing YoY growth of 22% and down (-0.9%) sequentially. Although management emphasizes strong AI-related demand, the guide shows a break in strong QoQ HPC revenue growth (more on this below). 

TSMC’s Q3 revenue rose 40.8% year-over-year, driven by strong AI and high-performance chip demand.

TSMC boosted 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.   

Management sounded very optimistic during the Q3 earnings call about long-term AI growth opportunities. As discussed below, AI momentum is stronger than expected. The growing adoption of AI consumer models is driving strong demand for AI chips. Similarly, enterprise AI demand is strong, and the rising sovereign AI opportunity will become another strong growth driver.

TSMC: AI Accelerator Growth to Hit Mid-40% CAGR by 2029

Management commentary suggested the chipmaker’s AI outlook through 2029 may be revised higher than the previously-guided mid-40% CAGR, though TSMC declined to provide an updated figure, opting to hold off until early 2026: 

“AI demand actually continues to be very strong, [it's] stronger than we thought 3 months ago, okay? So in today's situation, we have talked to customers and then we talk to customers' customer. 

So the CAGR we previously we announced is about mid-40s. It's [still] a little bit better than that. We will update you probably in beginning of next year so we have a more clear picture. Today, the [numbers] are insane.” 

TSMC Reports Softer HPC Growth After Historic Q2 Gains

TSMC reported a softer QoQ increase in HPC revenue in Q3 after the chipmaker posted its largest sequential growth in Q2 at nearly $3 billion. Q3 saw sequential growth of just over ~$800 million in USD terms, or ~5% QoQ, versus over 20% QoQ growth seen in Q2. However, Q3’s USD-visible growth continued to be inflated by forex, as HPC revenue in NTD was approximately flat QoQ at ~NT$564 billion, versus over 13% growth in Q2.

However, upon looking closer, HPC also saw its percentage of total revenue decline three points from Q2 to Q3, from 60% of total revenue to 57%. Meanwhile, smartphone revenue came in quite strong, gaining three points in total revenue to 30% share as revenue surged nearly 23% QoQ to $9.9 billion.

The softness in HPC revenue may stem from the upcoming platform shift to Nvidia’s Rubin architecture, which relies on a customized 3nm node, N3P, whereas Blackwell relies on TSMC’s N4P process, a customized 5nm node. As you can see in the chart below, TSMC reported a decline in HPC QoQ and YoY revenue at the time that Nvidia’s previous generation Hopper began to ship around Q1 2023. The decline persisted for a few quarters before TSMC resumed very strong QoQ growth in early 2024.  

HPC revenue grew 57% YoY and 5% QoQ in Q3 2025, easing from record sequential gains in Q2 as demand pauses ahead of Nvidia’s Rubin ramp.

Nvidia’s upcoming Rubin generation is slated to be released in the second half of 2026 as six variations entered trial production in August. According to CFO Collette Kress, "The chips of the Rubin platform are in the fab. The Vera CPU, Rubin GPU, CX9 Super NIC, NVLink 144 scale-up switch, Spectrum X scale-out and scale-across switch, and the silicon photonics processor [for co-packages optics]. Rubin remains on schedule for volume production next year.” 

According to Tom’s Hardware, Nvidia and its partners have “successfully created the photomasks and put Nvidia's Rubin GPU, Vera CPU, and various scale-up and scale-out switching ASICs to production.” The article states that Nvidia is now awaiting them to verify performance, power and other criteria.  

Although TSMC serves many high-profile customers in its HPC segment, such as AMD, Broadcom and Intel, it goes without saying that Nvidia is the heavyweight driving the larger swings in this segment as Nvidia has 10X AI revenue in the $200B range compared to second-place Broadcom in the $20B-ish range. As Tom’s Hardware estimates, it could take 9-12 months or longer for Rubin to enter production.  

Meanwhile, TSMC will likely report a lull in the HPC segment between the Blackwell and Rubin generations as Nvidia represents the lion’s share of this segment. 

TSMC’s Q3 EPS Surges 50.5% Year-over-Year, Beating Estimates by Over 12%

As much as TSMC is a top-line story, it is equally a bottom-line story. The company’s 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. Due to TSMC’s economies of scale, the margin dilution from overseas fab expansion is expected to be 1%-2% in 2025, lower than their initial estimate of 2% to 3%.

TSMC’s Q3 EPS rose 50.5% year-over-year to $2.92, marking its strongest beat in two years and exceeding analyst estimates by 12.3%, driven by cost efficiency and economies of scale.

TSMC Stock Trades at Very High Valuation 

Despite TSMC’s strong bottom line growth, the stock trades at one of the highest bottom line valuations since the AI boom began. As visible below, even the strong fiscal Q3 EPS beat of 12.3 points and strong forward EPS guide is not making a dent in the stretched valuation.  

Source: YChartsYCharts 

The AI trade has been particularly hard to nail on valuations. For example, we see some stocks such as Palantir trading as high as 100 forward PS, there are long-standing stocks like Broadcom trading higher than it ever has in its history and it seems there are new deals being announced every day followed by 20%+ pops. 

Regarding TSM, it’s up 290% since early 2023 while the Nasdaq is up 127% and market favorites like Apple are up 98%. There is no denying that TSMC has been as strong performer as it’s the common denominator across the AI accelerator supply chain.  

Below we look at the following to determine how to approach the combination of a strong AI stock with a high valuation:

• The top reason that TSMC has seen strong price action and what must happen for the strong price action to continue 
• How to weigh the United States providing more funding to Intel (to date) compared to TSMC 
• A new trade setup for TSM now that our original trade plan has played out as described last June

TSMC Strengthens Pricing Power as GPUs Transition to Advanced 3nm and 2nm Nodes

TSMC’s impressive price performance reflects many factors, but at its core, it comes down to the company’s unmatched pricing power in the AI ecosystem. As we had discussed in our previous newsletter on TSMC, Taiwan Semiconductor Stock: AI Growth Amid Geopolitical Risk, the chipmaker is the common denominator to essentially all mega cap stocks’ AI strategies, and the company is deepening its moat with more advanced nodes, such as N2 and A16.  

As chips progress to these more advanced nodes, such as Nvidia’s Rubin moving to 3nm and AMD now building CPUs on 2nm, TSMC stands to benefit from increased pricing power. This is because wafers at these new and upcoming nodes carry significant premiums versus the prior node, accounting for substantial increases in performance or power efficiency.  

Pricing for TSMC’s 3nm node was originally pegged by analysts at ~$18,000 per wafer at the start of 2025, before rising just over 10% to $20,000 by September, per reports. This would give the 2nm node a ~50% premium with its reported pricing at $30,000 per wafer.  

Now, reports claim that supply chain sources suggest 3nm pricing is closer to $25,000 to $27,000 per wafer, a 50% uplift from the start of the year. This is important for TSMC as this process underpins Nvidia’s Rubin, which is expected to see shipments of ~5.7 million units next year per JPMorgan. Assuming this pricing stands, this could provide a meaningful tailwind to TSMC’s AI revenue as Rubin ramps, though it would shrink the premium gap with 2nm to just 12-20%.   

TSMC Strong Margins Support Strong Pricing Power 

• Margins continue to expand due to cost controls, higher capacity utilization rates, economies of scale, and better price negotiation with customers and suppliers.  
• Operating margin crosses 50% in Q3. 
• Net income grew by 50.3% YoY. 

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. 

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.  

At the same time, it was partially offset by dilution from overseas fab and unfavorable foreign exchange rates. Management expects gross margin to improve 50 basis points further sequentially and 100 basis points YoY in Q4 to 60% with a boost from favorable foreign exchange rates next quarter. 

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. TSMC beat its operating margin guidance by a solid 410 basis points. Management Q4 guide is 50%. 

TSMC’s operating margin climbed to 50.6% in Q3 2024, up 310 basis points year-over-year, reflecting strong cost control, operating leverage, and continued AI-driven demand.

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.  

Risks: China, Margins following Onshoring and Intel 

As we look into the future, there are puts and takes to onshoring. Last Friday, TSM and Nvidia announced that the first US-made Blackwell wafer was produced at TSM’s Phoenix fab, marking an important milestone in building domestic supply chains for advanced chip production. However, this will mark a new test for TSMC’s pricing power as AMD CEO Lisa Su has stated that US-made chips will be between 5% to 20% more expensive than Taiwan-made chips, with rumors that US chips could be as much as 30% more expensive. While bringing this level of capacity to Arizona could provide a strong tailwind for revenue over the next handful of years, TSMC will have to prove it can maintain strong margins should US-made chips continue to command a premium versus Taiwanese chips. 

Although Intel has largely been written off, given it has nowhere near the IP as TSMC on advanced nodes, it’s important to note that Intel is seeing outsized support from the United States with $11.1 billion in funding compared to TSMC’s $11.6 billion despite the company being the market leader in the manufacturing of most advanced chips (so far).  

Broadly understood yet important to note, geopolitical tensions related to China could negatively affect the stock. The company has been reducing this risk by setting up fabs outside of Taiwan. However, it will dilute margins, since the cost of setting up fabs and operating fabs in the US is higher than in Taiwan. 

TSMC’s Technicals Overview: 

In our last report in June, we stated that “If we see the next drop take the form of a 3-wave drop that holds over $146, then we could be setting up for a rally toward the $300s.” 

This is exactly what happened, as we only saw a dip that tested $224, in what was obviously 3-wave move. TSM then pressed toward $309, and starting to turn lower. 

Considering that we saw TSM pushing toward our target zone on decelerating volume and momentum, it was apparent that we were in some type of 5th wave move, which is the final swing in a trend. There are two scenarios that make the most sense based solely on the price action. 

• Blue – We hit the lower bounds of a topping zone between $309 – $340. If TSM can hold $264, we can see another swing into the upper regions of this topping zone in the coming weeks – months. However, if this push to new highs is accompanied with a continued pattern of lower volume and momentum, then the odds will increase that a bigger correction will likely follow.
• Green – We have completed wave 5 of 3, which would put us in a 4th wave correction. We should break below $264, which will invalidate the blue count above. This larger 4th wave should see $243 – $227, then turn toward the $378 – $420 region to complete the large 5 wave pattern that started on the April low. We cannot break below $227, if this plays out.  

Conclusion: 

The I/O Fund often weighs stocks through an either/or lens. Today’s question: own TSMC at a valuation it hasn’t proven it can sustain—or Nvidia, as it moves into volume shipments of its Blackwell and Blackwell Ultra AI systems? 

We’ve recently chosen to stay on the sidelines with TSMC, but not on AI. We remain heavily invested in Nvidia and several suppliers we believe have been qualified to supply the AI systems ramping in volume as we speak.  

Join us this Thursday for a one-hour webinar, where we’ll outline our buy and sell strategies on under-the-radar AI stocks and discuss how we’re positioning in a market where some valuations look stretched while others still have room to run. Learn more here

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

Please note: The I/O Fund conducts research and draws conclusions for the Fund’s positions. We then share that information with our readers. This is not a guarantee of a stock’s performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.

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Micron’s stock is up 120% YTD – or 3X more YTD than AI heavyweight Nvidia. Recently, the high-bandwidth memory content that Micron supplies has increased 3.5X between GPU generations, leading to a quiet memory boom across DRAM and NAND suppliers.  

Memory is typically a cyclical industry that is low margin and lumpy, yet memory 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.  

In fiscal 2025, Micron’s HBM, high-capacity dual in-line memory modules (DIMMs) and low-power (LP) server DRAM revenue reached $10 billion, up more than fivefold from the prior year, while HBM alone reached $2 billion in revenue in Q4. Data center is already proving to be a strong driver of growth for Micron, accounting for 56% of sales in FY25, up from 35% in FY24. On a dollar basis, data center revenue surged 137% YoY to $20.75 billion. 

Below, we look at how Micron has quietly outperformed some of the biggest players in AI YTD and if its ability to defy the odds can continue. 

Micron Delivers 3.5× More Memory per GPU, Powering 34× Larger AI Models

HBM capacity per chip continues to rise with each new generation of GPU, as its ability to offer higher bandwidth, performance, and lower latency is crucial for increasingly powerful large language models.  

For example, we’ve seen a ~3.5x increase in HBM content in short fashion on Nvidia’s GPUs within about three years’ time frame: 

• The H100 featured 80GB of HBM2e content per chip. This chip began shipping in Q4 2022 and ramped in early 2023. 
• The H200 featured 141GB of HBM3e content per chip, 1.76x higher than its predecessor, which helped drive 1.4x to 1.9x faster inference on leading AI models. 
• 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. 

AMD is also showing surging memory requirements, to the tune of 3.5X across two main generations:  

• The Instinct MI250 featured 128GB of HBM2e memory. 
• The MI350X featured 288GB of HBM3e memory, a 125% increase versus the MI250 and on par with Nvidia’s Blackwell Ultra.  
• The MI400 series is expected to feature 432GB of HBM4 memory, a 50% increase versus the MI350X and the Blackwell Ultra. In the Helios rack configuration slated for 2026, the MI400 will boast 31.1TB of HBM content, 1.5x more than the GB300 NVL72.  

NVIDIA’s Grace CPU Boosts Demand for Micron’s LPDDR5X Memory

When thinking about Nvidia’s GPU platforms, it oftentimes is overlooked that the GB200, GB300 and the older GH200 generations are all paired with Nvidia’s Arm-based Grace CPU (hence the G-based nomenclature). The Grace CPU accelerates CPU-to-GPU connections with Nvidia’s NVLink C2C and helps boost performance and energy efficiency of AI workloads utilizing its Arm Neoverse V2 cores and LPDDR5X (low power double data rate 5) memory.  

For example, Micron tested inference performance on Meta’s Llama 3-70B with LPDDR5X memory on the GH200 versus DDR5 on the H100, and found that LPDDR5X delivered 73% less energy consumption with 5x higher throughput and 80% better latency.  

The timing and ramp of the GB200 and GB300 throughout the second half 2025 and into 2026 suggests the new LPDDR5X growth curve is at its strongest. To put in perspective, shipments of ~30K GB200/300 racks in 2025 would require more than one million LPDDR5X modules, with each NVL72 rack featuring 17.3TB, or 36 480G modules. If rack shipments double to ~60K in 2026, this would also double LPDDR5X module demand.  

Driven by the Blackwell platform, Micron saw revenue from LPDDR5X for servers up 50% QoQ in fiscal Q4 to a record level, though the company did not disclose its exact revenue contribution. 

Micron’s Expanding Role in AMD and NVIDIA’s HBM Supply Chain

The HBM market is quite competitive between Micron, Samsung and SK Hynix with Micron historically ranking third. However, Micron plays an increasingly important role in Nvidia’s supply chain, and to a lesser extent, AMD’s. Micron is expanding its presence within HBM, stating in Q4 that it has expanded its HBM customer base from four customers in Q3 to six.  

Micron has a range of products designed into Nvidia’s leading platforms: 

• Micron’s HBM3e 8-high 24GB cubes are designed into the HGX B200 and GB200 NVL72 platforms. 
• Nvidia’s HGX B300 NVL16 and GB300 NVL72 feature Micron’s HBM3e 12-high 36GB cubes.  
• Micron’s LPDDR5X supports Nvidia’s GB300 Superchip, with Micron stating in Q4 that “since NVIDIA's launch of LPDRAM in their GB-product family Micron has been the sole supplier of LPDRAM in the data center.”  

While Samsung remains a key HBM supplier for AMD, Micron has collaborated with the Nvidia challenger on the Instinct MI350 GPU family as well as its EPYC CPUs. Micron’s HBM3e 12-high 36GB cubes support the MI350X series, while its 128GB DDR5 RDIMM modules support AMD’s 4th gen EPYC CPUs, providing “up to 22% improved energy efficiency and up to 16% lower latency over competitive 3DS through-silicon via (TSV) products.”

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Moving through 2026, the industry is shifting to HBM4 products, where Micron believes it outperforms Samsung and SK in terms of performance and power efficiency. The chipmaker noted it is in active discussions with customers for HBM4 volumes and expects to sell out of capacity for 2026 over the next few months.  

This role of supplying both Nvidia and AMD with core memory products and leading on performance and power on the upcoming HBM generation positions Micron well for growth in 2026 and 2027.  

Micron Reports Strong 44% Revenue Growth Driven by AI Memory Demand

• Surging AI data center demand drives record FQ4 revenue. 
• Strong AI-demand for high-performance memory is creating tight supply, which in turn is driving higher DRAM and NAND prices.  
• Data center market growth is complemented by improvement in other end markets. 

Micron reported record FQ4 revenue of $11.32 billion. The primary drivers of last quarter’s record revenue were the company’s DRAM segment, specifically High Bandwidth Memory (HBM) products, which benefited from the rapid expansion of AI datacenters.  

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. Micron guided a fresh record in FQ1 at $12.5 billion at midpoint, pointing to 43.5% YoY growth and a 10.5% sequential growth. Analysts expect revenue growth to accelerate to 60.6% in FQ2. 

Micron’s FQ4 revenue growth accelerated by 9.4 percentage points sequentially to 46%, marking continued momentum in AI-driven demand.

FQ4 DRAM revenue grew by 69% YoY and 27% QoQ to $8.98 billion, a second consecutive quarter of strong sequential growth. DRAM revenue accounted for 79% of total revenue. The growth was driven by bit shipments in the low-teens percent sequentially and prices also increased in the low double-digit percentage range.  

FQ4 NAND revenue was down (-5%) YoY and up 5% sequentially to $2.25 billion. NAND bit shipments declined in the mid-single digits, and prices increased in the high single digits percentage sequentially due to a favorable mix and tight supply. 

Micron benefits from other markets such as smartphones and automotive, represented by the mobile and client business unit (MCBU) up 5% YoY and up 16% sequentially to $3.76 billion.  

For FY25, revenue rose 49% YoY to $37.38 billion, driven primarily by DRAM and HBM revenue, which rose more than 62% YoY to $28.58 billion. HBM reached an annualized run rate of $8 billion in FQ4, with HBM share expected to grow again in FQ1 and HBM4 capacity in discussions to soon be sold out for calendar 2026.  

Micron has not provided a full-year guide for revenue, but current consensus estimates call for 43% growth to $53.5 billion in revenue. 

Micron Leads the AI Memory Supercycle with Record Data Center Growth

The AI-driven demand for memory (especially HBM and high-performance DRAM) is still in the early stages of a multiyear growth cycle. The company’s CEO and Chairman, Sanjay Mehrotra, also mentioned in the recent earnings call, “Memory is very much at the heart of this AI revolution. This means a tremendous opportunity for memory and certainly a tremendous opportunity for HBM." 

In fiscal 2025, Micron's data center reached a record 56% of company revenue, with growth primarily driven by DRAM products and aided by data center SSDs and NAND components. Overall, data center revenue increased 137% YoY to $20.75 billion.  

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 revenue surge to … 

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• Micron’s AI-related segment that surged over 200% last fiscal year and what management is saying about growth in the upcoming fiscal year  
• The key line item in the income statement for every AI-related hardware player, and if Micron has what it takes to see sustained, bullish price action  
• What Micron’s valuation is communicating and if the stock still has room to run 

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 revenue surge to 257% YoY in fiscal 2025 to $13.5 billion, or YoY growth of nearly $10 billion. Micron’s other data center unit, its Core Data Center Business Unit (CDBU), consists primarily of data center SSDs and NAND components. This unit saw revenue growth of 45% YoY to $7.23 billion.  

For Q4, CMBU revenue rose 214% YoY to $4.54 billion, while CDBU revenue declined (23%) YoY. CMBU revenue growth was driven by HBM and strong bit shipment growth, though Micron offered no commentary behind the decline for CDBU. 

Management expects robust AI server demand, the shift to HBM4 and tight DRAM supply to remain tailwinds to growth and profitability moving through 2026: “we expect healthy demand supply environment in 2026 for overall DRAM, and that bodes well for profitability of DRAM, profitability of HBM and of course, profitability of non-HBM as well, which is experiencing tight supply.” 

When looking toward industry-level estimates, Goldman Sachs projected the HBM market to reach $45 to $51 billion, up ~37% YoY at midpoint from Micron’s $35 billion 2025 TAM estimate. With Micron’s HBM share expected to match its DRAM share in the low-to-mid 20% level, this would project HBM revenues likely surpassing $10 billion next year. Over the long run, Micron expects HBM’s total addressable market (TAM) to hit $100 billion or higher by 2030, which assuming some continual share gains would potentially give the chipmaker a $25 billion-plus HBM business by the end of the decade, or more than 4X from 2025.

Micron Clears 50% Gross Margin as Profitability Surges

• Solid margin expansion driven by favorable pricing, improved product mix, disciplined cost management, and operating leverage. 
• 50% gross margin bar cleared.  
• The growing proportion of higher value products mix to further aid margin expansion. 

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.  

Adjusted operating margin was 35%, up 8.2 points QoQ and 12.5 points YoY, driven by operating leverage. For Q1, Micron expects adjusted operating margin to be 40.8%, up by 5.8 points QoQ and by 13.3 points YoY, signaling strong operating leverage. 

The strong margins are expected to continue in FY2026 due to continued increase in memory prices due to supply tightness, cost controls, and growing proportion of higher value product mix. 

Micron’s adjusted gross margin guidance for FQ1 stands at 51.5%, up 12 percentage points year over year.

Gross margin is the key line item for every hardware player in the AI market to see sustained, bullish price movements as it helps to communicate if the stock is participating in a commoditized trend, or if there’s something more secular and unique to the hardware player’s product that can lead to charging higher prices. Of course, driving down costs is also good to see – but nothing beats being able to charge more for a hardware product in terms of communicating the strength of an AI hardware stock. 

Micron has a lot it must prove in terms of its lumpy margins yet is off to a solid start by moving from the mid-30% range to expected >50% next quarter. 

Adjusted EPS Soars 157% Amid Strong AI Memory Demand

Micron is expected to see earnings double this fiscal year as margins have swiftly recovered from late 2023 and early 2024. 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 guidance and corresponding to YoY growth of 110%. Earnings growth is expected to reaccelerate to 155% in Q2 but then decelerate to 126% in Q3. For the full year, Micron is expected to see 100% YoY growth to $16.63 primarily driven by better pricing, cost improvement, operating leverage, and a growing proportion of higher value products.  

Micron’s FQ4 adjusted EPS climbed 157% YoY to $3.03, marking a strong earnings rebound as AI-driven demand and pricing strength lifted profitability.

Micron’s Free Cash Flow Surges 10x with AI Memory Boom

•  Adjusted free cash flow is on track to improve significantly in FY2026, driven by margin expansion. 

Strong revenue and profits are leading to higher cash flows. Micron has seen a significant turnaround in the adjusted free cash flow from (-$5.45 billion) in FY2023 to $368 million in FY2024 and up nearly 10x to $3.72 billion in the recently concluded FY2025. 

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 

Despite its recent rally, Micron trades at reasonable multiples, well below its peak from 2024. On the top line, Micron trades at 4x forward revenue, 10% above its average 3.6x multiple and far below its peak of 6.8x from mid 2024. 

On the bottom line, Micron trades at 11.6x forward earnings, though its 43.9x average is skewed higher by 2024’s >100x multiples when margins were razor-thin. Since the start of 2025, Micron has traded as high as 16x forward earnings and as low as 8x. 

Source: YChartsYCharts

Key Risks to Micron’s AI Memory Growth Outlook

Micron’s growth to this point and beyond has been centered around HBM, both on the top and bottom lines. CMBU is the only unit that sees operating margins above the corporate total, at 48% versus 25%, 29% and 20% for its other segments, meaning that future operating margin expansion will be tied solely to growth from CMBU, and felt more the faster CMBU grows. This may mean that margin and earnings upside in 2026 may be limited come 2027.  

Conclusion  

Micron’s stock has quietly outperformed AI leaders YTD by a wide margin such as Nvidia, Broadcom, Oracle, Meta, Microsoft and more. This has been achieved by AI-related segments surging over 200% YoY, leading to a critical improvement to their margins and by also rebounding to become cash flow positive again.  

Clearly, Micron is no longer tied to consumer device cycles. Instead, HBM had led to higher margins and multi-year supplier agreements, resulting in a leveraged approach to participating in the AI infrastructure buildout. 

In terms of whether Micron can become more secular, this past year has proven that HBM memory is a component multiplier when compared to GPUs in the hardware stack, as HBM scales faster than GPUs on a per-system basis. Each generation of GPU, from Hopper to Blackwell to Rubin, requires more memory capacity and bandwidth per chip. Therefore, there is compounded effect, as the number of GPUs rises combined with each GPU system requiring more HBM per package.  

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Palantir leads the AI software pack in terms of strong earnings reports this past quarter as the company achieved significant milestones, the most impressive being US commercial revenue grew 93% YoY and 20% sequentially. You will be hard pressed to find this kind of QoQ growth across AI’s biggest players. 

The Artificial Intelligence Platform (AIP) is driving most of the Commercial growth as there was a clear and obvious revenue inflection when AIP launched in mid-2023. AIP is a cloud-agnostic and model-agnostic platform that connects AI with existing systems and operations. AIP goes beyond what LLMs can deliver on their own by embedding models in workflows and logic. The value creation comes from being able to work with incomplete data sets through the ontology layer while also offering a level of reasoning that goes far beyond just analysing the data itself.  

AIP’s scalability and flexibility continues to attract larger and more ambitious commercial engagements. As you’ll see below, key metrics such as total contract value (TCV), US commercial customer count, US commercial remaining deal value (RDV) and RPO are supportive of continued growth in future quarters.   

There are also robust cash flows and expanding margins to strengthen the story. However, what is this Perfect 10 worth? In fact, Palantir is well beyond a Perfect 10 and is rather a Perfect 100 as its forward P/S sits at an astonishing 104. This means taking FY2025 revenue of $4.2B , it would take over 100 years to pay back its current market cap.

Below, the I/O Fund team weighs in on the future growth opportunities of Palantir, the spectacular earnings report and how we view it’s hotly debated valuation. 

Palantir’s Platforms: The Foundation of Its AI Growth Strategy

Palantir’s first platform was Gotham for government purposes before many of the integrated features were expanded to Foundry, which launched around 2021 for commercial purposes (exact date is not available but generally understood to be around this time).   

Gotham and Foundry create a unified data set for actionable insights across industries such as manufacturing, product development, and customer experience. Palantir primarily uses its customer's own databases for data but may also use publicly available information, like social media, for government clients. The system is traditionally deployed on-site at the customer's data center.  

Its main competitive advantage is its ability to work with incomplete data sets, unlike traditional business intelligence tools that require complete data. Palantir describes this as offering "actionable depth"—focusing on the reasoning behind decision-making, not just analyzing the data itself. 

The core platforms are designed to create a model of the real world by analyzing numerous data points. Unlike traditional SQL databases, they allow users to query data using natural language and receive results in real-time. 

The Gotham platform enables users to identify patterns hidden deep within datasets using semantic, temporal, geospatial and full-text analysis.   

Palantir Foundry is the commercial offering and has four layers of tooling: Foundry Core, Data Foundation, Ontology and Workflows. The Ontology layer offers a distinct, competitive advantage by allowing datasets to be turned into real-world concepts with the ability to accelerate on the company’s core ontology to reduce redundancy. Workflows are where it all comes together in an integrated environment. When a user has a question, it answers it using all layers and tools available 

The Apollo layer provides continuous delivery and an automated configuration layer that enables Foundry and Gotham to operate across all cloud environments and in places where there is little to no connectivity. On top of Palantir being able to form conclusions from incomplete data sets, the company can also deploy its platform and applications anywhere. 

Palantir’s marketing team says Apollo “goes where no SaaS has gone before” because it allows what is done on-premises to also run on multi-cloud SaaS with code that is deployed across all environments rather than written for a specific environment. 

Where bandwidth is not an issue, the company transmits all raw inputs and enriched metadata from models. Where there are constraints, the platform transmits meta-data only which can reduce bitrate by 20X. 

Apollo Edge AI creates a "meta-constellation" by linking up to 237 satellites to reduce decision-making delays. This network coordinates hundreds of sensors and AI models, enabling complex tasks like tracking submarines in areas without bandwidth. One example is tracking submarines that pose a threat to the U.S. and its allies. In this case, submarines are being tracked on a granular level in areas where there is no bandwidth available. A key feature is its ability to operate independently, without relying on a single cloud provider such as AWS or Azure. 

Palantir’s Artificial Intelligence Platform (AIP) 

The Artificial Intelligence Platform has helped the stock surge in recent years as it integrates generative AI with operational data and workflows. When AIP is combined with Foundry and Apollo, it provides an AI service mesh that can run hundreds of microservices, scale compute through its Rubix engine and orchestrate updates through Apollo. Like Apollo, AIP Is independent from any one cloud environment.   

AIP Ontology is what Separates Palantir:  

The 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.”   

You will often hear the management team state large language models will become commoditized, which is a way of saying the software that is on top of the LLM is where value creation comes from rather than the LLM alone. For this reason, AIP is designed to not only be cloud agnostic but to also be LLM-agnostic as it works with any large language model – for example, OpenAI, Anthropic, Meta’s Llama, etc.   

The platform also offers an AI agent workflows for building AI agents that are further optimized for specific use cases and customized through additional tools. Autonomous agents can be built and tested on the platform.    

When it comes to security and governance, Palantir’s roots in government contracts means the software company is exceptional compared to peers in this area. 

Enterprise Growth in AI is Accelerating 

Cloud and model providers are now pushing for greater enterprise AI adoption, a trend that arguably will benefit Palantir just as much from new use cases for AI, and increasing amounts of data generated from AI models and agents. 

For example, OpenAI CEO Sam Altman told investors that they “should expect a huge focus from us on really leaning into enterprise,” as the company unveiled an array of integrations such as integrating Codex with Salesforce’s Slack, or using Figma in chats to create diagrams. OpenAI also launched AgentKit, aiming to provide its 4 million developers with a “unified suite” for AI agent development, a key area other enterprise-focused software firms like ServiceNow are focusing on.  

IBM teamed up with Anthropic on Tuesday to integrate its Claude models on IBM’s platform to advance enterprise software development, with IBM noting that early testing across 6,000 clients found productivity increases of ~45% on average with recognizable cost savings. This follows Anthropic’s announcement on Monday that it would roll out its Claude models to Deloitte’s entire 500,000 global workforce.  

… and Surging Token Growth Support Palantir’s Story 

Surging token growth in a way also supports rising enterprise AI adoption and a tailwind for growth for Palantir, despite a majority of tokens likely being generated by the hundreds of millions of users for consumer-facing AI products. OpenAI disclosed that it is processing 6 billion tokens per minute, or ~260 trillion per month, while Google’s token generation more than doubled to 980 trillion in one month.  

AI agents are expected to generate magnitudes more tokens, with Anthropic estimating agents process 4x more tokens and multi-agent systems 15x more than typical chatbot interactions. Over the long run, Dell projects data generated will more than triple from 2024 to 2029, from 174 ZB to 523 ZB. To put this in perspective, 1 ZB is approximately equivalent to nearly 4 billion 256GB iPhones, and over the next four years, 350x that.  

For Palantir’s AIP, which connects frontier models directly to enterprise data streams, this creates a surge in data that Palantir can then contextualize and provide value for decision making for its customers. There is already more evidence below the headline figures that Palantir is benefiting from increasing enterprise AI adoption, such as Palantir’s quarterly deals closed, which not only shows that its deal flywheel remains healthy with 13% QoQ growth in Q2 (accelerating from 8% QoQ in Q1), but also an increasing amount of larger deals over the last three quarters.   

Palantir’s quarterly deals closed rose 13% sequentially in Q2, accelerating from 8% growth in Q1, signaling strong AI-driven enterprise growth momentum.

Palantir Raises FY Guidance Following Strong Earnings Performance

Palantir's second-quarter performance surpassed a significant one billion revenue milestone for the first time. This achievement was driven by remarkable 48% YoY growth to $1.0 billion, a figure that outpaced consensus estimates by 6.8%. The result represents a dramatic inflection from the 12.7% growth reported in Q2 2023—the launch quarter of its Artificial Intelligence Platform (AIP), underscoring the platform's profound impact.  

Most importantly, Q2 marked the eighth consecutive quarter of accelerating revenue growth, with the rate increasing by 870 basis points sequentially, signalling powerful and sustained business momentum driven by AI. The Q2 revenue growth rate also smashed the high end of the company’s prior guidance by nearly 10 percentage points and represents a 21 percentage points increase compared to the growth rate in the same period last year.  

The company is witnessing strong growth in customers, which grew by 43% YoY and 10% sequentially to 849. Most importantly, revenue from the largest customers continues to expand. Second quarter trailing 12-month revenue from the top 20 customers increased 30% YoY to $75 million per customer, indicating strong market adoption and consistent expansion. 

AIP remains the primary driver of the company’s revenue reacceleration. Its scalability, flexibility, and adaptability enable rapid integration across enterprises. Commercial customers leverage Palantir’s AI and machine learning capabilities to harness the power of cutting-edge large language models (LLMs) within Foundry and Gotham, delivering near-instant analytics and insights, as well as meaningful gains in productivity and efficiency. The company’s US commercial revenue was the main driver of growth, which accelerated 22 percentage points sequentially to 93% YoY growth to $306 million. 

Palantir’s Q2 revenue growth surged 870 basis points quarter-over-quarter, highlighting powerful AI-driven momentum and accelerating enterprise adoption.

The company's Q3 revenue guide was also impressive in the range of $1.083 billion to $1.087 billion, representing a YoY growth of 49.5% at the midpoint. On a sequential basis it represents an 8-percentage growth and is the highest sequential revenue growth guide in the company’s history.  

The current consensus estimates point to a 50.5% YoY growth to $1.09 billion. The company's Q3 revenue estimates have witnessed strong positive revisions, up from 34.8% during the first week of May, representing a solid 15.7 percentage point improvement within five months. While Palantir has been delivering tremendous results and consecutive acceleration on the top-line each quarter, a crucial moment to watch for will be when the company reaches its peak growth quarter. Analysts are currently modelling this to come as early as Q4 with revenue growth expected to be 44%, decelerating more than 6 points sequentially. This could be a tough spot for investors considering the company's stretched valuation, as there has yet to be a test of growth peaking and decelerating. 

On the back of the solid Q2 results the management also raised the full year 2025 revenue guidance midpoint to $4.146 billion, representing a 44.7% YoY growth rate, a solid 880 basis points increase over the full year 2025 revenue guidance provided last quarter, and the largest ever full year revenue guidance raise. 

Analysts expect 2025 revenue to grow 45.3% YoY to $4.16 billion, an increase of 10 percentage points from the 35.3% growth expected in the beginning of May. Looking forward, analysts expect 2026 revenue to grow 35% YoY to $5.62 billion and 34.4% YoY growth to $7.55 billion in 2027. 

Palantir Stock Gains as U.S. Commercial Revenue Jumps 22%

AIP continues to drive strong results for the company’s US commercial segment. The Q2 US commercial revenue grew by a whopping 93% YoY and 20% sequential growth to $306 million. Revenue growth rate accelerated from 71% YoY growth and 19% sequential growth recorded in the previous quarter.  

The strong acceleration also led to US commercial revenue to comprise 31% of the company’s Q2 revenue compared to 23% in the same period last year. If we exclude revenue from strategic commercial contracts, the Q2 US commercial revenue grew by 95% YoY and 20% sequentially. Management also emphasized during the earnings call that the company’s products are used in real-world applications and provide tangible benefits. The company is benefiting from larger new deals and the continued strong momentum with existing customers, driving strong revenue growth. 

U.S. commercial revenue growth accelerated from 22% to 93% year-over-year in Q2 2025, reflecting surging enterprise adoption and AI-driven demand.

Here are some of the top highlights from the quarter for US commercial: 

• The company reported the strongest quarter of US commercial TCV booked at $843 million, representing a YoY growth of 222%. 
• Over the trailing twelve months, the company closed $2.8 billion of US commercial TCV bookings, an increase of 141% from the prior 12 months period, demonstrating the demand for AI production use cases. 
• Total remaining deal value in the US commercial segment was up 145% YoY and 20% sequentially, reflecting continued momentum and expanding customer demand. 
• The US commercial customers grew by 64% YoY and 12% sequentially to 485 customers, adding 53 customers in the recent quarter. It also implies that the company’s customers increased 4x from Q2 2022. 

Management shared a couple of TCV highlights during the earnings call, wherein a healthcare company completed a boot camp in April of this year and later signed a $88 million TCV deal a month later to coordinate and automate its patient care across facilities. Similarly, an American telecom company started working with the company in 2022 and since then has increased their contract 10x, projecting hundreds of millions in cost savings.    

Management raised its full-year US commercial revenue guidance to over $1.302 billion, implying at least 85% YoY growth. This updated outlook is 17 percentage points higher than the prior quarter’s guidance, reflecting strong commercial business momentum. 

Overall, Commercial revenue grew by 47% YoY and 14% sequentially to $451 million. Revenue accelerated by 14 percentage points from the previous quarter. When excluding the impact from strategic commercial contracts, second-quarter commercial revenue grew 49% YoY and 14% sequentially. The company closed $1.1 billion in commercial TCV bookings, up 185% YoY. 

International Commercial revenue remains a weak spot, as Q2 revenue declined (-3%) YoY but grew just 2% sequentially to $144 million. Management noted in the earnings call that Palantir continues to “capitalize on targeted growth opportunities in Asia, the Middle East and beyond, but remain focused on accelerating the growth in our U.S. business.” 

Strong Government Contracts Drive 49% Revenue Growth for Palantir

While Palantir’s success in the commercial sector is now quite evident, the government sector remains Palantir’s bread and butter. Government revenue accounted for 55% of the total revenue, and the commercial revenue accounted for the remaining 45%. Government outpaced commercial growth for the fourth consecutive quarter; however, if we exclude strategic commercial contracts, both government revenue and commercial revenue grew by 49% in the recent quarter. 

In Q2, government revenue grew by 49% YoY and 14% sequentially to $553 million, accelerating four percentage points from the previous quarter. Within that, US government business grew by 53% YoY and 14% sequentially. 

Management highlighted during the Q2 earnings call that the US Space Force's Space Systems Command had awarded the company a $218 million delivery order to support seamless, synchronized multi-domain warfighting for the space and air operational communities. Additionally, the ceiling for the Maven Smart System contract was increased by $795 million to prepare for what they expect will be significant demand from combatant commands for the AI-powered software capabilities over the next four years.  

In early August, the company secured a 10-year enterprise agreement with the Army, valued at up to $10 billion, which consolidates 75 existing contracts into a single contract. More recently, the company also won the first billion-dollar deal outside the US. It signed a $1 billion AI deal with the UK’s Ministry of Defence. 

What Key Metrics are Saying About Palantir’s Future Growth 

Clearly, Palantir has been a winner up to this point – there is no denying that. However, what are the key metrics saying about future growth? Do the company’s fundamentals support the market’s lofty expectations—and what does a fair valuation look like from here? 

Below, we examine the following 

• If the key metrics support continued growth – with one metric that you must not miss 
• The I/O Fund’s thoughts on Palantir’s valuation  
• The one risk that Palantir bulls are overlooking 
• Our Premium members received a 15,000 word report outlining the Top 15 AI Stocks for Q3 of 2025 with many stocks seeing higher returns last quarter than Palantir. Sign up now to find out which AI stocks we like better than Palantir.Top 15 AI Stocks for Q3 of 2025 with many stocks seeing higher returns last quarter than Palantir. Sign up now to find out which AI stocks we like better than Palantir. 

There were a handful of other key metrics that performed quite strongly in Q2. This suggests that the underlying business momentum remains robust in the coming quarters. These include:  

• The company booked the highest TCV and ACV ever in the recent quarter with $2.3 billion in TCV and $684 million in ACV. The deal momentum was strong, as it closed 157 deals worth $1 million or more, including 66 deals worth $5 million or more and 42 deals worth $10 million or more.  
• The total remaining deal value for the company grew by 65% YoY and 20% sequentially to $7.1 billion, a stunning 20 points acceleration from the 45% YoY growth reported in the previous quarter.  
• RPO grew by 77% YoY and 27% sequentially to $2.4 billion, a whopping 31 percentage points acceleration from the previous quarter.  
• The net dollar retention rate accelerated 400 basis points sequentially to 128%. It is the highest rate since the first quarter of 2022. It was primarily driven by both expansions of existing customers and new customers acquired in Q2 of last year, implying that the company is a key beneficiary of the AI revolution. 

Net Dollar Retention improved 400 basis points sequentially to 128% in Q2 2025, marking the highest level in over two years.

Strong Margin Expansion Supports Profitability

Revenue growth and key metrics were impressive, and management complemented this performance with solid bottom-line improvement, demonstrating disciplined execution. 

• The company’s gross profits grew by 47.5% YoY to $810.76 million 
• The operating profits grew by 155.7% YoY to $269.3 million, driven by strong operating leverage. Operating margin improved 11 percentage points YoY and 7 percentage points sequentially to 27%. 
• The adjusted operating profits grew by 83.1% YoY to $464.4 million. The adjusted operating margin improved by 9 percentage points YoY and 2 percentage points sequentially to 46%.

Palantir also delivered the highest Rule of 40 score of 94% (revenue growth + adjusted operating margin) in Q2. It also accelerated 11 percentage points from the previous quarter and was the eighth consecutive quarter of an expanding Rule of 40 score. Due to the increase in full-year revenue and adjusted operating margin guidance, management now expects a Rule of 40 score of 91% for the year 2025, up from 68% in 2024. 

Q2 adjusted operating margin expanded 9 percentage points year-over-year to reach 46%, reflecting continued operating leverage and disciplined cost management.

Adjusted EPS Surges 78% Year-over-Year

The company’s adjusted EPS grew by a solid 77.8% YoY to $0.16, beating estimates by 15.6% driven by strong operating leverage. 

• Analysts expect adjusted EPS to grow 67.4% YoY to $0.17 in Q3 and 35.5% YoY growth to $0.19 in Q4. 
• Looking forward, analysts expect strong adjusted EPS growth of 56.7% YoY to $0.64 in 2025 and 31.8% YoY to $0.85 in 2026. 

Adjusted EPS surged 78% YoY in Q2 2025, beating estimates by 16%, driven by strong operating leverage. Analysts project continued strength with 67% YoY growth in Q3 and 36% in Q4, underscoring robust earnings momentum through 2026.

Adjusted Free Cash Flow Margin Expands to 57%

The company’s strong revenue growth and profits are driving robust cash flows.  

• Q2 operating cash flows grew by 274.3% YoY to $539 million. Operating cash flow margin improved by 33 percentage points YoY and 19 percentage points sequentially to 54%. 
• Adjusted free cash flows grew by 282% YoY to $569 million. Adjusted free cash flow margin improved by 35 percentage points YoY and 15 percentage points sequentially to 57%. 
• The company has a strong balance sheet with cash & marketable securities of $6.0 billion, up from $5.43 billion in the previous quarter. 

Valuation

To many investors on social media, Palantir’s valuation remains a hot topic, with it blowing past norms and reaching the upper echelons of the stratosphere for what is considered ‘typical’ for SaaS stocks. Put it this way — how often do you see a software company re-accelerate revenue from 13% growth a couple of years to 50% in nine quarters organically and sustainably, while both increasing profitability and posting cash flow margins more than >50%? 

Palantir is now trading at about 105x forward P/S ratio, making other best-of-breed cloud names like Cloudflare and CrowdStrike look cheap at 35.5 and 25.2, respectively. On the bottom-line, it is trading at forward P/E ratio of 287, close to Cloudflare’s forward P/E ratio of 251. 

Source: YChartsYCharts

Given Palantir is at 105 forward PS, there are certainly easier stocks to own going into the second half of the year. Within AI, specific niches are booming such as AI networking, AI energy and AI data plays that are trading far lower than Palantir yet will see an incremental lift from the incoming inference market.

Potential Risks and Challenges

The valuation with Palantir is a gamble. The bulls believe they’ve speculated correctly, while there’s likely to be short sellers who do well with this stock too. Palantir is attempting to set a new bar for AI software with the 105 forward valuations, it’s truly anyone’s guess if the stock can sustain the valuation or not.   

Despite US Commercial serving as a crucial lever for Palantir’s tremendous eight-quarter acceleration on the top-line, government revenue cannot be overlooked as it remains Palantir’s bread & butter. Government still accounts for 55% of Palantir’s revenue, reinforcing the importance of the segment. Regarding the government, Palantir found itself in the hot seat on Oct 03rd, with shares down 9% as reports surfaced claiming that the Army stated in a memo that Palantir’s battlefield tech developed with Anduril posed a major security risk. Both companies have later clarified that the issues have been fixed.  

Conclusion 

Part of our process is to highlight stellar earnings reports and Palantir certainly qualifies. It’s hard to find a blemish in the company’s current quarter as it’s perhaps one of the best reports the company has reported yet – which is saying a lot. However, at the current valuation, it would take Palantir 100 years to pay back its market cap. Therefore, we feel there are easier AI stocks to own as Palantir’s current valuation does not leave much room compared to the dozen or so others also benefiting in AI’s enormous tailwinds.  

Our Premium members received a 15,000 word report outlining the Top 15 AI Stocks for Q3 of 2025 with many stocks seeing higher returns last quarter than Palantir. Our Premium members will be receiving the Top 15 AI Stocks for Q4 next week. Sign up now to find out which AI stocks we like better than Palantir.Top 15 AI Stocks for Q3 of 2025 with many stocks seeing higher returns last quarter than Palantir. Our Premium members will be receiving the Top 15 AI Stocks for Q4 next week. Sign up now to find out which AI stocks we like better than Palantir.

Please note: The I/O Fund conducts research and draws conclusions for the Fund’s positions. We then share that information with our readers. This is not a guarantee of a stock’s performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.

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CoreWeave saw muted price action following the latest earnings report; yet the soft price action is rare for the AI darling. The company went public in March and has stood out as the premier IPO among AI stocks given the stock is up over 200%. The lockup expired last month, which begs the question – can CoreWeave continue to defy the odds and overcome the typical insider selling that is seen around a lockup expiration? Investors typically fare better waiting for anxious insiders to sell, yet CoreWeave has been anything but ordinary.  

In terms of timing, CoreWeave has hinted the second half of the year will be stronger. We look at why CoreWeave could end the year on a high note, yet to be prudent, we also look at why there was a negative reaction to the most recent earnings report. We end with a buy plan strategy the I/O Fund is eyeing for weighing the puts and takes on what promises to be a highly volatile, fast moving stock.

CoreWeave Rivals the Big 3 as the First “AI Hyperscaler” 

CoreWeave brands itself as the world’s first “AI hyperscaler” as they offer both infrastructure and a software platform for developing large language models and deploying them. Being dubbed an AI infrastructure player means CoreWeave must offer a compelling value proposition to attract business from arguably the largest competitors in the world – AWS, Microsoft Azure and Google Cloud.  

In the S-1 filing, the company points out it was built for AI workloads as opposed to the legacy cloud infrastructure-as-a-service providers that were primarily optimized for the cloud software era and e-commerce era. CoreWeave also asserts that outdated cloud infrastructure leads to lower utilization rates when you factor in usage.  

One of their primary value propositions is offering bare metal servers, as the company does not need to offer shared GPUs like the hyperscalers. By stripping away the virtualization layer, raw performance goes up for R&D labs, who do not need workload flexibility. Although CoreWeave offers shared infrastructure in terms of storage and networking, one of the company’s key differentiations from the Big 3 is by offering dedicated bare-metal access. 

The company also offers proprietary software to help achieve higher total system performance and more favorable uptime relative to competitors. According to the S-1 filing, “by delivering more compute cycles to AI workloads and thereby reducing the time required to train models, our capabilities can significantly accelerate the time to solution for customers […].” 

CoreWeave Competes with Big 3 on Higher Usage Utilization Rates (MFUs) 

To further understand CoreWeave’s competitive advantage, it’s important to discuss the model FLOPs utilization gap. The “MFU gap” is a metric that describes the gap between compute capacity and usage, which today often ranges between 30% and 40%. Cloud providers are often at 100% GPU utilization, yet there is a much lower utilization rate for GPUs when factoring in maximum floating-point operations per second (FLOPs). Initially, when MFU was coined by Google’s PaLM Paper, model training was running at 20% MFUs. 

According to Google’s PaLM paper, they came up with the metric to better gauge a more realistic utilization rate: “Given these problems, we recognize that HFU (hardware FLOPs utilization) is not a consistent and meaningful metric for LLM training efficiency. We propose a new metric for efficiency that is implementation-independent and permits a cleaner comparison of system efficiency, called model FLOPs utilization (MFU).”  

When factoring in FLOPs, the best possible (realistic) MFU is in the range of 50% to 60%, as this translates to raw compute being the bottleneck. Lower MFUs indicate inefficiencies, which CoreWeave specializes in solving. This could involve optimizing memory bandwidth, improving communication between GPUs, clearing data input bottlenecks, and other ways in which to fix batch size, enable faster data loading, and/or better ways to balance the compute.  

Popular large language models do not publicly report their MFUs, but internally, this utilization rate is a dominant factor in competitiveness and time to market. R&D labs with a higher MFU rate have an important advantage as even an incremental increase in single digits to low double digits can result in a 25% to 50% increase in training speed and cost. 

Due to going public, 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.  

To put it simply, efficiency equals money and time in large-scale AI projects — training huge models can cost millions of dollars and weeks of time, so even a few percentage points of MFU improvement can translate to a significant advantage. 

We covered this in more detail on our premium site in the analysis “CoreWeave: AI Infrastructure Built for the Next Decade.” 

CoreWeave is Adding Capacity Hand over Fist Supported by OpenAI, Meta Agreements Totaling $36.6B 

Before looking too granular at the financials, it’s important to note that CoreWeave is adding new capacity at a rapid clip. At a high level, the company is the most competitive outside of the Big 3 for new AI workloads, evidenced by the strong partnerships it’s securing with Meta and R&D labs like Open AI. 

Last week, CoreWeave announced an expansion of its agreement with OpenAI, worth an additional $6.5 billion. The extension now takes CoreWeave’s total deal value with OpenAI up to $22.4 billion, building on to its initial $11.4 billion deal in March and the first $4 billion expansion in May.  The $6.5 billion deal extends through May 2031, representing average annual revenue of more than $1.2 billion.  

On Tuesday, CoreWeave signed a $14.2 billion deal with Meta, also lasting through 2031, marking one of its largest single deals to date. The deal represents average annual revenue of more than $2.3 billion. 

This provides CoreWeave with other major revenue anchors and additional diversification away from its largest customer Microsoft (72% of revenue in 1H), as the deals could represent nearly 30% of CoreWeave’s current 2026 revenue estimate of $12.1 billion.  

When discussing its customer concentration, CoreWeave made it crystal clear that there is no better customer to have at the moment: “And that when you have a company like OpenAI or an entity like OpenAI consuming compute, they're just doing it at an order of magnitude that these other companies have not achieved yet.” 

Looking beyond Open AI, CoreWeave has a contracted backlog of $30.1 billion, up $4 billion from Q1 and has doubled year-to-date, with expectations for 50% (or ~$15 billion) to convert to revenue over the next 24 months. The most recent deals with OpenAI and Meta bring this to over $50 billion in contracted backlog. 

There are many pieces that must come together to deliver this backlog in the coming years including raising capital to build the infrastructure. However, keep in mind the company has a market cap of about $60 billion or roughly 1.3X the contracted backlog. Although I’m not suggesting a valuation be based off backlog, it’s certainly convincing the stock has room to run given the sheer size of the contracts it’s securing from the largest players in AI. 

In early September, CoreWeave announced that key partner and investor Nvidia had entered a new order worth up to $6.3 billion under the duo’s pre-existing 2023 master services agreement.  

With the new order, whenever CoreWeave’s compute capacity is not fully utilized, Nvidia will be obligated to purchase the unsold capacity. The deal extends through April 2032 and carries a total value up to $6.3 billion. While demand is currently strong and capacity is likely sold out for the near future, having Nvidia backstop future capacity helps alleviate concerns related to high customer concentration and de-risks its future growth story by providing some degree of guaranteed revenue. CoreWeave will disclose the entire MSA in its upcoming quarterly report.  

Expanding Footprint with $6B Pennsylvania Data Center, UK Investment 

In mid-July, CoreWeave announced a $6 billion data center project in Pennsylvania, with an initial capacity of 100MW with potential to expand to 300MW, though the company has not been upfront about delivery timelines for the initial phase or subsequent phases. This project is expected to be the cornerstone of CoreWeave’s vision of creating a mid-Atlantic hub from New York to Virginia. 

Under its first phase, it likely will become one of CoreWeave’s largest data center facilities, considering its current active power footprint averages just over 14MW per data center. At full capacity, the facility will represent nearly 14% of CoreWeave’s current contracted power. On the capex side, CoreWeave has secured $4 billion in funding for the project, including a $200 million investment into grid infrastructure to support the facility. This will limit the amount the company will have to fund out of pocket, lessening its capex needs, which will already be quite elevated come Q4.  

CoreWeave is also expanding its presence in the UK with a new ~$2.0 billion investment, working with Nvidia and data center operator DataVita in Scotland to deploy Blackwell Ultra GPUs. CoreWeave’s international presence is rather limited, with just five data centers across Europe and two in the UK, and investing to expand its international presence will help the company tap into growing demand across Europe.  

Capex Weighted Heavily Towards Q4 

One of the larger risks for investors coming into year-end is CoreWeave’s planned capex, with the company currently expecting the majority to land in Q4 due to timing of when infrastructure will go live. CoreWeave maintained its full-year capex guide of $20 to $23 billion, though in the first half, reported capex was only $4.8 billion (total PP&E increase of $5.7 billion minus $0.9 billion related to construction progress). To put this in perspective, this is 4-5x of the company’s guided revenue for the year. 

Given that CoreWeave guided for just $2.9 to $3.4 billion in capex in Q3, or YTD spend of just $7.7 to $8.2 billion, Q4 capex is implied to be in the range of $12 to $15 billion, or nearly 7-9x estimated quarterly revenue of $1.8 billion. 

The first caveat here is that CoreWeave does not have nearly enough cash to fund this capex entirely by itself. CoreWeave likely will have close to $5 billion in cash and equivalents after raising $2 billion in 9.25% senior notes and upsizing another 9.0% note raise to $1.75 billion, with additional access to a third delayed draw term loan facility for $2.6 billion to fund capex and GPU acquisitions for customer contractions. Combined, this still will not fully cover projected capex for Q3 and Q4.  

The second caveat is that turning to the debt market will be costly, as CoreWeave has currently been pricing senior notes at or above a 9% rate, meaning raising $10 billion in fresh debt (such as what analysts from DA Davidson expect) at a similar rate could cost nearly $1 billion annually in interest payments.  

CoreWeave Only Has 20% of Contracted Power Active 

The reason why CoreWeave must spend aggressively on capex is directly tied to capacity, which is needed to convert its backlog to revenue and maintain hypergrowth. As of Q2, CoreWeave had ~470MW of active power across 33 data centers, or nearly 20% of its 2.2GW of contracted power, leaving an additional ~1.73GW to be developed. At its current scale, CoreWeave has energized >250,000 GPUs, suggesting that at 2.2GW, it can easily energize well over one million leading-edge GPUs. 

Bringing the rest of its power footprint online will not only be expensive but necessary to support its growth story. Management stated they are aiming to nearly double active power by year-end to 900MW, hence the substantial increase in capex in 2H: 

“We are aggressively expanding our footprint on the back of intensifying demand signals from our customers, ensuring that we maintain a durable multiyear runway for growth. We are now on track to deliver over 900 megawatts of active power before the end of the year.” 

CoreWeave operates 33 data centers, primarily in the U.S. with five in Europe, supported by ~470MW active power and ~2.2GW contracted power. Source: CoreWeaveCoreWeave 

Core Scientific’s acquisition has provided an extra leg for growth in power: “Upon closing, CoreWeave would own approximately 1.3 gigawatts of gross power capacity across Core Scientific's national data center footprint with an incremental 1 gigawatt or more available for future expansion. This scale enhances our flexibility to take on new projects and meet accelerated customer demand.”  

Looking ahead, and assuming power and revenue remain correlated linearly, CoreWeave’s current contracted power footprint may be able to sustain a $25 billion revenue run rate, or enough capacity to take it to 2029’s current estimate.   

Unleashing CoreWeave’s Monetization Path and Stock Buy Plan 

CoreWeave’s suite of software is another area the company extends its value proposition beyond the Big 3 as the company reduces the need for specialized orchestration frameworks, engineering resources component failures and the need to constantly monitor for downtime. 

Sign up below to continue reading: 

• How CoreWeave plans to monetize every chatbot response, API call and application 
• The I/O Fund’s buy plan and risk management strategy to help participate in this stock while protecting to the downside 
• Details from the recent earnings report that help clarify why the stock sold off 
• Important commentary from management that hints the end of the year will be strong for CoreWeave

According to Uvation, by focusing only on GPUs and software optimizations (detailed below), CoreWeave offers bare metal servers at a cost that is up to 20% to 50% cheaper than hyperscalers. This helps to explain why the company’s rapid and aggressive growth. 

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. Customers can connect workloads to other clouds like AWS, Azure and Google Cloud. In the most recent earnings call, CoreWeave stated: “We also saw significant growth in our backbone and networking service as one of our largest AI lab customers leveraged our networking backbone to connect its multi-cloud inference infrastructure.” 

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 for 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 access 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 fo their core storage to CoreWeave in the form of multiyear contracts.” 

CoreWeave recently completed its acquisition of Weights&Biases in May, with reports placing the transaction at $1.7 billion, a 36% increase from the startup’s $1.25 billion valuation in 2025. The core product that W&B offers is 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 responses, API calls and applications to easily payback their initial investments plus some (in time). 

Here is what was stated on the call: “In addition to that, the infrastructure that we're building has increasingly been used for chain of reasoning, which is driving a substantial amount of consumption on the inference level. And that's very exciting for us. As I always say, inference is the monetization of artificial intelligence. And we are extremely excited to see that use case expanding within our infrastructure.” 

CoreWeave also acquired agentic AI training startup OpenPipe in early September for an undisclosed sum. OpenPipe aids enterprises in customizing AI agents via reinforcement learning with its open-source toolkit ART (agent reinforcement trainer), tying into W&B’s observability and evaluation frameworks for agents that can be built directly on CoreWeave’s infrastructure platform.

Financials 

Strong Revenue Growth of 207% 

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. 

Revenue growth is expected to be strong in the coming quarters, driven by the robust demand due to training and inference workloads. Management revenue guidance for Q3 is in the range of $1.26 billion to $1.30 billion, representing YoY growth of 119.2% and 5.5% QoQ at the midpoint. While the underlying business momentum remains robust, 

CoreWeave’s revenue growth is decelerating due to tough comparables. For example, the company put up sky-high growth of 420% in Q1 of 2025, thus making it challenging to sustain a higher growth rate a year later. 

Revenue growth is expected to show a 20% acceleration QoQ in Q4 with revenue growing 139.5% YoY and a further 16 percent acceleration QoQ in Q1 2026, highlighting the strong deals signed in the recent quarters.

CoreWeave revenue growth is projected at 119% in Q3 2025, re-accelerating to 156% by Q1 2026.

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. 

Robust Backlog  

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 is signing new contracts with enterprise customers and AI startups along with expansion with its hyperscaler customers. More recently, the company also expanded its contract with OpenAI by $6.5 billion which brings the total contract value with the company to $22.4 billion. The company had signed an initial contract with OpenAI in March 2025 for $11.9 billion and an expanded contract in May for $4 billion. 

The company’s CEO and co-founder, Michael N. Intrator, highlighted in the Q2 earnings call that the company is signing deals with a diverse customer base, of particular interest is sovereign customers: “We have a tremendous number of sovereigns that are beginning and discussing and talking through how to go about doing this, what technology to use, what software stack to use, where it should be placed right up and down the line. And we are very confident that we will continue to expand our footprint within the sovereign cloud universe.” 

The key takeaways are that the company has strong future growth and it is also diversifying its customer base, as this helps to allay investor fears regarding the high customer concentration. 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.  

Margins 

The company is investing heavily in data center and server infrastructure to meet very strong AI demand from its customers. The management tried to explain in the Q2 earnings call that expenses are front-loaded and have a short-term impact on the margins. However, the Street sold the report as the top line raise did not flow through to the bottom line, causing a post-earnings sell-off.  

Operating leverage will help the company improve margins in the coming years. Furthermore, the company is also expected to have $500 million of annual run rate cost savings by the end of 2027 once the Core Scientific acquisition is completed.  

GAAP profitable in 2027 

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. 

Analysts expect CoreWeave to turn GAAP profitable by 2027 with estimated earnings of $1.59 per share.

Cash, Debt & Capex 

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. 

Management Hinted 2025 Will End Strong 

As stated, CoreWeave currently operates 33 data centers for 470 megawatts of power, yet is going to deliver an additional 400-plus MW of power by the end of the year. This means the year will be back-half loaded, as management made abundantly clear: 

“And so we are very comfortable with the ramp that we are seeing in front of us in order to deliver the 900 megawatts-plus of power as we go through Q4. It is going to be backloaded, as Nitin said. We knew that it was going to be backloaded as we came in. And we're watching the build-out and scaling of that infrastructure very systematically as we continue to move through the year.” 

It was also helpful to hear in the last earnings all that the company has signed expansion contracts with both hyperscalers, with one of those contracts being reported in Q2 already but the other will be reported in the upcoming Q3 earnings report: “One of those contracts was signed in Q2 and is reflected in the Q2 revenue backlog number. The other one was signed in Q3 and will be reflected in our Q3 revenue backlog number.” 

Given the use of the word hyperscaler, this would be in addition to the OpenAI $6.5B announcement.  

CoreWeave’s Buy Plan 

The near-vertical move from CoreWeave’s IPO low suggests the formation of a bullish long-term structure, taking the shape of a developing five-wave pattern. Since the June peak, price action has produced a three-wave pullback, which supports the potential for a larger breakout and a push to new highs. 

Based on the current, limited price history, I am tracking two potential scenarios. Both imply that this correction could ultimately lead to new highs, provided that any additional weakness remains above $61.50. 

• Green – In this case, the market is in the early stages of a new uptrend. As long as any pullback holds above $96.75, we should expect a move back to retest the all-time highs. A decisive breakout above those highs would likely confirm a sustained continuation of the uptrend that originated at the IPO low.

  The current pattern suggests a leading diagonal is in play. This is evident with the overlapping push higher from the September 12th low. We should see this push fail under $155 and then trend back into the $125 – $115 range but holds $114.65. If we instead see a strong push over $155 on expanding momentum and volume, we will then likely attack the $183 – $188 region. Over $188, and we should see the larger uptrend resume.  

• Red – If price breaks below $114.65, and then $96.75—ideally in a sharp, decisive decline—downside targets shift toward the $65 region before a meaningful bounce develops. Under this scenario, any long positions should be managed with protective stops near $61.50.

CoreWeave stock's buy plan by Knox Ridley, Portfolio Manager of the I/O Fund

For more Information: 

Join us this Thursday at 4:30 p.m. Eastern Time as Portfolio Manager, Knox Ridley, goes through in detail the I/O Fund’s plans for buying CoreWeave with a strategy for risk managing the stock while also protecting to the downside. Every week, Ridley discusses the most promising AI stocks, and more.  

The I/O Fund issued 22 buy alerts between March and April of this year, targeting the AI economy. We now have a handful of positions up over 80%, one position up over 100% and two entries up over 300% in 2025.  Our cumulative returns of 210% over a five-year period would place us as #2 if we were a hedge fund and #5 if we were an ETF. Learn more here

Please note: The I/O Fund conducts research and draws conclusions for the Fund’s positions. We then share that information with our readers. This is not a guarantee of a stock’s performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.

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The AI frenzy has investors fixated on revenue growth as proof of returns on AI spending that can be as high as $100 billion per year, depending on the company. Yet, Meta is proving that a stronger signal of AI strength may be found further down the income statement — in the bottom line.  

Without much fanfare, Meta put up a solid earnings report this past quarter as ad impressions rebounded to 11% up from 5% growth; this is a critical metric for the company as management must prove they are reaping the rewards of large capex spending. However, it’s also clear the large capex spend is impacting the bottom line as the company beat by 22% for growth of 38.4%. When adding back the $0.52 tailwind from increasing the useful life of servers, EPS beat by 11.2%. 

There is evidence that both the top line and bottom line can continue to improve as Meta quietly asserts its AI strength come 2026. This quarter, average revenue per person (ARPP) is showing initial signs of bottoming with an important uptick YoY that was absent last quarter when ARPP declined YoY. Secondly, Meta has indicated their internal AI operations will result in lower headcount come 2026 as AI reaches the capabilities of a mid-level software engineer. Combined with a potential inflection point in their ad business, that indicates strong double digit EPS growth will continue in 2026. 

Accelerating Growth in Core Business – Largest Beat in Nearly 4 years

Revenue for the quarter came in at $47.5 billion, beating consensus by $3 billion. While a 5% top-line beat may seem modest at first glance, this was Meta’s largest revenue surprise in 15 quarters. When removing one-time adjustments, EPS beat by 11%, or nearly double the beat seen on the top line. 

Meta’s year-over-year revenue growth shows acceleration from 16% in Q1 FY25 to 21.6% in Q2 FY25, with projections for continued growth above 20% into Q3 FY25.

This quarter’s performance stands in sharp contrast to Q1, when revenue grew a modest 16% YoY, with just a $1 billion beat, and ad impressions were up a muted 5%. In other words, Q2 wasn’t just another incremental improvement, it was a potential inflection point that reset expectations for the back half of the year. It may have also signaled that Meta’s core advertising engine could renew its upward trajectory from the impact of its AI investments. 

Looking ahead, Q3 guidance calls for revenue between $47.5 billion and $50.5 billion, implying another quarter of ~21% YoY growth at the midpoint. If the Company can continue to deliver back-to-back quarters of >20% growth, this should put the narrative of slowing growth in the rearview.  

Sequential Improvement in Margins, up 5 points YoY 

Revenue grew 16% YoY, the slowest rate since Q2 2023 as Meta lapped tough comps. Ad impressions growth decelerated to 5%, with all regions slowing sharply. 

Meta’s operating margin expanded five points year-over-year, rising from 38% in Q2 FY24 to 43% in Q2 FY25, highlighting stronger profitability trends.

Ad impressions rebounded to 11% YoY, more than doubling sequentially. APAC led the way with +16% impressions growth, while US & Canada improved significantly, climbing to +9% from just +4% in Q1. Ad pricing remained firm at 9% YoY, a slight deceleration from Q1 but notable given the acceleration in impressions.  

AI at the Core of Ad Re-Acceleration 

The key driver behind this resurgence is Meta’s aggressive deployment of AI to improve ad efficiency and user engagement. Management highlighted recent upgrades to its ad recommendation system, which now leverages more signals and longer context windows to drive higher performance.  

These improvements had tangible effects in Q2. Ad conversions increased ~5% on Instagram and ~3% on Facebook, reflecting the system’s ability to better match advertisers with the right audiences. Time spent also improved meaningfully, rising 5% on Facebook and 6% on Instagram, which expands available inventory.  

Meta Q2 2025 Ad Impressions Surge: Significant Quarter-over-Quarter Growth Highlights Strong Performance

This dynamic showed up clearly in Meta’s performance metrics. The rebound in ad impressions from +5% in Q1 to +11% in Q2 was the sharpest sequential improvement over a year, driven by strength across regions, particularly in APAC. Despite this surge in volume, pricing held firm, increasing 9% YoY, just a modest deceleration from the prior quarter’s 10% growth. This stability indicates advertisers are seeing higher value per impression, thanks in large part to AI-driven performance gains. 

ARPP also benefitted from these trends, climbing nearly $2 year over year to $13.65, just shy of Q4’s record $14.25. This suggests advertisers aren’t just buying more impressions, they’re paying more for better-performing ones. 

At the center of this success is Advantage+, Meta’s flagship AI ad platform. Advantage+ automates campaign targeting, budget allocation, and creative generation, providing advertisers with a powerful easy-to-use tool that integrates generative AI directly into Meta’s ad ecosystem. The results speak for themselves: Advantage+ is now operating at a $20 billion annual run rate, up 70% YoY. 

Advertisers using Advantage+ report up to 22% improvements in returns on ad spend (ROAS), and adoption continues to climb, with more than 4 million advertisers now using at least one generative AI creative tool.  

According to the most recent earnings call, management stated why they are seeing such rapid growth: "studies show that for every dollar spent with our AI-enabled Advantage+ products, advertisers generate on average $4.52 in revenue for their businesses.” 

Why Meta’s AI Story Stands Apart 

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• The one simple reason that Meta could see a stronger 2026 than currently anticipated 
• Whether Meta’s high capex of $100B run rate is a boon for future growth or a concern for investors to watch out for 
• Looking beyond revenue, what line item we are watching for weakness in 2026 and what needs to happen to offset this

Overall, Meta theoretically has a quick time to market for AI improvements to make an immediate impact on its existing monetization engine; the ad platform. This difference makes Meta’s capex cycle less speculative in the immediate term. While many peers front-loaded their AI spending over the past 12-18 months without a clear timeline for payback, Meta is scaling infrastructure after achieving product-market fit, with clear visibility into ROI. 

Meta also has an unrivaled distribution advantage. Roughly 700 million monthly users already engage with embedded Meta AI features inside Facebook, Instagram, and WhatsApp. More recently, the company announced they reached 1 billion users across their AI services following the launch of the Meta AI app last April 

With 3.4 billion total daily active people across its Family of Apps, Meta can distribute new AI features at scale. Unlike standalone AI apps that must drive user acquisition, Meta can compress the adoption curve dramatically by deploying AI directly into platforms where billions of people already spend time. 

Building the Infrastructure to Match 

Mark Zuckerberg confirmed that the Company is building Prometheus, which will be the first 1+ GW AI Accelerator cluster, slated to come online in 2026. Capex is ramping rapidly to meet these goals. For FY25, guidance now calls for $66-72 billion, up from roughly $40 billion in 2024. 

Meta FY25 Capex Guidance Hits $69B: Market Surprised by Continued Spending Surge

Management also provided visibility into $100 billion in annual capex by 2026, reflecting Meta’s commitment to building out training and inference capacity at unprecedented scale. Unlike earlier cycles, where spending was tied to long-lived assets or speculative projects like the metaverse, this wave of investment is highly focused on shorter-lived assets such as GPUs, networking gear, and data center hardware that directly power ads, inference and generative AI workloads. 

Funding From Strength, Not Dilution

One of Meta’s biggest advantages is its ability to self-fund this ambitious AI buildout. The company generated $25.6B in operating cash flow during Q2, representing a robust 53.8% margin. Free Cash Flow came in at $8.6B, down from $10.3B in Q1 as capex surged, but still massive relative to nearly any other company in tech. 

Cash balance declined to $47.1B, reflecting the Company’s $15 billion Scale AI acquisition, while debt remained steady at $28.8B. Management emphasized that it plans to finance the bulk of its capex internally, while also exploring co-development partnerships for certain mega-projects. This flexibility distinguishes Meta from smaller AI infrastructure players that rely heavily on capital markets to fund growth. 

Margins Stable Today, but 2026 a Watch Item 

Despite the surge in spending, Meta’s margins held strong in Q2. Gross margin held steady at 82.1%, up 80 basis points year over year. Operating margin improved to 43.1%, rising 170 basis points sequentially and 500 basis points YoY, while net margin came in at 38.6%. 

Management did caution, however, that 2026 expenses will grow faster than revenue as depreciation, energy costs, and data center operating expenses rise with the scale of new infrastructure. If revenue lands near $230 billion in 2026, above current consensus of $215 billion, operating margins could dip toward 34-36%, down from ~39-40% today. Even so, Meta’s high cash generation and potential partnerships for data center development give it multiple levers to manage this growth without compromising financial stability.  

Conclusion: 

Meta’s Q2 could quietly become the company’s inflection point after a weak Q1. Impressions rebounded, pricing held firm, and ARPP was up $2 YoY, driving the Company’s largest top-line surprise in nearly four years. Guidance for Q3 sets up another quarter of >20% growth, cementing the case that Meta’s core business is back in growth mode.  

Notably, Meta’s AI spend is already paying off. Its investments are directly linked to revenue growth through its ad platform, creating a virtuous cycle that reinforces itself with every incremental improvement in AI performance. While 2026 expenses will pressure margins in the near term, Meta is entering this next phase from a position of extraordinary strength: a core business growing north of 20%, is cash flow positive even after $100 billion in capex, and offers an AI roadmap that offers quicker monetization.

Following 22 trade alerts between March-April this year, we have a handful of positions up over 80%, one position up over 100% and two entries up over 300% in 2025.  Our cumulative returns of 210% over a five-year period would place us as #2 if we were a hedge fund and #5 if we were an ETF. Learn more here

Please note: The I/O Fund conducts research and draws conclusions for the company’s portfolio. We then share that information with our readers and offer real-time trade notifications. This is not a guarantee of a stock’s performance and it is not financial advice. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis. Beth Kindig and the I/O Fund own shares in META at the time of writing and may own stocks pictured in the charts.

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Nvidia stock faced a rare price target cut last week following a weaker-than-expected Q2 and heightened competition from Broadcom. The company has faced numerous headwinds from China and also production delays in their current generation of GPUs. 

As someone who has tracked Nvidia’s cyclical downturns closely since 2018,the culmination of negative narratives in-between GPU generations is eerily familiar. Needless to say, in the past, Nvidia’s cyclical bottoms were buying opportunities where getting the stock lower helped to increase stock returns in the span of a few months. 

Investors who bought Nvidia stock at the October 2022 bottom have seen more than 10X returns in just three years, underscoring Nvidia’s explosive AI-driven growth. Source: YChartsYCharts

Nvidia’s softer price action this past month is partly due to Broadcom hinting they will see strong AI growth next year. There were some important numbers in the report that we covered for our premium members to help gauge just how much growth Broadcom could see.  

Although I’ve been quite vocal around Broadcom’s importance as a contender on AI accelerators, the chances are low that custom silicon can compete with the powerful and versatile NVL72 systems that Nvidia is shipping now. There will certainly be a time when custom silicon helps to drive down costs for Big Tech, especially around inference. However, it is too early for this to be a serious threat to Nvidia given one of their most important GPU generations to date is (finally) shipping in volume. 

There are other clues that Nvidia’s reign will continue. Prior to the earnings report, I discussed why Big Tech is providing an important green light, stating the capex numbers we saw as recently as two weeks ago are “beautifully packaged” to help guide AI investors on where Nvidia’s stock can go next.

In the analysis below, my firm crunched the hard data on Q2 capex numbers and what is coming down the pipe for Q3. If you are an AI investor like we are, this is an analysis you will not want to miss as the numbers below help to dictate how much room is left in many AI stocks. 

As a final highlight, we are rolling out a brand-new buy plan for Nvidia stock – which is highly dependent on capex growth. When it comes to Nvidia buy plans, many of you are aware the I/O Fund has a strong track record — from our $3.15 entry in 2018, to buying at $10 in October 2022 on the very day the stock bottomed before the AI surge, with real-time trade alerts sent to Members.  

More recently, we stood apart by urging caution just before the DeepSeek news, outlining a “wait to buy” strategy in the analysis “Where I Plan to Buy Nvidia Stock Next” as we anticipated Nvidia could dip below $100. That call paid off, allowing us to secure shares at $95 and $88, again with real-time alerts to Members. 

Below, we present a new buy plan for you below plus a few reasons why I am (once again) saying the Street has Nvidia all wrong. 

Looking back, Q1 Capex was Weak with 2% QoQ Decline 

Before deep diving into Q2’25 growth, let’s contextualize Q1 and why the AI trade was soft earlier this year beyond tariff impacts. Total Capex of $77.3 billion, was up 62.4% YoY from $47.6 billion in Q1’24 but down (2.0%) QoQ when compared to $78.9 billion in Q4’24.  

As seen below, this was the first quarterly decline in capex in 8 quarters, likely triggering some doubts regarding the durability of spend for short-sighted investors.  

In Q1, Big Tech reported a rare 2% decline in capex, pressuring Nvidia’s stock earlier in the year as AI infrastructure spending slowed.

It is important to note that this weakness was broad-based, with three of four hyperscalers declining, signaling a timing issue rather than a fundamental demand problem. During earnings calls, management teams largely cited timing issues and power constraints as the main contributors to the QoQ decline — specifically grid hookups, permitting delays, and PPA negotiations. Needless to say, investors were especially focused on these capex numbers coming into Q2.   

AI Stocks, like Nvidia, set to benefit from Q2 cap-ex acceleration 

In the table below, Big Tech Capex is surging QoQ in Q2 with Alphabet, Amazon, and Meta all spending 24% and up to 30% more QoQ on AI infrastructure. This far exceeded previous estimates which led to further upward revisions of capex guidance for the full year.  

In Q2 2025, Big Tech companies — Microsoft, Meta, Alphabet, and Amazon — accelerated capex spending by 24% QoQ to $95B, raising full-year guidance to $359B. This surge in cloud and AI infrastructure investment is a strong tailwind for AI stocks, including Nvidia.

Q2 hyperscaler capex hit a combined $95.0 billion (+23% QoQ, +63% YoY) with multiple raises and Q3 run-rate signals. Street’s FY25 roll-ups moved from ~$300B to ~$359B (+20% upward revision) and still look light if energization stays on track. These dollars are concentrating in servers / accelerators, DC shells, interconnects, cooling, and networking – setting up a sustained spend momentum into 2026. 

The graph below shows a sharp uptick specifically in Q2 2025 compared to the previous quarter, helping to illustrate why AI spend is not slowing down (quite the opposite). This had an important readthrough for Nvidia and other hardware players like Broadcom. 

Big Tech capex growth is fueling AI infrastructure demand and supports a higher move in Nvidia’s stock.

Below, we take a look at each Big Tech company and what they are individually communicating about the year ahead for AI stocks.

Microsoft Guides Capex 27% Higher than Street Estimates 

Q2 capex totaled $24.2 billion (+13% QoQ, +27% YoY), reversing Q1’s brief dip and setting a quarterly record. MSFT confirmed this was driven by AI data center build-outs, with a heavy mix of short-lived IT gear (GPUs, servers, networking) versus real estate.  

CFO Amy Hood stated in the earnings call that capital expenditures were expected to exceed $30 billion in Q3, driven by “continued strong demand signals”, specifically referencing AI-related services and Azure.   

Azure revenue was reported as a standalone metric for the first time in its latest quarterly report, being stripped out of “Azure and Other Services.” The company stated Azure saw $75 billion in revenue or growth of 34%. For comp purposes, the original segment grew 39% up from 33% / 35% on CC basis last quarter.  

According to the CEO, Microsoft is ahead of other hyperscalers in speed of data center buildouts: “We continue to lead the AI infrastructure wave and took share every quarter this year. We opened new DCs across 6 continents and now have over 400 data centers across 70 regions, more than any other cloud provider. There is a lot of talk in the industry about building the first gigawatt and multi-gigawatt data centers. We stood up more than 2 gigawatts of new capacity over the past 12 months alone. And we continue to scale our own data center capacity faster than any other competitor.” 

The heightened guide was notably higher than both analysts’ expectations at the time and higher than Microsoft’s own Q2 level (~$22.6 billion), marking a sharp step-up for the quarter. FY25 total capex is now expected to reach ~$80 billion, well ahead of original Street expectations of ~$63 billion going into the year.  

Alphabet Q2 is Highest Quarterly Capex Spend Ever 

Q2 capex came in at $22.4 billion, up 30% QoQ & 69% YoY, marking its highest quarterly spend ever. This quarter made a significant step-up as Google accelerated TPU vNext production and bulk GPU orders alongside new data center builds.  

Alphabet raised FY25 capex guide by ~$10 billion, now targeting ~$85 billion versus ~$75 billion previously. Management guided continued sequential growth in Q3, though not the same YoY % step-up seen from ’23 to ’24. Investment consists of Custom TPUs, Nvidia GPUs and Data center shells and land acquisition. Cloud remains a bright spot, with revenue growth up +35% YoY in Q2.  

This elevated spend is highly correlated with Google’s new chip, Ironwood, considered its largest, fastest, and most power efficient TPU yet – designed for both AI training and inference workloads. Although Management has not provided any direct figures around spend, they noted that in April 2025 that Ironwood “ships sometime later this year. We reckon it will be towards the end of the year, perhaps in the fall and maybe even in the early winter depending on how tough manufacturing ramp is.” 

This move signals Google’s ambition to reduce dependence on Nvidia, win AI cloud workloads, and monetize inference at hyperscale. Alphabet’s AI growth engine is monetizing faster than expected, validating its aggressive hardware pipeline.  

Amazon Plays Catch-Up with 29% QoQ Capex Growth 

Q2 capex totaled $31.4 billion, up 29% QoQ and 63% YoY, reflecting a strong ramp in AWS capacity buildouts. CEO Andy Jassy reiterated that AWS demand outstrips supply, with Q2 spend focused on GPU clusters and Trainium/Inferentia ASIC deployments.  

Amazon is now signaling >$118 billion for FY25 capex vs ~$100 billion prior. Management expects Q3 capex to stay near Q2 run rate as new data centers energize and custom silicon ramps. Capex is split between Nvidia GPUs (~196K Hoppers deployed in 2024, growing further in 2025) and Next-gen Trainium 3 clusters. This capex spend is necessary to accelerate growth for AWS to compete in the marketplace, as Azure is currently growing twice as fast and gaining market share. 

AWS remains the core profit driver, with >30% OP income growth for five straight quarters. Market analysts see potential for AWS re-acceleration as Morgan Stanley analysts noted that “Amazon Web Services could experience growth above 20% in 2026 as the company expands capacity to meet increasing demand”. The bank’s analysts now have “more conviction that AWS growth has the potential to accelerate to 20%+ in ’26’” which would be “ahead of our base model and key driver of AMZN’s multiple,” with a base-case valuation of $300 per share and a bull-case scenario of $350.”  

While extremely optimistic on AWS, Morgan Stanley did note that that the company was continuing to operate among “capacity constraints (data center builds, delivery of chips, racks, cables, power, etc.), which our new analysis suggests AWS is working through… which we view is a positive signal of faster AWS revenue growth ahead.”  

Meta Capex up 100% YoY 

Q2 capex reached $17.0 billion, up 24% QoQ & 100% YoY, making it Meta’s largest quarterly spend ever. Sequential growth was driven by server deployments, with data centers and networking also stepping up. Meta tightened FY25 capex guide to $66–72B billion vs $64–72 billion prior. Management emphasized “significant growth” in 2H25, led by servers for AI training/inference and core product refresh cycles. Servers remain the largest driver and largest portion of spend.

In its latest quarter, Management stated that while the “infrastructure planning process remains highly dynamic, we currently expect another year of similarly significant CapEx dollar growth in 2026 as we continue aggressively pursuing opportunities to bring additional capacity online to meet the needs of our AI efforts and business operations.”

Meta’s rapid deployment of custom MTIA accelerators and GPUs positions it as a top-3 AI infrastructure buyer. AI-driven ad optimizations have boosted pricing and are offsetting slowing impression growth, adding incremental ROI to Meta’s infrastructure spend.

FY Capex Guidance: What These Guides Imply for Q3 & Q4 

On the topic of full year guidance, all of these firms have significantly increased the fiscal -year 2025 capitalization budgets, largely due to AI, data center buildouts, and cloud infrastructure. As seen below, coming into FY25, Big Tech was expected to spend $300 billion in capex. Following Q1 & Q2 earnings announcements, these estimates have now shifted to $359 billion.

Alphabet raised 2025 capex guidance to $85 billion, Amazon is projected to exceed $100 billion with analysts estimating $117 billion, Microsoft plans $80 billion in 2025 capex, while Meta narrowed its guidance to a range of $66–72 billion.

Of the Big Tech players, only Microsoft is indicating that growth could moderate:

• Microsoft provided commentary around its capex spend, noting that elevated capex in the first half of its fiscal year (which includes Q3 of calendar year) is due to large finance lease site deliveries and datacenter ramp-ups. This indicates there may be some moderation in H2 growth driven by a softer Q4 figure.
• Meta has continued to raise full year guidance which indicates spend remains elevated, with Ad revenue seasonality and infrastructure ramp-ups likely pushing strong spending into H2.
• Amazon indicated that quarterly capex will “mirror second-quarter spending” so the expectation there is a consistent ~$31 billion spend each quarter, in line with Q2.
• Alphabet will likely distribute spending evenly across H2 to meet its FY capex guide, with potential upside in cloud infrastructure should construction projects advance in Q2.

As shown in the table above, Big Tech capex spending typically skews toward the second half (H2) of the year, supporting stronger growth for AI stocks.

In FY23, H1 represented roughly 45% of total spend while H2 accounted for ~55%. Similar trends exist as we move forward to FY24, as H1 spend accounted for roughly 43% of annual spend while H2 reflected ~57% spend.

If we assume that budgeting systems remain consistent and that H1’25 spend remains within that 43-45% band, that would imply that H2 capex spend of ~$218 billion and full year spend of ~$390 billion, well above current estimates of $359 billion.

AI bulls will point towards this calendar spend cadence as continued fuel for potential upside against current guidance.

What Big Tech Capex Means for Nvidia’s Stock

Nvidia’s Q2 results reported a decline of (1%) for the Compute segment. This alone should have tanked the stock. Instead, we saw a mild reaction because the forward-looking guidance for the Q3 quarter was quite strong. The ramp from Big Tech capex helps to support Nvidia’s strong Q3 guide. That part is key – that Big Tech and Nvidia remain in lockstep, as they have been since the start of the AI boom. 

Sign up for free below to find out the following information: 

• My prediction on when Nvidia will reach a $10 trillion market cap 
• Why a semiconductor trough can often be the best time to buy 
• The I/O Fund’s updated buy plan. We nailed Nvidia buys at $3.15 in 2018, $10 in 2022, and more recently at $95 and $88 after calling for patience ahead of the DeepSeek news. Now we’re rolling out a new buy plan — access for free below.

Prediction: Nvidia Will Reach $10 Trillion by 2028 

Big tech capex will reach mid-$300 billion to high-$300 billion this year with Nvidia downwind from a large portion of this spend.  

The company’s Q3 guidance – supported by strong capex spending – essentially puts the data center on the brink of a $200 billion run rate with $48.5 billion at the midpoint. If Q4 delivers 10% sequential growth, revenue would reach $53.4 billion — roughly 62% higher than analyst estimates from May 2024. That substantial disconnect has been a profitable one for investors who tracked our nuanced analysis. 

Why does this matter? Because hitting a $50 billion quarter this year sets the trajectory toward $75 billion per quarter by the end of fiscal 2027, assuming 50% CAGR across six quarters and 10–11% sequential growth. That would imply roughly 60% growth in the AI segment compared to the most recent $47 billion quarter. This is why we emphasize buying at cyclical lows, even as the market tends to sell semiconductor stocks during the trough. 

In my premium research, I laid out the case for a $200 billion data center run rate — or $50 billion a quarter — followed by $300 billion and eventually $500 billion by 2028. On a 20x forward sales multiple, that path implies a $10 trillion market cap by 2028; an upgrade to my original target of $10 trillion by 2030. 

Our $6 trillion and $10 trillion market cap scenarios remain intact. At a 20x forward sales multiple, $300 billion in data center revenue supports a $6 trillion valuation, while $500 billion supports $10 trillion.  

Analysts don’t see Nvidia hitting the milestone of a $500B data center until after 2033, but I believe it can arrive much earlier by 2028 — especially since AI software will proliferate and is expected to match hardware in size. CUDA plus the AI stack (TensorRT, Triton, NIM, cuDNN and more to come), Enterprise AI software and licensing from robotics hasn’t been fully factored into the consensus. If Nvidia grows revenue at a 30% CAGR between 2026 and 2028, that timeline accelerates by at least five years.  

We’ll adjust our view if the market shifts, but as of now, Q3 guidance puts Nvidia firmly on track toward the $50 billion data center quarter — the first major milestone in the path toward a double-digit market cap. 

Nvidia’s Buy Plan 

Nvidia’s Q3 guide helped to keep the overall trajectory on track, but near-term price action has been soft. The China narrative has been beaten to death, Q2 marked a cyclical bottom as hyperscalers pause before Blackwell ramps, and semis rarely shine at their lows. For now, the AI trade is running on fumes until Nvidia can carry the market again in Q3–Q4.  

Fortunately, we have a buy plan that allows us to capitalize on any softness seen in the stock. 

Nvidia’s Updated Buy Plan 

Since the April 7th low of this year, Nvidia has advanced nearly 100%. The first higher low on April 21st established the trend, which has since accelerated in a near-straight line with only small dips along the way. The structure unfolding aligns with a standard 5-wave pattern, which remains incomplete and suggests at least one additional high before a meaningful correction sets in.

The current decline appears to be a 4th wave consolidation. This pullback should hold above $135 and, once complete, set the stage for a final 5th wave advance toward the $210–$240 region. We are tracking two primary scenarios based on this interpretation:

• Blue Scenario – The 4th wave extends lower into the $155–$135 target zone, providing a potential buying opportunity. The areas of interest are: $155, $152, $146, $138. As long as price action holds above $135, the 5th wave should advance into the $210–$240 range, completing the larger 5-wave structure from the April 7th low. Below $135 and this scenario gets invalidated, which opens the door to a more prolonged period of volatility.
• Green Scenario – The 4th wave was shallow and may already be complete. A breakout above $185 would confirm that the 5th wave is underway, with upside momentum likely targeting the upper range of the $210–$240 target zone.

In both cases, the technical setup remains constructive for another leg higher before a larger corrective phase begins.

Closing Point 

The re-acceleration of hyperscale capex into 2H25 is a powerful sign for investors. While Street estimates are catching up, they still underestimate the scale of AI infrastructure build-out. In the near-term, we are looking for Nvidia to grow 50% year-over-year or about 10% to 11% QoQ on average. Further out, the company must clear 30% YoY growth to reach a $10 trillion market cap by 2028. Given Nvidia’s rapid product road map and the AI software opportunity, this is a low bar for the clear leader in AI.  

The I/O Fund issued 22 buy alerts between March and April of this year, targeting the AI economy. We now have a handful of positions up over 80%, one position up over 100% and two entries up over 300% in 2025.  Our cumulative returns of 210% over a five-year period would place us as #2 if we were a hedge fund and #5 if we were an ETF. Learn more here

Please note: The I/O Fund conducts research and draws conclusions for the company’s portfolio. We then share that information with our readers and offer real-time trade notifications. This is not a guarantee of a stock’s performance and it is not financial advice. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis. Beth Kindig and the I/O Fund own shares in NVDA at the time of writing and may own stocks pictured in the charts.

Recommended Reading:

• Oracle Soars After Earnings – Is ORCL Stock Still a Buy?
• Nvidia Stock Forecast: The Path to $6 Trillion
• Bitcoin Bull Market Guide: When to Hold, Trim, or Re-Enter (Webinar)
• Reddit Stock Blows the Doors Off – Can it Last?

This quarter was less about the headline P&L figures and more about a narrative shift: Oracle’s stockis being re-rated by the market as a hyperscaler and AI infrastructure play, not a slow-growth enterprise software company. The 36% gap reflects a structural repricing based on unprecedented backlog visibility and OCI’s growth trajectory.

The market is clearly excited about this report, and for good reason. 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. The RPO growth was strong enough to negate the miss Oracle reported in the current quarter.

Another key reason that Oracle’s stock is exploding higher despite a lagging fiscal Q1, is that 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. Also, consider that Azure is at $75 billion, which means Oracle and Microsoft will likely be on par with each other over a four-year period for their infrastructure segments.

Given this, there’s no denying that Oracle reported impressive results, yet can the stock continue its run – or has the easy money been made? Below, we look more closely at Oracle’s report plus offer a buy plan that discusses how the I/O Fund – a leading AI tech portfolio – is approaching this stock.

RPO Surges to 359% YoY Growth, up from 83% Last Quarter

Remaining Performance Obligations (RPO) exploded to $455 billion, up 359% YoY. Management also guided that it could exceed $500 billion in the near term with additional multi-billion-dollar contracts, stating: “Over the next few months, We expect to sign-up several additional multi-billion-dollar customers and RPO is likely to exceed half-a-trillion dollars.” This backlog provides unprecedented revenue visibility, locking in future OCI and SaaS growth.

Oracle reported surging RPO, causing the stock to go up 36% from the earnings report.

Oracle Cloud Infrastructure (OCI) Could Surpass the Big 3 with 77% Growth

OCI (IaaS) revenue grew 55% YoY to $3.3 billion, faster than hyperscaler peers. We had pointed out in the analysis “Can Oracle Become the Next $1 Trillion AI Stock” that Oracle was quietly sneaking up on AWS, Azure and Google Cloud with a higher growth rate, stating:

“Though Oracle is growing off a much smaller cloud base than say Azure, robust IaaS momentum could drive its Cloud growth at a much faster rate than the Big 3 – defined as Microsoft, Amazon, and Alphabet — over the next few years.

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.

This rapid IaaS growth could fuel a 40% CAGR for Oracle’s total Cloud growth by FY28, taking its Cloud segment from $24.4 billion to $66 billion. This 40% CAGR will far outpace AWS’ growth in the high-teens, and Google Cloud and Azure in the high-20% to low-30% range.”

The earnings report is especially groundbreaking as Oracle is now forecasting an even higher number than our previous models had indicated. Management raised its guidance to +77% growth in FY26 to $18B, with a clear multi-year ramp to $144 billion within five years.

Our firm had begun to form a picture that Oracle could become more attractive than the Big 3 based on previous estimates of $46 billion in FY2028. As of last night, these estimates are now at $73 billion – suggesting Oracle is becoming a force to contend with.

Oracle’s infrastructure-as-a-service segment (IaaS) is growing faster than the Big 3, putting Oracle’s revenue on a path to contend with traditional hyperscalers.

MultiCloud DB up 1,529%YoY

Over the past 1-2 years, Oracle has been working with AWS, Azure and Google Cloud to offer database collocation, running Exadata and Oracle Autonomous Database within their cloud infrastructure. This allows enterprises to leverage Oracle’s database platforms across a multi-cloud environment without major migrations and lower data egress costs This led to multicloud database revenue with Amazon, Google, and Microsoft surging 1,529% YoY.

Oracle discussed ways that multicloud will continue to grow, citing that multicloud will continue to grow from 37 data centers to a total of 71 over the next several years. These data centers host Oracle’s databases that are embedded into the Big 3 with low latency.

Oracle’s Fiscal Q1 Earnings Results

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. While the headline miss and QoQ contraction might have raised eyebrows in another context, management quickly shifted the focus forward, guiding Q2 revenue growth of 12-14% YoY – an outlook that suggests a rebound and signals confidence that momentum will accelerate from Q1 levels.

Segment Level Results: All Eyes on Cloud

Diving deeper, Oracle’s segment level results highlight a company amid a decisive mix shift. Cloud is the clear growth engine, with revenue climbing to $7.2 billion, up a robust 28% YoY and 7.3% sequentially from $6.7 billion in Q4. Cloud now represents 48% of total revenue, a sharp step up from 42% a year ago – underscoring the Company accelerating mix shift toward next-gen infrastructure and applications. Within the segment, Cloud Infrastructure (IaaS) stood out with $3.4 billion in revenue (+12% QoQ), sustaining hyperscaler-like momentum, while Cloud Applications (SaaS) delivered a steady $3.8 billion (+4% QoQ), anchored by Fusion ERP and NetSuite growth. Together, these results reinforce that Oracle’s transformation is no longer aspiration – the company is increasingly defined by Cloud, not legacy software.

Oracle’s Software revenue came in at $5.7 billion in Q1’26, essentially flat YoY but sharply lower sequentially, making it the primary drag on total revenue this quarter. The decline underscores the continued erosion in legacy licensing which remains a structural headwind. While maintenance and support revenues provide a degree of stability, the segment is steadily losing relevance in the growth narrative. Investors should expect Software to remain a transition burden until Oracle’s cloud scale-up fully eclipses the legacy base.

Oracle’s Hardware revenue was $670 million in Q1’26, essentially flat YoY (+2%) but down 21% sequentially from Q4. While the sharp QoQ decline is a visible drag on top-line optics, Hardware now represents less than 5% of total revenue and continues to shrink in strategic importance. Management has long signaled that the mix shift away from on-prem hardware is deliberate, freeing up resources to scale higher-growth cloud infrastructure. For investors, Hardware is best viewed as a legacy headwind that will gradually fade from relevance, with little bearing on the core thesis around OCI and Saas growth.

Oracle’s Services Revenue reached $1.35 billion in Q1’26, up 7% YoY from $1.27 billion but essentially flat sequentially. This segment provides steady, recurring revenue, anchored by consulting, support, and implementation work tied to Oracle’s enterprise base. While not a growth engine, Services play an important supporting role in the broader cloud story, helping customers migrate workloads and deepen adoption of Oracle’s SaaS and OCI platforms. The real value here is its stickiness – ensuring that once customers enter Oracle’s ecosystem, they are more likely to expand and consume additional cloud services over time.

EPS Split: GAAP Miss, Adjusted Beat

EPS Trends reflect a split narrative, as GAAP EPS missed while non-GAAP EPS beat. Both GAAP and adjusted EPS fell QoQ as the Company leaned heavily into investment mode. Adjusted EPS still showed positive YoY growth, flexing underlying profitability despite the cloud buildout. The market appears to have looked past the GAAP miss because adjusted EPS and cloud momentum underscore the long-term growth story.

• 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. This decline was largely driven by restructuring charges, higher interest expense, and heavy investment.
• 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.

Liquidity Steady, Capex Heavy as Oracle funds the Cloud Buildout

Oracle’s balance sheet and cash flow metrics show a deliberate tilt toward aggressive investment as the company is pulling every lever (e.g. heavy capex, payables management, heavy debt burden, etc.) in the near term to build datacenter capacity and capture OCI demand. Operating Cash flow is growing and outpacing revenue growth slightly, signaling operational effectiveness and economies of scale. Liquidity remains adequate with cash steady at $10B and deferred revenues providing visibility, but working capital is increasingly cloud-contract driven. The tradeoff here is clear: short term FCF pain for long-term hyperscaler positioning.

Next week, we will break down how capex compares to AI revenue for the major hyperscalers plus Oracle – which stock is seeing the highest ROI? Sign up here to get this free analysis in your inbox.Sign up here to get this free analysis in your inbox.

How Oracle Compares to the Big 3

Oracle’s ability to drive lower latency and high performance is one of the main reasons enterprises use Oracle for AI, as it allows enterprise customers to run demanding AI workloads faster and at a lower cost.

RDMA (Remote Direct Memory Access) is helping to drive Oracle’s AI story by enabling direct memory access between servers without utilizing CPUs, resulting in low-latency, high-bandwidth performance. Bypassing the CPU greatly accelerates data transfer rates, a necessity for large AI workloads requiring massive compute.

RDMA is integral to Oracle Cloud Infrastructure as the backbone of Oracle’s Gen2 Cloud and increasingly large Superclusters for AI training and inference, allowing ultrafast, near real-time performance. Oracle says that it can offer less than 10 microseconds of latency between nodes, improving efficiency.

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.”

Last night in the 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 cost $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.”

The Importance of Vectorized Data

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. Oracle noted in Q3 that its Oracle Database 23ai can convert data into any vector format to be understood by an AI model of choice, facilitating AI training and inference on private data in Oracle’s Database.

The announcement of Oracle’s AI database is particularly interesting in terms of the stock extending its run. As explained in the call last night, 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. Here is what was

said: “Then we made it very easy for our customers to directly connect all their databases, all their new Oracle AI databases and cloud storage, OCI Cloud storage to the world's most advanced AI reasoning models, ChatGPT, Gemini, Grok, Llama, all of which are uniquely available in the Oracle Cloud. After you vectorize your data and link it to an LLM, the LLM of your choice, you can then ask any question you can think of. Who's offering that to customers? We'll be the first when we deliver it and demonstrate it at AI World next month.”

After a 35% Gap Up, is ORCL Stock Still a Buy?

After a historic day in the markets with Oracle up 36% after Tuesday's print, the main question that remains is if Oracle is still a buy or has the easy money been made? Considering that RPO is up 359%, cloud RPO is up nearly 500% and multi-cloud database growth is up over 1,500% – it’s well worth the time to look at what the technicals are saying as Oracle approaches a $1 trillion market cap.

Below, we discuss:

• Is Oracle stock still a buy using technical analysis to discuss potential entry points.
• What levels to watch to confirm Oracle still has room to run ahead of a highly anticipated Oracle Cloud World next month.
• The key to Oracle’s stock expanding – which was not in the most recent earnings report, but rather, the two key items that will help drive the stock upward in 2026 and beyond.

The I/O Fund is a leading AI portfolio with 45% allocation to tech stocks going into 2023 before Wall Street caught onto the potential of AI, yet this stands at an 87% allocation to AI stocks today. With cumulative returns of 210%, we’d place #2 if we were a hedge fund and #5 if we were an ETF.

The Key to Oracle’s Stock Expanding is Two-Fold 

There are a few key reasons Oracle stock can continue to expand: 

1. AI Database: 

Oracle is teasting a more beefed-up AI database, which management stated will officially launch at Oracle World Cloud next month, 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.  

HeatWave Gen AI is another piece to Oracle’s AI database offerings, as it combines systems for analyzing data. By combining systems, AI can run queries faster and cheaper compared to when data scientists have to use many different database systems. For example, HeatWave can theoretically replace a larger stack, such as AWS AI, Snowflake and Databricks, with the goal of lowering internal complexities for data engineers and also helps to lower costs. 

The inference market will defined 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. 

Next month, Oracle is expected to expand its Oracle AI Database, which is designed to combine large language models – such as ChatGPT, Grok, or Gemini – with customers’ private databases and automated agents to help increase the depth of what models can achieve for enterprises. Oracle has already released many features for AI databases, yet management teased an announcement for next month’s Oracle World, hinting they will be offering more agentic AI.  

Where Oracle is in a unique position is the company can keep private data secure, vectorize the data to be better understood by an AI model, while bundling the full-stack data layer with the public cloud and foundation models. It's a combination of lower costs, lower complexity and combining publicly available data with private data that is setting Oracle on a longer runway than what the market may be initially realizing – and yes, that statement includes the 36% move. 

2. Look for Margins to Expand 

If we assume the AI Database becomes a catalyst for Oracle, the likelihood of margin expansion is a key reason the stock could have more horsepower.  

In the near term, Oracle is deliberately trading margin for growth as margins compressed QoQ across the board. Heavy restructuring and datacenter investments clipped profitability in the short term but underlying gross margin stability and YoY gains in adjusted income exhibit how Oracle is scaling Cloud while keeping structural profitability intact.  

Longer term, the expectation is that margins should expand as the Company benefits from deploying AI databases across multicloud environments. 

Here are the current operating metrics: 

• Q1 GAAP Gross Profit of $10.6B, down QoQ from $11.2B in Q4 but up compared to $9.4 in Q1’25. This represents a 71% gross margin, up from 70% in prior quarter and in line with 71% in prior year quarter. 
• Q1 GAAP operating income was $4.3 billion, down from $5.1 billion in Q4 but up from $4.0 billion in Q4’25. Q1 figures represent a 29% operating margin, down from 32% in prior quarter and 30% in prior year quarter.
• Q1 Non-GAAP Operating income was $6.2 billion, down from $7.0 billion in Q4 but up from $5.7 billion reported in Q1’25. Q1 figures represent a 42% operating margin, down from 44% in prior quarter and down compared to 43% in prior year quarter.

  This contraction is likely to resolve from a higher mix of AI database revenue – and that is where there could be more alpha for this stock

• Q1 GAAP Net Income was $2.9 billion, down from $3.4 billion in Q4 and in line with $2.9 billion reported in Q1’25. Q1 figures represent a 20% net income margin, down from 22% reported in prior quarter and down from 22% in prior year quarter. 
• Q1 Non-GAAP Net income was $4.3 billion, down from $4.9 billion reported in Q4’25 but up from $4.0 billion reported in prior year quarter. This represents a 29% adjusted net income margin, down from 31% in Q4’25 and 30% in Q1’25.

What the Technicals Say about ORCL Stock: 

The earnings gap today is the key driver for the current setup. When we see a vertical price move like the one following earnings, which is backed by maximum volume and momentum, it strongly suggests we are in the middle of a 3rd wave advance. This points to two bullish scenarios:  

Green Scenario (Large 3rd Wave Breakout):  

In this case, the rally from the April low into the July high represents wave 1. Today’s breakout would confirm wave 3, setting the stage for further upside with pullbacks along the way. The projected wave 5 targets fall in the $850 – $1000 range.  

Blue Scenario (3-Wave Uptrend):  
Here, the runoff the April lows was wave A, followed by a shallow B wave correction in July/August. The current move would represent wave C, with targets in the $394 – $567 zone.  

Key Supports  

For this trend to remain intact, the following levels should be monitored:  

• $306 – First warning level; a break below here raises doubts about higher prices, but does not invalidate anything.  
• $273 and $261 – Critical supports. As long as these levels hold, the broader uptrend remains valid, and the market should continue trending toward the target region. 

Conclusion:

The I/O Fund initiated its position in Oracle because the inference market has not really kicked off yet. Some refer to this as early innings, but I would argue it's pregame. This conviction on timing is reinforced by Oracle’s latest earnings report, which showed a blowout in OCI growth and RPO, yet the current quarter fell short of expectations with a 6% QoQ decline. Even though Oracle fell shy of consensus estimates for the current quarter, the backlog and visibility point to robust AI-driven demand ahead. From a technical perspective, the stock also sets up for potential upside, creating what we see as a compelling risk/reward profile for investors. 

The I/O Fund is a leading AI portfolio with 45% allocation to tech stocks going into 2023 – the highest allocation of any firm on record at the time, and today, this stands at an 87% allocation to AI stocks. With cumulative returns of 210%, we’d place #2 if we were a hedge fund and #5 if we were an ETF. Premium members receive real-time trade alerts, weekly webinars, deep dives on lesser-known AI stocks and more. Learn more hereLearn more here

Please note: The I/O Fund conducts research and draws conclusions for the Fund’s positions. We then share that information with our readers. This is not a guarantee of a stock’s performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.

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Two years ago, the April 2023 quarter delivered a historic 18% beat, followed by an even bigger 30% beat in July 2023. Compare that to the most recent quarter ending July 2025 — just a 4% beat, the smallest in two years. The narrowing beats combined with a rare QoQ decline in the Compute segment could be interpreted as Nvidia is running out of steam. 

I am frequently asked by notable media anchors if Nvidia could be topping, and as you’ll see below, I substantiate why Nvidia is not running out of steam. I spoke with Charles Payne from Fox Business and Caroline Hyde from Bloomberg, followed by a 45-minute interview on the topic with Maggie Lake of Wealthion. In these conversations, we discussed some of the most pressing issues that AI investors face – does China revenue matter for Nvidia, how does the world’s most valuable company continue to grow, are we in an AI bubble, and lastly – where is the I/O Fund positioning next.  

For those new to my firm, the I/O Fund is among the top-performing AI portfolios globally. Our track record was built in part by taking a significant Nvidia position years before the market embraced the AI story, with allocations as high as 10–20%. While our calls on Nvidia are well recognized, we’ve also held a number of lesser-known AI winners that together have driven a cumulative return of 210%. To put that in perspective, if we were a hedge fund, we’d rank #2 — and if we were an ETF, we’d rank #5. 

What that ranking should communicate to you is that the I/O Fund does not rest on our laurels, we rigorously pursue a portfolio positioning that will outperform. Let me rephrase this to say that my firm will not continue to hold Nvidia out of fandom, rather, we will continue to hold Nvidia only if we believe the stock continues to offer alpha. 

Below, I explain why this stock has the potential to outperform the indexes — and how we’re positioning to capture even greater returns from lesser-known stocks that are riding Nvidia’s momentum.  

Is There Alpha Left in Nvidia (NVDA) Stock? 

After being crowned the world’s most valuable company with a market cap over $4 trillion, it's natural to wonder if the easy money has already been made. For investors, the debate comes down to whether Nvidia can keep outpacing both the Nasdaq and its semiconductor peers given its phenomenal run. 

Regardless of market fluctuations, Nvidia’s product road map is not slowing down. As described in the videos below, Nvidia is on “the eve of releasing its next generation of GPUs” combined with its enviable software platform CUDA and strong QoQ growth in AI networking (NVLink, Spectrum-X, InfiniBand).  

In the interview below with Charles Payne of Fox Business, which took place ahead of earnings, I offer key reasons that Nvidia continues to offer alpha as we head into calendar year 2026 and why we plan to buy the stock on any dips.

I also had the opportunity to talk to Maggie Lake of Wealthion on the importance of Nvidia and why the company is moving from its 2.0 era to the 3.0 era, and how this transition from server-scale to a rack-scale AI systems company is key as to why Nvidia has further room to run. In the clip, I also describe the opportunity that Nvidia is poised to capture that will be as large as the AI hardware opportunity.  

The AI Bubble: Fact or Fiction 

Fears as to whether AI is reaching bubble territory were ignited this past month when Sam Altman compared AI to the dot-com era, stating: “When bubbles happen, smart people get overexcited about a kernel of truth. If you look at most of the bubbles in history, like the tech bubble, there was a real thing. Tech was really important. The internet was a really big deal. People got overexcited.” 

Given OpenAI is seeing about $20 billion in revenue as of now with no profits, it makes sense that Altman would be concerned about valuations. However, a lack of profits is certainly not Nvidia’s concern. The company had a GAAP operating margin of 60.8% in Q2 and an adjusted operating margin of 64.5% with over $13 billion in cash flow for the quarter. 

There is clearly a bifurcation in the AI economy as some companies must spend heavily to compete, while others are profiting heavily from the steep competition.  

In as lucid of a manner as possible, I break down in the videos below the following: 

• Why technically every tech trend goes through a boom/bust, why this should not scare investors off, plus the strategy investors can use to successfully win with surging tech trends 
• What companies are more insulated from the effects of a bubble and why AI software like OpenAI is at higher risk 
• The differences between an enterprise technology and a consumer technology in terms of how AI will repay Big Tech capex 

Nvidia’s Stock Can Reach $6 Trillion Market Cap by Next Year  

In an interview that went viral with Caroline Hyde of Bloomberg, I discussed why it’s important to not focus too closely on quarterly earnings reports for determining Nvidia’s growth potential, and to rather focus on GPU generations.  

If we look at the revenue potential for quarterly data center revenue once Blackwell and Blackwell Ultra ship in volume, this leads us to a $6 trillion valuation by next year.  

Predicting 50% upside may not seem like much given Nvidia is up 325% since early 2024 and up 4,000%+ since my firm first bought the stock in 2018 – however, there is a chance investors have an opportunity to get Nvidia lower.  

For example, as recent as January of this year, my firm predicted Nvidia would dip below $100 – this was published before the DeepSeek news hit. This afforded our followers a better entry, leading to higher upside. Next week, we will be updating our buy plan for Nvidia for free. Don’t miss it by signing up for our weekly newsletter here.

The Inevitable AI Trend that will Profit Most from Nvidia’s Upcoming Generation of GPUs 

Nvidia 1.0 was defined by the company's lead in gaming, whereas Nvidia 2.0 was defined by the introduction of Tensor Cores with Volta. These cores evolved through Ampere and the Hopper generation, ultimately leading to the transformer engine and more precision support for accelerating AI compute. The market eventually caught onto the enormity of the AI market as Hopper facilitated more accurate GenAI applications coming to market. You can read more about this history in the analysis: “Here’s Why Nvidia Will Reach a $10 Trillion Market Cap by 2030.”

Looking forward, what I am dubbing as “Nvidia 3.0” will be the shift from 8-GPU server-scale systems to 72-GPU rack-scale systems — which is augmented with the back-to-back release of Blackwell and Blackwell Ultra. Nvidia’s new rack-scale systems will mark one of the most significant turning points in its history. Regardless of what market participants think about Big Tech’s surging capex spend, the spend will continue to rise as those who get the NVL72 systems (that are beginning to ramp now) will have a critical advantage over those still on the HGX or DGX systems with 8 GPUs. 

There is one inevitable trend that will profit most from the upcoming generation of GPUs, with significant momentum from Nvidia’s new rack-system architectures. This 5X to 9X opportunity that is already beginning to take shape with material evidence of the momentum.  

Don’t miss out on what a leading AI portfolio and analyst team is saying about where to position next to take advantage of AI’s next major move.   

AI Networking is the #1 Opportunity from Nvidia’s Upcoming GPUs 

Under the hood, what defines the upcoming generation of GPUs from the previous generation is AI networking. When you move from 8 GPU severs to 72 GPU rack-scale systems, your intra-rack networking shifts as does the rack-to-rack for larger clusters due to higher GPU density. For example, we’ve seen hyperscalers plan to deploy 1 million GPU clusters by 2027-2028 up from clusters with 10s of thousands right now. Therefore, both scale-up and scale-out architecture are going through a rapid transformation on the networking side.  

In the video below, I discuss why the I/O Fund is concentrated in AI networking stocks as our #1 trend right now: 

Conclusion: 

Nvidia and its ecosystem of suppliers are the best way to position for the rest of 2025.  While headlines were fixated on China, the bigger story is clear: H20s contributed about $4B, while Blackwell generated an estimated $28B this past quarter — over a $100B run rate. This is why my stance has been to focus on GPU generations to track the AI opportunity rather than quarterly earnings or any single geographic area for seven years and counting. Semiconductors are particularly tricky as the cyclical bottom can often be the best time to buy.  

Keep an eye out for the I/O Fund's new buy plan for Nvidia, hitting inboxes next week. Our last buy plan provided an entry under $100 when the market felt the stock was invincible. This led to entries with real-time trade alerts at $94.48 and $87.99 with real-time trade alerts sent to our Premium Members.

For 2025, the I/O Fund has worked to identify key Nvidia suppliers with Blackwell on deck to ramp significantly, sharing our in-depth research on stocks within the AI networking stack. We hold high allocations in two specific Nvidia AI networking suppliers. 

Sign up to join our upcoming webinar, held every Thursday at 4:30 pm EST, where we discuss buy zones for AI stocks and more. Learn more hereLearn more here

Please note: The I/O Fund conducts research and draws conclusions for the company’s portfolio. We then share that information with our readers and offer real-time trade notifications. This is not a guarantee of a stock’s performance and it is not financial advice. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis. Beth Kindig and the I/O Fund own shares in NVDA at the time of writing and may own stocks pictured in the charts.

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In this post, we examine the AI platform, products, and other driving forces behind ServiceNow’s (NOW) beat-and-raise earnings results for Q2, plus: 

• ServiceNow’s evolution from a provider of SaaS solutions for IT service management to an agnostic AI platform aspiring to impact nearly every facet of the enterprise. 
• The company’s impressive QoQ acceleration across subscription revenue, margins, RPO, and large deal activity. 
• The cost of meeting AI demand through cloud infrastructure costs, and the news of a deal for multi-billions in cloud commitments through 2030. 
• Plus, who’s really winning the race in AI enterprise. 

Last month, after ServiceNow reported second quarter results that exceeded expectations on multiple fronts, shares of NOW rose by 6%. The company is attempting to reposition itself beyond a provider of cloud-based digital workflows to what they are calling “the AI-powered operating system for enterprise transformation.”  

Yet, the market is cautious as the stock is down nearly 20% YTD and lags other AI software stocks – our analysis below looks at the puts and takes weighing on the stock. 

ServiceNow’s Q2 Results Help to Sustain AI Narrative 

As CEO Bill McDermott enthusiastically delivered highlights from his company’s second quarter on the call, he echoed the company’s marketing with repeated use of the word “any,” as in the ServiceNow platform’s ability to integrate with any data, any workflow, any tech stack, any cloud and hyperscaler, any AI agent and LLM, any system across the enterprise, in any industry. McDermott is confident that his firm is delivering the unified solution to what he says is the #1 focus of leading enterprises and CEOs—AI transformation. 

Many tech companies talk about their all-in-one platform as the be-all, end-all solution for every challenge facing the enterprise, but ServiceNow has the metrics to warrant watching the stock closely in future quarters. Most notably, Q2 2025 total revenue of $3.215 billion, representing 21.5% YoY growth in constant currency, up from 20% last quarter for an acceleration of 150 bps. The 150 bps acceleration in total revenue gives credence to McDermott’s statements that the company is seeing increased customer demand for AI transformation solutions, as well as strong execution across sales and product teams.    

In addition, ServiceNow reported subscription revenues of $3.1 billion representing 21.5% YoY growth. This is up from $3.01 billion last quarter for QoQ growth of 3.3%. The current RPO of $10.9 billion represents growth of 21.5% YoY and is up from $10.3 billion last quarter for QoQ growth of 5.8%. Total RPO was $23.9 billion up from $22.1 billion last quarter for YoY growth of 25.5% and QoQ growth of 8.1%. 

In Q2, ServiceNow guided for growth of 20% to 20.5% on subscription revenues yet current RPO growth is expected to lag at 18.5%. Typically, it’s best if cRPO growth exceeds subscription revenue growth. Notably, free cash flow is lumpy between quarters yet the company has a sizable free cash flow margin regardless at 48% last quarter and 16.5% this quarter. In both quarters, FCF expanded on a YoY basis. 

For full year guidance, guidance was reaffirmed for subscription gross margin to hold steady at 83.5%, operating margins at 30.5%, and free cash flow margin at 32%—indicating confidence in long-term profitability and efficiency. 

Now Assist Sees AI Deals Grow 50% QoQ 

ServiceNow also delivered strong numbers showcasing momentum in large deals and increased annual contract value (ACV). In Q2, AI deals were up 50% QoQ, including 89 deals with $1 million in net new ACV. There are 528 customers that now have more than $5 million in ACV, a 19.5% YoY increase. The number of customers with more than $20 million ACV grew by 30% YoY, representing strong relationships with top customers. ServiceNow has also shared that 85% of the S&P 500 are actively using ServiceNow’s platform or services. 

The primary driver of the increases in deal size and volume is Now Assist, the company’s flagship generative AI suite of applications, agents, LLM, and customizable tools built directly into the NOW platform. Now Assist drastically simplifies AI integrations and makes it easy for non-technical people to work with, talk to, manage, and customize all the AI capabilities available on the platform. The key components are Skills, which can be thought of as customizable building blocks for performing tasks like summarizing incidents or suggesting next steps in processes; AI Agents, which are autonomous agents with reasoning and planning capabilities extending far beyond chatbots, including the ability to automate tasks, solve problems, and proactively manage workflows; and Agentic AI Orchestrator, which acts as a coordinator with and manager of other agents and systems, not just from ServiceNow but from other companies, too. 

Here is what was stated on the earnings call: 

“Our beat and raise quarter showcases the mission critical nature of the ServiceNow AI Platform. Every business process in every industry is being refactored for agentic AI. ServiceNow has never been more differentiated as a full-stack agentic operating system for the enterprise.” 

ServiceNow confidently reiterated its goal of reaching $1 billion in ACV from Now Assist by 2026. The I/O Fund foresees this being an important moment for the stock as few AI midcap software stocks have reached this scale. The company has this confidence due to agentic AI, and also due to Now Assist unifying additional solutions, workflows and data across multiple enterprise productivity tools—ITSM, CSM/CRM, HRSM, DevOps, Sales, and more.  

Another key product in the generative AI suite is AI Control Tower, a centralized command center and single-pane-of-glass orchestration layer for managing, optimizing, and governing AI across the enterprise. Launched earlier this year, AI Control Tower allows third-party applications to integrate seamlessly into the ServiceNow platform, and it provides the business context organizations need to connect AI initiatives to core business services and technologies in the rest of the tech stack. It provides AI lifecycle management, real-time reporting, risk and compliance monitoring to help organizations scale AI responsibly and efficiently.  

McDermott referenced AI Control Tower during the earnings call Q&A when he was asked to explain the success the company is having at the C-level and to define the one asset that will help ServiceNow win in the long run. He described AI Control Tower as the governance piece that unifies so many of the other apps and AI solutions organizations are juggling, minimizing the pain and complexity of integration including vendor management that enterprises have been facing for the past 50 years.  

As today’s enterprises race to transform and consolidate every aspect of their business through AI, leaders are struggling to choose, let alone integrate, 10, 15, 20 or more components of the tech stack, with new AI offerings rolling out and vying for inclusion every day. AI Control Tower can manage systems and other agents from other companies, not just ServiceNow’s. The agents need managing just like people do, McDermott added.   

Within two months of its launch, AI Control Tower surpassed the company’s internal targets for the entire year.  

ServiceNow’s Stock Sells Off Due to Cost of Scaling AI 

The day after its Q2 earnings release, shares of NOW retracted 3% as a regulatory filing revealed the company is set to spend $4.8 billion in total commitments for cloud infrastructure through 2030. The largest partner among the cloud providers is Google, for $1.2 billion over the next five years. 

With leadership bullish on Now Assist reaching its goal of $1 billion in ACV by 2026, the company appears to be preparing to report AI revenue independent of other revenue sources. Given the run rate above and assuming no acceleration, we consider the spend net neutral as the ACV would net very little ($800M in 4 years). The market will want to see ACV higher than this to offset the spend. 

The disclosure of $4.8 billion in cloud commitments share a similar narrative as the $85 billion annual cloud capex lift that Alphabet guided to last week —AI demand is skyrocketing, and so are the costs of meeting it. This is a dynamic that investors should factor in when assessing any stock in the AI sector. 

Find out the Top Enterprise AI stock we like better … 

This quarter, one enterprise AI stock reported commercial RPO that was so high, it’s nearly inconceivable. Commercial RPO represents the value of contracted commitments; so, in other words it’s revenue that has not yet been recognized but is in the pipeline to be recognized over the next few years.  

The reported Commercial RPO from this Top Stock coupled with its growth rates puts this company on track to see anywhere from $100 billion to $200 billion in AI revenue by the close of the decade — which would represent a significant milestone that only Nvidia has reached. Find out what the Top Stock is below. 

Sign up for free below to get Beth’s latest write-up on the world’s leading AI software stock.

To access more in-depth analysis and AI growth stock recommendations, join tens of thousands of investors who are already following Beth and the I/O Fund.

Microsoft FYQ4: One of the Strongest Earnings Reports in Multi-Decade History 

Recently, in the Top 15 AI Stocks analysis it was stated “If Nvidia holds the crown in the AI hardware arena, then Microsoft holds the crown in the AI enterprise arena.” Tonight, Microsoft proved why the AI Enterprise crown is rightfully theirs. 

Management came out swinging this evening on multiple fronts. First off, the acceleration in Azure and Other Services to 39% up from 35% last quarter was significantly higher than expected, with the Street calling for growth of 33.7%. To grow nearly 40% at this scale is impressive.  

Microsoft also revealed its Azure revenue number for the first time of $75 billion for FY2025 (although not entirely surprising as we were modeling for Azure to be hitting $80 billion very soon). From there, the CFO guided for 37% growth in Azure for next quarter – indicating continuing a high growth rate at scale will not be a problem in the near-term (note, H2 is expected to see lower growth than H1). 

However, if we look at Commercial RPO, it’s clear something big is going on. Last quarter, we pointed out that Commercial RPO was the one key metric we were watching, stating: “Commercial RPO growth above 30% suggests that Microsoft’s stock could (finally) resume strength again.” At the time, RPO was at $315 billion, up 34% and 33% on a constant currency (CC) basis.  

This quarter, Commercial RPO has accelerated to $368 billion, up 37% and 35% on CC basis. Microsoft’s Commercial RPO was in the mid-$100 range in 2022-2023 period to help illustrate how quickly contracted revenue has grown. Wow. We do not typically see such large growth rates on such a large RPO base. It’s almost inconceivable.  

A few years back, I described in detail why AI is first and foremost an enterprise technology, specifically calling out Microsoft’s path to $100 billion in AI revenue by 2027. We are seeing this materialize now. Microsoft is putting formidable distance between itself and best-of-breed cloud players. To illustrate, stocks like Confluent are down 27% after hours following the loss of a large customer.  

In addition to the key metrics stated above, management carries a sense of confidence  when analysts question the ROI on capex. And when Mark Zuckerburg boasted about building a gigawatt-plus cluster called Prometheus next year, Satya made sure to lead his introduction by saying “We stood up more than 2 gigawatts of new capacity over the past 12 months alone.” You’ll find more commentary on this below. 

Revenue – Azure reported as standalone segment for first time 

Revenue was up $76.4 billion for growth of 18% or 17% in constant currency. This is up from last quarter with growth of 13% or 15% in constant currency and beat consensus of $73.83 billion. For the fiscal year ending in June, the company reported revenue of $281.7 billion, up 15%.  

Azure revenue was reported as a standalone metric for the first time, being stripped out of “Azure and Other Services.” The company stated Azure saw $75 billion in revenue or growth of 34%. For comp purposes, the original segment grew 39% up from 33% / 35% on CC basis last quarter.  

Below, you can see the visible acceleration in overall revenue

Below you can see that 39% is the highest growth rate we’ve seen in some time for Azure and Other Services:

Looking forward, management guided for revenue of $75.25B at the midpoint, beating consensus of $74.15B. This would represent growth of 14.7%. 

According to the CEO, Microsoft is ahead of other hyperscalers in speed of data center buildouts: “We continue to lead the AI infrastructure wave and took share every quarter this year. We opened new DCs across 6 continents and now have over 400 data centers across 70 regions, more than any other cloud provider. There is a lot of talk in the industry about building the first gigawatt and multi-gigawatt data centers. We stood up more than 2 gigawatts of new capacity over the past 12 months alone. And we continue to scale our own data center capacity faster than any other competitor.” 

Revenue segments – Cloud has highest growth rates since 2022 

Cloud reported some of its highest growth in three years. The CEO stated: “Through software optimizations alone, we are delivering 90% more tokens for the same GPU compared to a year ago” as well as “ 

• Microsoft Cloud was up 27% and up 25% on CC basis for revenue of $46.7B. This marks the highest quarterly growth rate since CY2022 
• Gross margin was 70% up 100 basis points from 69% last quarter 
• Productivity and other Businesses was $33.1 billion, up 16% and 14% on CC basis.  
• Intelligent Cloud was up 26% and up 25% on CC basis for revenue of $29.9 billion. This was the highest growth rate since CY2022 
• More Personal Computing was up $13.5B for growth of 9% 

Commercial Bookings Surpasses $100 Billion for the first time 

To help support the case for future growth, both commercial bookings and commercial RPO came in surprisingly strong.  

The CFO stated that for the first time commercial bookings surpassed the $100 billion mark, increasing 30% on CC basis. Commercial RPO increased to $368 billion, up 35% on CC basis with 35% recognized in revenue in the next 12 months. 

Additional key metrics: 500 trillion tokens processed last year; 800M AI Product Users 

Azure is always the main metric looked at, yet we should pause and share a few more important key metrics in this banner report. 

• Copilot apps have surpassed 100 million monthly active users across commercial and consumer.  
• Across broader AI features, there are over 800 million monthly active users. 
• Foundry Agent Service is now being used by 14,000 customers to build agents.  
• 80% of Fortune 500 use Foundry, processing 500 trillion tokens, up 7X YoY.  
• Microsoft Fabric is a data and analytics platform for AI workloads, with revenue up 55% year-over-year and over 25,000 customers. According to management: “It's the fastest-growing database product in our history.” 
• There are 20 million GitHub Copilot users. GitHub Copilot enterprise customers increased 75% quarter-over-quarter and 90% of the Fortune 100 use GitHub Copilot.

Margins & Earnings 

EPS of $3.65 beat consensus estimates of $3.38.  

• Gross margin was 68.5% up from 68.1% last quarter for gross profit of $52.4B. 
• Operating margin of 44.9% was up from 44% for operating profits of $34.3B. 
• Net margin was 35.6% up from 34.9% last quarter for net profits of $27.2B. 

Cash flows & capex raised to eye-watering $30B per quarter  

• Operating cash flow of $42.6B was up 15% YoY 
• Free cash flow of $25.6B was up 10% YoY 
• Capex of $24.2 billion was up 27% YoY with management guiding for capex of $30 billion next quarter.

Earnings Call Q&A: 

Capex Spend Correlates to $368B in RPO: 

Every Big Tech company will be asked about ROI on capex spending, and the CFO handled the question quite well, stating: “when you think about the full year comments I've made on CapEx as well as the Q1 guidance of over $30 billion, you first have to ground yourself in the fact that we have $368 billion of contracted backlog we need to deliver, not just across Azure but across the breadth of the Microsoft Cloud. 

So in terms of feeling good about the ROI and the growth rates and the correlation, I feel very good that the spend that we're making is correlated to basically contracted on the books business that we need to deliver and we need the teams to execute at their very best to get the capacity in place as quickly and effectively as they can. 

And so when you look, and we've talked about the growth rate [of capex] will decline year-over-year, but at its core, our investments, particularly in short-lived assets like servers, GPUs, CPUs, networking storage, is just really correlated to the backlog we see and the curve of demand. And I talked about, my gosh, in January and said I thought we'd be in better supply demand shape by June. And now I'm saying I hope I'm in better shape by December.”

Conclusion: 

This was an earnings report for the ages – simply because the Commercial RPO is massive, and Microsoft is proving they can grow at a scale we haven't seen yet in AI software. Earlier today, I had stated on Bloomberg that Microsoft could see $40 billion in AI revenue sometime in 2026 – which is a massive number, but what's most important is the rapid ascent in reaching that number.  

If you zoom-out, a few years back I've made the case that Microsoft could see as much as $100 billion in AI revenue by 2027 and then I upped it to $200 billion by 2028.  Should we see this ballpark figure, it would mark a rapid ascent hard to fathom a few years back. This earnings report is a step in the right direction to meet that mark.

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Please note: The I/O Fund conducts research and draws conclusions for the Fund’s positions. We then share that information with our readers. This is not a guarantee of a stock’s performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.

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In this post, we take a deeper look at Google's earnings results for Q2 and share our thoughts on:

• Earnings results for Google Search and updates on the battle between Gemini and ChatGPT
• Google Cloud’s results, and what the increase to capex means in competitive context
• Threats to Google’s ecosystem—the one serious concern that remains for Google Stock
• Who benefits from Google’s $85 billion capex and the AI growth stock we like better than Alphabet

On May 7th of this year, during the Department of Justice’s antitrust trial against Google, Apple's Senior Vice President of Services, Eddy Cue, revealed in his testimony that Safari searches declined for the first time in 22 years. Mr. Cue attributed the decline to the rising popularity of AI-powered search and assistants such as OpenAI’s ChatGTP, Perplexity AI, xAI’s Grok, and Anthropic’s Claude. On the topic of the eventual transition from traditional search to AI-powered alternatives, Cue added, “There’s enough money now, enough large players, that I don’t see how it doesn’t happen.”

In response, shares of Alphabet fell 9%, erasing an estimated $140 billion in market value.

Since then, investors have been awaiting Alphabet’s Q2 earnings to provide clarity around the issue—and it has, at least for Google’s Search business. But other questions remain in terms of one area Google is losing major real estate, which we discuss below.

Search reported 12% YoY revenue growth of $54.2 billion, helping drive Alphabet’s total revenue to $96.4 billion, up 14% YoY. While OpenAI’s ChatGPT, Perplexity’s new Comet browser, the Department of Justice, and others deserve continued monitoring, Google’s resilience in this space is impressive.

On the Q2 earnings call, Alphabet stated that Google is successfully integrating AI Overviews into its core search experience. With 2 billion monthly users across 200 countries, AI Overviews contribute 10%+ additional queries for the searches in which they appear. For Google, this represents a value add and engagement driver, not a disruption.

Google’s Gemini and ChatGPT are battling to become the AI assistant of choice for consumers. To compare, Gemini has reached 450 million MAUs, up 100 million from March of this year, with daily requests surging 50% over Q1. But according to Google’s own data shown in court back in March of this year, ChatGPT had an estimated 600 million MAUs, and likely many more by now. Gemini is gaining ground, though still lags behind ChatGPT.

Alphabet also reported on its launch of AI Mode—a new option displaying as the first tab in Google’s main search menu, next to All, News, Videos, Images, and the rest—in the U.S. and India. The company said AI Mode has already amassed 100 million MAUs.

Capex Now 40% Higher Since the Start of 2025

While Google Cloud revenue reaccelerated four points to 32% to $13.6 billion—a welcome beat considering Q1 had seen a 2-point sequential deceleration —the big news on Cloud is the reported $10 billion increase to capex, now up to $85 billion. This is 40% higher than the $60 billion capex estimate coming into the year, signaling Alphabet's willingness to spend on AI to drive accelerating cloud growth.

Similar to Oracle stock, this surging capex is weighing heavily on free cash flow, and will likely continue to pressure free cash flow in the upcoming quarters. Operating cash flow rose just 4% YoY to $27.7 billion in Q2, yet free cash flow declined (61%) YoY to $5.3 billion. While TTM free cash flow is still up 10% YoY to $66.7 billion, the market is forward looking, and this capex hike implies TTM free cash flow will continue to trend much lower over the next few quarters.

It is understandable why Alphabet is willing to increase its capex, as it is beginning to witness increasing operating leverage in Google Cloud and seeing AI usage proliferate across its core Search business. For example, AI Overviews now serves 2 billion users and processes 980 trillion tokens monthly, doubling since May, a scale which helps explain the explosive compute costs driving Google’s massive investment in Cloud.

Cloud operating margins have expanded significantly, up more than nine points from 11.3% to 20.7%, as operating income rose 141% YoY to $2.8 billion. Prioritizing AI investments in an effort to drive Cloud growth of >30% could see the segment reach a $120 billion run rate by mid-2028, more than double its $54 billion run rate this quarter. Should operating margins begin to expand towards the high-20% to 30% level by mid-2028, versus AWS in the high-30% range, Cloud could generate $30 billion in annual operating income, or more than 3x from today.

This represents more than one-quarter of current company-wide operating income, or a potential massive driver of profitability in the future — the point here is that Alphabet is essentially sacrificing some FCF growth in the near-term and spending heavily in an aim to reap the rewards of a much larger, fast-growing Cloud segment in the future.

Another market reality adding pressure to Google’s Cloud and AI initiatives is the fact that Microsoft Azure has already set a high bar and is leading the race to monetization by a substantial margin. Whereas Google processes huge volumes of tokens—980 trillion, a figure that has doubled since May of this year—Microsoft’s deeply established enterprise relationships with hundreds of millions of users has unlocked user and revenue growth.

Microsoft’s fiscal Q3 report helped cement the company as the strongest AI player in the hyperscale crowd due to its focus and dominance across enterprise software offerings and deep AI integrations aided by its partnership with OpenAI.

I/O Fund covered Microsoft’s impressive Q3 2025 earnings and Azure’s outperformance on May 15th, which you can read for free here: Microsoft Stock Surges After Q3 2025 Earnings: What Separates Azure from AWS, Google CloudMicrosoft Stock Surges After Q3 2025 Earnings: What Separates Azure from AWS, Google Cloud 

One Serious Concern Remains for Google’s Stock

The intense regulatory pressure on Google to open its ecosystem, even as leading AI assistants are knocking on the door, is a lot for Google to overcome. The DOJ’s proposed remedy—Alphabet divesting itself of the Chrome browser—comes as rivals like Perplexity, OpenAI, and Anthropic are developing assistants that can integrate with other Android apps. The pressure on Google to open its ecosystem is mounting, and the competition is already finding their way in.

Primarily, it’s the loss of Google Search being the default search engine on Samsung devices that poses a larger threat to the company, in our opinion. This is because any loss of real estate – especially on mobile – during a time when there are fierce rivals only creates more headwinds for the stock.

As was reported in early June, Samsung is entering a deal with Perplexity to become the default AI search engine on their devices. According to sources such as Bloomberg, Samsung plans to preload the Perplexity AI assistant and app onto its smartphones, with its AI search built directly into Samsung’s Internet Browser. There could also be AI-powered operating systems built later down the line for multi-agent platforms. This shift could happen as soon as 2026.

Here are a few of the key developments that could lead to Google Search losing market share on mobile, specifically, in the next 1-2 years:

• OpenAI, Perplexity, and Anthropic are developing assistants that can integrate with other Android apps, undermining Gemini usage on devices.
• OpenAI has expressed interest in acquiring the Chrome browser to boost already strong usage of ChatGPT, while Perplexity recently launched its own agentic browser, Comet.
• On April 1st, Google signed a new, non-exclusive agreement with Samsung that includes no restrictions on the smartphone manufacturer loading alternative search products. 
• Anthropic recently introduced the ability of its Claude assistant to integrate with Google Workspace, and OpenAI will soon introduce its own assistant that can connect with Android apps and Google Workspace.
• While Google is also in talks with Apple to integrate its Gemini assistant with Siri, Google Search is unlikely to enjoy the "default" status that it has enjoyed for many years on iPhones, given that Apple is also in talks with other AI rivals.

The takeaway is that Google’s ability to leverage one of its key distribution channels during the generative AI revolution is already compromised. The real threat kicks in when Android smartphone users have the choice to opt for third-party digital assistants over Gemini—subsequently undermining Google’s advertising revenue growth.

One Stock that Will Benefit from Google’s $85 Billion Capex

As I pointed out in the Bloomberg interview above, the best way to position is with stocks that directly benefit from Big Tech’s increase in capex.

While Alphabet is still a very solid business with the major advantages outlined in this analysis, its $85 billion capex commitment could require years to generate meaningful returns in the Cloud. Therefore, we prefer to invest in companies that benefit strongly from capex over those that spend heavily on capex.

Keep in mind that some companies will benefit from capex across all of Big Tech – therefore, the $85 billion from Google is just the start to the tailwinds for specific AI hardware stocks. Investors should factor in there is similar spend from Big Tech: Alphabet, Amazon, Meta, Microsoft and Apple.

Below, my firm outlines a direct beneficiary of Google’s enormous capex spending – which was increased 40% this year alone and was raised $10 billion in the most recent earnings report. After all, one stock’s loss is another stock’s gain.

For investors hungry for more near-term growth, we recommend Broadcom (AVGO) as it directly supplies tensor processing units (TPUs) to Google.

Alphabet is a primary custom silicon chips (ASICs) customer for Broadcom, with HSBC estimating the giant will account for nearly three-fifths of Broadcom’s ASICs shipments in its fiscal 2026.

With Alphabet’s newest TPU version, Ironwood, expected to carry a premium $13,000 ASP, versus Broadcom’s other customers at ~$5,000 , this could drive a 128% YoY increase in ASICs revenue to $28.4 billion (not including AI networking). Alphabet’s capex increase in Q2 further cements this story into Broadcom’s AI growth thesis for next year.

Why Big Tech Is Chasing Cheaper Inference

For the providers in the AI ecosystem, monetizing GPUs depends on inference, and thus revenue becomes a function of GPUs and tokens and profits become a function of cost. Nvidia’s Blackwell offers a massive leap in performance and can train models such as Meta’s Llama 3.1 405B in as little as 27 minutes, yet the cost advantages offered by custom silicon can translate into higher margins in the long run from lower inference serving costs. 

For example, Google recently announced that its upcoming seventh-gen TPU Ironwood is its “most performant and scalable custom AI accelerator to date, and the first designed specifically for inference.” Ironwood comes in two sizes, a 256 and a 9,216 chip configuration, with the larger size offering up to 42.5 exaflops of performance.

Google adds that Ironwood offers 2x the performance per watt as last-year’s generation Trillium, with 6x more HBM and 4.5x the HBM bandwidth. This allows it to deliver more capacity per watt at a time when power is a primary constraint, and provide customers with more cost-effective AI workloads.

This is exactly what Broadcom sees arising from this inference growth curve, as CEO Hock Tan asserted that the company has quite a bit of visibility into “increased deployment of XPUs next year, much more than we originally thought and hand-in-hand with it, of course, more and more networking.” The necessity of networking in larger clusters means demand is likely to remain robust even given custom silicon will not keep pace with Nvidia’s merchant sales into the hundreds of billions.

Higher-than-expected deployments of custom silicon combined with strong demand for networking should provide robust tailwinds for AI revenue growth beyond 2026. Broadcom currently has enough visibility to place possible demand acceleration for 2H 2026 on the table, and this could easily persist through 2027 and beyond should inference demand flourish and as the path to 1 million accelerator clusters materializes.

Assuming Broadcom can maintain another 60% YoY growth in FY27 on stronger demand and potential conversion of its 4 current prospects, AI revenue would close in on $50 billion, or up to 60% share of revenue. Even if growth then slows to 30% YoY in FY28, Broadcom would still be more than doubling its AI revenue to $65 billion in just three years.

Broadcom Reports 170% YoY Growth in AI Networking

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.”

Q3’s guidance was ahead of some analyst expectations for $4.9 billion in AI revenue in the quarter, ticking higher as Google’s TPU v7p (Ironwood) begins to ramp. Q3 would also mark the largest sequential growth in over a year on a dollar basis, at ~$700 million.

Additionally, analysts look to already be penciling in further strength in Q4, with Bernstein’s Stacy Rasgon suggesting that Broadcom could be eyeing $5.8 billion in AI revenue in Q4 assuming it sustains 60% YoY growth. Given that Broadcom’s 1H revenue was up more than 57% YoY, this seems a reasonable assumption, especially considering management is eyeing near 60% growth in FY26.

More importantly, 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.

Despite this weakness extending into Q3 with revenue expected to be flat QoQ at $4 billion, semiconductor revenue is accelerating – growth accelerated from 11% to nearly 17% in Q2, with the $9.1 billion semiconductor revenue guide pointing to an acceleration to nearly 25% growth in Q3.

Should non-AI revenue soon find the bottom and begin to recover, this will provide support for continued Semiconductor growth. However, any persisting weakness in non-AI stemming from this elevated consumer and Apple exposure that AI revenue must absorb presents a real risk that investors should keep in mind through the rest of the year. Broadcom is also one of the more exposed semiconductor companies to China with tariffs, with more than $10 billion in revenue from the nation in fiscal 2024. 

Broadcom Stock to See Lift from AI Inference

Broadcom is aiming to capture growing inference tailwinds, with management explaining that the recent surge in inference demand is driving increased confidence in their FY26 AI revenue growth rate.

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.

Valuation is Too High for Broadcom

Broadcom is a key beneficiary of Google’s capex yet the stock is richly valued.

On the top-line, Broadcom trades at nearly 22x forward revenue, a 5% premium to Nvidia’s 21x multiple. AVGO stock was at a 14% premium heading into Q2’s earnings. This is also 85% higher than Broadcom’s 5-year average 11.8x forward revenue multiple.

On the bottom line, Broadcom trades at 43.8x forward earnings, an 8% premium to Nvidia. Broadcom has strong margins – 65% adjusted operating margin and 52% adjusted net margin – driving strong EPS growth, at a 25% expected CAGR through FY27; however, the custom silicon ramp presents some headwinds to gross margin as it grows its mix share.

To find out key levels the I/O Fund plans to buy Broadcom next, consider joining our 1-hour webinar on Thursday at 4:30 pm EST – plus the one thing the CEO stated that all investors must hear in this article “This Stock is Set to Surge from Inference Demand” reserved for premium members only.

For 2025, the I/O Fund has worked to identify key Nvidia suppliers with Blackwell on deck to ramp significantly, sharing our in-depth research on the AI networking stack. Sign up to join our upcoming webinar, held every Thursday at 4:30 pm EST. Our cumulative 5-year results would place us #2 if we were a hedge fund and #5 if we were an ETF. Learn moreLearn more

Please note: The I/O Fund conducts research and draws conclusions for the Fund’s positions. We then share that information with our readers. This is not a guarantee of a stock’s performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.

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