I/O Fund Called the Bitcoin Selloff: What Liquidity & DXY Data Predict Next

Posted on November 28, 2025June 30, 2026 by io-fund

Within crypto, there are perma-bulls and perma-bears, but both are too emotional and dogmatic to consistently participate in Bitcoin’s epic swings. Bitcoin and crypto have consistently tested investors by doing the exact opposite of what the herd is expecting.

Last August, my firm, the I/O Fund, offered a rare explanation of how Bitcoin is sensitive to investor sentiment patterns and global liquidity trends, thus predicting the asset could be topping in an article for our free newsletter readers entitled “Is Bitcoin’s Bull Run Nearing a Top? What the Herd Missed at $16,000 and is Missing Now”

In that article, I stated …

“…the system that helped us identify the $16,000 bottom in Bitcoin is telling a more complex story. Global liquidity appears to be stalling and setting up for a reversal. This is historically not good for Bitcoin and tends to coincide with major tops. This inflection point lines up with our Technical Analysis that has us in the final leg of the multi-year bull market.”

This is the core differentiator of our approach: we analyze Bitcoin not as a belief system, not as ideology, not as emotion — but as an asset driven by sentiment patterns, that also operates within a global liquidity machine.

Today, the buzz word is “liquidity” and how it’s draining from global markets, causing volatility in risk assets. This is not a surprise to our readers, as we have been discussing liquidity dynamics for months, as it is one of the few data-driven dynamics that can help predict Bitcoin’s swings. We even hosted a free webinar to the public in August alongside WealthUmbrella, explaining how these dynamics are threatening Bitcoin’s advance higher.

Since our free webinar, Bitcoin has dropped ~37% and even broke one of our critical supports. We followed through with four sell alerts to our premium members as Bitcoin traded between $95,000 and $113,000, securing exceptional gains and reducing our Bitcoin exposure by 80%. We did something similar with altcoins.

However, looking forward, we could see more volatility before Bitcoin resumes its leadership to all-time highs. If you hold Bitcoin or have large unrealized gains, this is a crucial moment. The technical picture has shifted, increasing overall risk, with a scenario where we head lower. Our analysis breaks down the exact support levels that must hold, the scenario for a final push to new highs, and the path that would confirm a deeper downturn.

Global Liquidity and DXY: The Inverse Relationship Driving Bitcoin's Cycles

Since the market peak in late October, “liquidity” has become a buzzword, casually invoked as though its meaning were universally understood. Instead, liquidity is one of the most overused – and least understood – terms in financial markets.

Liquidity refers to the availability of capital in the system—specifically, how easily businesses, consumers, and financial institutions can obtain cash or credit. But when it comes to actually positioning a portfolio through different liquidity regimes, how this impacts risk-on assets often gets lost in translation.

In modern markets, liquidity is inseparable from debt dynamics. It is not the creation of new debt that dominates capital flows, but the ability to roll over existing obligations. In fact, three out of every four global financial transactions are related to debt refinancing, not expansion. Moreover, nearly 80% of global lending now requires collateral, typically in the form of high-quality, low-volatility assets like U.S. Treasuries.

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This creates a framework where liquidity—and by extension, risk appetite—is dictated by how cheaply and easily borrowers can refinance without overextending their own balance sheets. The more capital that’s freed through this process, the more capital can rotate into risk-on assets such as Bitcoin.

A few key variables influence a country’s liquidity conditions:

Central bank policy
Fiscal spending
The Treasury General Account (TGA)
Federal Reserve repo operations
Broad equity market performance
Bond market volatility

Collectively, these forces determine whether capital and confidence flow into the system or are pulled out. An internal calculation we have created at the I/O Fund, which incorporates all of these factors, can be seen below. Domestic liquidity has broken through the 2022 low, driven predominantly by questionable FED policy, the Reverse Repo Operations at $0, and the Treasury General Account remaining elevated due to a shift in public financing policy.

I/O Fund chart showing Domestic Liquidity (WALCL) levels falling below the critical 2022 lows, tracked via Reverse Repo, TGA Balance, and Fed’s balance sheet, signaling increased downside risk for risk assets and equities.

Even with Domestic liquidity in free fall, there is one factor that is the most important when discussing this topic – U.S. Dollar.

Roughly 64% of global debt is denominated in USD—which means foreign borrowers who accessed cheap U.S. capital must continue sourcing dollars to service that debt. When the dollar weakens relative to their local currencies, less local currency is needed to meet dollar obligations. This frees up capital that can chase higher-yielding risk assets, including Bitcoin.

This inverse relationship between the U.S. Dollar Index (DXY) and Bitcoin has been both consistent and predictive across cycles:

I/O Fund chart comparing Bitcoin's price to the U.S. Dollar Index (DXY), demonstrating that every major Bitcoin bull market occurs during a declining dollar, and bear markets coincide with a rising dollar.

In the above chart, three dynamics are evident:

Every major Bitcoin bull market occurred during a declining dollar.
Every significant Bitcoin bear market coincided with a rising dollar.
The steepness of the dollar’s trend often defines the magnitude of Bitcoin’s move in the opposite direction.

In August, we approached a critical inflection point. The Dollar Index had been in a clear downtrend since peaking in late September 2022—just weeks before Bitcoin bottomed. The most recent leg of this decline in the dollar shows a completed five-wave structure, typically the final phase of a correction before a reversal. Momentum is starting to shift upward, and a sustained break above $101 on the DXY would confirm a major low and the onset of a new dollar uptrend.

However, if we analyze the technical pattern in DXY, as long as DXY stays below $101, there is a setup where it drops to new lows. – likely targeting between $93 – $89.

I/O Fund Technical Analysis of the U.S. Dollar Index (DXY) showing potential final 5th wave drop toward $93-$89. The chart highlights the critical $101 resistance level and uses momentum indicators to predict an imminent move lower, increasing global liquidity and likely pushing Bitcoin higher.

Note how the current bounce is not a direct move higher. It is a messy, and overlapping push higher, which is characteristic of corrections within a larger trend – in this case, pointing lower. Furthermore, the momentum indicators point to a rare overbought condition, while also showing that momentum is fading the higher we go. This is what we see at the end of swings, suggesting a move lower is imminent.

If DXY fails under $101, and the following drop is a more vertical and aggressive drop lower, then we could see an extended drop in DXY to new lows, which would increase global liquidity, and by extension, should push Bitcoin higher.

Having correctly called the U.S. Dollar Index low earlier this year, we noted that, “Until DXY can break above $101, it can still make another low, which will further support higher prices in Bitcoin. The takeaway here is to note that the U.S. dollar is closer to a major low than most think. While it can extend further, and likely will, once we get evidence of a major trend reversal, this should line up with a topping process in Bitcoin. Until then, we can and should see Bitcoin continue an upward trajectory.

Bitcoin Price Drivers: Why Sentiment and Technical Analysis Beat Fundamentals

Bitcoin is unlike stocks. There are no earnings reports, no 10-Ks, no revenue models, no management teams to evaluate, and no real competition—despite occasional claims that alternatives like Ethereum could challenge it. The reality is simple: Bitcoin has already established itself as the definitive digital store of value.

Thematic investing also suggests that the positive news developments are tailwinds for Bitcoin that should support higher prices from here. In fact, we are hearing the same today – A favorable administration that is supporting Bitcoin, as well as a strategic Bitcoin reserve being established. These are both bullish narratives for Bitcoin, which should logically support higher prices. However, if we look at history, Bitcoin has an uncanny inclination to do the opposite of what the news-based narrative at the time suggests. In other words, it likes to top on bullish news and bottom on bearish news.

Chart comparing Bitcoin Price to major news events, demonstrating that movements are driven by market psychology and technical analysis patterns—like the five-wave pattern—rather than fundamentals or bullish narratives.

So, if narratives do not seem to affect price, what actually drives its price? One of the major drivers of crypto is sentiment, which can only be measured through the lens of technical analysis.

Sentiment is simply analyzing herd mentality, which manifests in repeatable patterns. It is a powerful force in the markets. When you funnel human consciousness into a quantifiable system like public markets, strange patterns emerge and they emerge time and time again on all timeframes, on all markets and going back throughout history. Patterns like triangle, bull flags, bear flags, head and shoulder patterns, cup and handle patterns, are very common technical analysis patterns that gauge where the herd is likely moving next.

The most important pattern within technical analysis is the five wave pattern, which we have discussed in the clip below. It underpins all of this and is what marks a trend.

The clip below from our Free Bitcoin Webinar further explains the importance of a 5-wave pattern in markets…

I/O Fund Portfolio Manager Knox Ridley analyzes two potential scenarios that could push Bitcoin to a major top in the $200,000 range following the current pullback.

The fact that a clear 5 wave uptrend has completed off the 2022 low, with the final push moving higher on decelerating volume, had us quite concerned. The most likely path forward has been higher, which I presented in our August report – yet this has now been invalidated, forcing me to create a more unconventional path higher. While this path is possible, it is not probable, based on the technical outlook alone.

I/O Fund Technical Chart: Bitcoin's 2022 Bull Cycle has completed a full Five-Wave Pattern, with weakening Volume and RSI trends signaling increased market risk. The breaking of key support levels below $74,440 suggests a major warning for the bulls.

However, if any break lower can hold over $74,440, then this path is valid and worth monitoring, especially if we see DXY break lower. We could even see this drop push toward $67,000 in an extended move. However, below $67,000 and there is no path higher, before seeing an extended bear cycle take us back into the $40,000 region or lower.

What is also concerning can be seen in the volume and momentum patterns above. Note how volume has always expanded as price went higher, then contracted as price corrected. This is a healthy trend and one we have used to time buys along the way.

However, since the April low in 2025, we have reversed this trend. Volume has been decelerating as price went higher, and now it is expanding as price moves lower. This is not a healthy trend and is signaling that sellers are starting to show up in force.

This is further backed by the RSI breaking through its bull market support. Note how each correction found a low when the RSI bottomed out around 33. This support has held throughout the bull cycle. However, it recently broke this support, which is not what we typically see in bull cycles.

We are not only seeing critical supports break in Bitcoin, but the volume and momentum trends are shifting in real time. Technicals alone are flashing big warnings for the bulls, which has us in a much more defensive posture than any time during this bull cycle.

Regarding the bull scenario, we would need to see a vertical push over $114,000 before the odds start shifting in that direction. If this happens, we will continue our game plan to trade Bitcoin in its final swings of the epic bull cycle that started in 2022.

If you are sitting on outsized gains from Bitcoin or wondering how to professionally incorporate risk management into your process, join us Thursdays for our premium webinars. In the weekly webinars, we discuss what we are doing with our crypto positions in real-time.

For a limited time, get up to $250 off with one of our biggest sales of the year starting Nov 28th. For more information on our annual sale, click hereclick here.

On-Chain Analysis by WealthUmbrella: A Healthy Ecosystem held Hostage by ETF Flows.

We’ve consistently relied on WealthUmbrella’s top-tier On-Chain Analysis throughout this cycle. Their model flashed a buy alert in December 2022, around the same time our own system showed a major opportunity in Bitcoin. The below section was contributed by Vincent Duchaine of WealthUmbrella, who sees higher levels before a cyclical top for Bitcoin.

Since the new bull cycle in Bitcoin started in December of 2022, we are seeing the largest price drop within this cycle, which is currently greater than -35%. Strangely, and unlike any period of notable volatility we have experienced in the last 3 years, the on-chain health of Bitcoin simply does not warrant the size of this drawdown.

While we are seeing a healthy on-chain ecosystem, what is driving the current period of volatility is ETF selling. We were expecting this dynamic at some point, because the hype around the BTC spot ETF created an unusually tight correlation between Bitcoin and the stock market. In that environment, Bitcoin was unlikely to thrive while market breadth was deteriorating and signaling a risk-off shift.

This new dynamic has linked Bitcoin to the state of the equity market, which could see another leg lower. However, our cyclical indicators suggest that we are likely not experiencing a cyclical top, and any further volatility could be considered a mini bear phase, within a larger bull cycle, like we experienced in 2013 and 2021.

For example, new non-zero-balance addresses remains quite healthy. People are still joining the network at a steady rate.

WealthUmbrella’s On-Chain Analysis chart showing Bitcoin's network adoption remains healthy and strong, evidenced by a steady increase in new non-zero-balance addresses despite the recent -37% price drop in the bull cycle.

Furthermore, this is happening while the sentiment of people who hold Bitcoin as an actual crypto asset on the blockchain remains far from bearish. Not only is the influx of new participants on the blockchain still very healthy, but whales have also been aggressively buying the dips.If we look at holders controlling more than one hundredth of the total supply (around 200,000 BTC), their balances have actually increased since the end of October.

WealthUmbrella On-Chain Chart illustrating significant Bitcoin Whale accumulation (approx. 110,000 BTC) during the recent price drop, contrasting underlying network strength with masking ETF outflows and signaling seller exhaustion.

In fact, their accumulation — roughly 110,000 BTC — is almost identical to what they accumulated during the “Tariff correction” earlier this year (about 120,000 BTC). These are not signs of desperation, and it’s entirely possible that the scenario where whales ultimately come out on top of this correction will play out once again.

The issue is that ETF outflows are masking this underlying strength. That being said, ETF balance sheets have already shrunk by about 4% in native units (from 1.362 million BTC to 1.307 million BTC), on top of a decline of roughly 36% in value at the worst point. Not only do we expect the stock market to rebound somewhat, but Friday’s flush happened on noticeably lower BTC ETF outflows, which is a classic pattern of seller exhaustion.

WealthUmbrella chart of Bitcoin Spot ETF Net Inflow/Outflow shows recent volatility driven by ETF selling, with a notable slowdown in outflows signaling potential seller exhaustion and a shift away from a full cycle top.

Now, as we sit nearly $10k above the recent low, it’s clear that we are at least in a bounce. The question is whether this is just a bounce or the beginning of a renewed bullish trend?

According to our analysis, while ETF dynamics are creating a new risk in our models, we are simply not seeing the type of signals that coincides with a cycle top. We created four cycle top indicators, which monitors different layers of the Bitcoin ecosystem. None of these indicators have reached levels that is consistent with a true euphoric/overbought top consistent with prior major tops.

WealthUmbrella On-Chain Chart showing Bitcoin Cycle Top Indicators remain below euphoric/overbought levels, suggesting the current volatility is due to ETF selling and not consistent with a final cyclical Bitcoin top consistentwith the end of bull cycles in Bitcoin.

The current correction, as shown above, has a unique dynamic, which is the result of ETF adoption. The volatility we are experiencing is being driven mostly by ETF selling and is a stark reminder of the risks associated with Bitcoin. Even in a neutral on-chain environment — not a bearish one — ETFs selling just 4% of their holdings triggered a 35% drop in price. This highlights how illiquid the market has been over the last few months. It’s something that has concerned us since 2022, when the proportion of long-term holders on the blockchain became extraordinarily high (the share of coins unmoved for a year peaked at 71% at the end of 2023). Bitcoin’s strength back then was that nobody was selling, unlike in 2017 when everyone was instead eager to buy. ETFs brought back a bit of that demand dynamic, but it became clear that unless euphoria returns on-chain, Bitcoin will remain tightly correlated to stock-market risk-off movements and may suffer from liquidity shortages during equity corrections. In our view, the long-term risk of holding Bitcoin will diminish once the balance between ETF-driven buying and on-chain buying normalizes, and once Bitcoin’s strength relies less on a pure hodler mindset and more on a healthy, rotating, and liquid market.

In Conclusion

Bitcoin is undeniably the most lucrative asset in market history with an astronomical return of over 100,000%. Even if you missed day one, there have been many opportunities to participate along the way. This is where our firm has excelled as we have a strong track record of trimming near local tops and loading back up at lower prices. This can significantly shift total return.

For example, while many chased the 2021 hype with $200,000 or $500,000 price targets, we took a disciplined approach—cutting crypto exposure by half to lock in gains at $58,000. We then went on record stating Bitcoin was a strong buy at $16,000. From there, we continued to highlight Bitcoin as a buying opportunity in six additional free articles (here, here, here, here, here) all the way through October of 2024. We didn’t just talk about the early stages of the bull cycle—we acted on it, issuing 12 buy alerts to our premium members as Bitcoin advanced from $25,000 onwards.

Beginning in August, our tone changed. We began to warn that the risk in Bitcoin was rising, even though the same talking heads that missed the lows were telling us the rally was just beginning. Since then, we’ve released two articles outlining this increased risk (here, here), and even hosted a free public webinar, just before Bitcoin dropped 35%

No investor is perfect — rather our results reflect a disciplined, data-driven approach that has delivered a track record surpassing many of Wall Street’s most recognizable firms. That same framework informs our AI research, including a leading AI-energy position up ~500% this year.

If you’d like to see the exact stocks we own — including weightings, real-time trade alerts, and the in-depth research that attracts Tier-1 media coverage — we invite you to take advantage of our Black Friday Sale.

Take advantage of the I/O Fund’s largest sale of the year with up to $250 off Advanced Market Signals, which offers Knox’s weekly webinars, real-time trade alerts, and in-depth analysis on the most powerful tech trends. Learn more here.Take advantage of the I/O Fund’s largest sale of the year with up to $250 off Advanced Market Signals, which offers Knox’s weekly webinars, real-time trade alerts, and in-depth analysis on the most powerful tech trends. Learn more here.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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Cloudflare: Revenue Accelerates to >30%, Key Metrics Strengthen

Posted on November 28, 2025June 30, 2026 by io-fund

Cloudflare’s fundamental profile strengthened in Q3 with the company reporting its fastest revenue growth rate in seven quarters, returning to >30% YoY territory, while a majority of key metrics all accelerated in unison.

Outside of the financials, Cloudflare remains very well positioned for AI inference, though inference does not yet contribute meaningfully to revenue. Discussion on GPU utilization rates was fruitful and highlighted how Cloudflare can remain in near lock-step with demand while avoiding capacity constraints and with relatively low capex.

Management also believes that versus the hyperscalers, they have a strong TCO advantage when it comes to inference, and in the future, the network will be one of the best places to run inference requests. Cloudflare also shed more light on Act 4, its Pay Per Crawl feature, which will enable creators to be monetized for AI data scraping, and while it is quite early, it is aiming to solve a quickly emerging pain point.

Material Evidence of Revenue Reacceleration, Driven by US and Enterprise Clients

Cloudflare reported its largest beat since Q1 2022, reporting revenue of $562.0 million in Q3, 3.1% ahead of estimates as growth accelerated nearly three points to 30.7%. On a QoQ basis, revenue accelerated to 9.7% from 6.9% last quarter.

The US is emerging as a primary driver for this reacceleration, with growth rebounding 10 points sequentially, from 21.7% YoY in Q2 to 31.5% YoY in Q3. US revenue jumped 12.2% QoQ versus a 7.2% QoQ increase in Q2.

Additionally, Cloudflare’s enterprise cohort, or customers contributing >$100K ARR (and likely primarily US-based) are another key factor behind the reacceleration. >$100K ARR customers drove 73% of revenue in Q3, or ~$410 million, rising 42% YoY and 13% QoQ. This was a sharp 12 point acceleration in YoY growth from 30% in Q1, to the fastest growth since Q1 2023, while QoQ growth was the highest since Q2 2022 at 13%.

Q3 also marked Cloudflare’s first >30% growth quarter in the past five and its fastest revenue growth in the last seven quarters. This is the first step in confirming a sustained revenue acceleration, yet the more important piece is showing that >30% growth can actually be sustained for multiple quarters.

For Q4, Cloudflare guided for revenue of $588.5 to $589.5 million, a slight deceleration to 28% on the topline. This was ahead of estimates for $580.8 million. Interestingly, consensus estimates, just one day following earnings, moved from $589 million to $617 million, suggesting analysts are increasingly optimistic on the company’s ability to sustain this revenue acceleration, supported by strong key metrics.

For FY25, Cloudflare boosted its revenue guidance to $2.142 to $2.143 billion, a $28 million increase from its prior guide. This points to YoY growth of 28.3%, a slight deceleration from 28.8% growth in FY24.

Key Metrics Strengthen, Aided by Enterprise Transition

Despite a lack of meaningful AI contribution, other key metrics strengthened significantly in Q3 and support this material reacceleration story. Cloudflare cited its shift from a product-led, SMB-focused company to an enterprise sales company as a primary driver behind the improvement in key metrics.

There are a few reasons that this focus on enterprise clientele is important for Cloudflare’s growth story, with the simplest being that visible acceleration of enterprise customer revenue in Q3 translated to the material topline reacceleration. Enterprise customers are also likely to expand much quicker than SMBs – for example, Cloudflare noted that accelerating QoQ and YoY growth in its >$1M and >$5M customer cohorts acted as a significant tailwind to DBNRR, which rose five points sequentially to 119%, the highest since Q4 2022.

This DBNRR expansion is also linked to Cloudflare’s Pool of Funds billing approach, which provides a seamless vector for large customers to explore adoption of Cloudflare’s 55 products under a single contract, and allocate funds to different products based on consumption. While management explained that the rollout initially created some downward pressure on DBNRR, consumption of these deals acted as a tailwind to DBNRR this quarter. CFO Thomas Seifert added that POF is “now low double-digits of ACV” and gaining share in the quarter.

Enterprise traction is also showing up in RPO, which accelerated four points to 43% YoY to $2.14 billion; on the other hand, current RPO decelerated three points to 30% YoY and accounted for 64% of RPO.

Management explained that this RPO acceleration “points to primarily 2 drivers, the customer quality and the platform expansion. We are seeing exceptional strength with our large customer cohorts, specifically those that spend more than $1 million or $5 million with us, both delivered record growth this quarter. And in addition to that strength is increased consumption of our large Pool of Fund customers, demonstrating I think, the increasing strategic importance of our platform for those large enterprises globally. And in addition to that, our Workers platform, the developer platform, including Workers AI, is just providing to be a significant new vector for long-term commitment and with that growth.”

Moving forward, it will be important to see consistent strength in both DBNRR and RPO as further evidence that Cloudflare’s large customers can continue to support >30% revenue growth.

Bringing GPU Utilization up to 70-80%

GPU utilization can easily be overlooked, but arguably it is one of the most important discussions for Cloudflare, as its value proposition is inherently tied to executing workloads for customers quickly, efficiently, and with a strong TCO advantage.

Management provided a more extensive discussion on utilization than they have in recent quarters, hinting that they can potentially improve utilization rates further and quickly bring more capacity online to meet demand without becoming capacity constrained.

From our free newsletter in February 2025 recapping Q4 results, Encouraging Growth in Key Metrics Drives 60% Gain YTD for Cloudflare Stock, we pointed out that Cloudflare was seeing peak GPU utilization around 70% with room to improve through the year. Now, in October, CEO Matthew Prince slightly raised this, saying that they are leaning heavily on their experience of running CPUs at 70-80% utilization and aiming to have GPUs match that level. This ties in to Cloudflare’s architectural differences compared to the hyperscalers, with Cloudflare’s main goal being improving utilization to serve more workload requests and the hyperscalers’ goal of making as much money from renting GPUs:

“The other thing that I think is unique about us is that certainly versus the hyperscalers, the primary business of the hyperscaler is to essentially rent you a server or a fraction of a server, and they try to effectively get whatever they pay for the server back 5x over the life of the server. That's their business. Whereas we're about, again, getting work done for our customers. We're selling something different, which is a sort of level of abstraction up from that. What that means is that we believe it's our job, not our customers' job to make the utilization rates as high as possible, make our systems as efficient as possible.

And so it's been remarkable to see over the last 15 years, how our team has been able to squeeze as much as possible out of the CPU capacity that we have, where we can run that CPU capacity at 70% to 80% utilization and get more out of every CapEx dollar we spend. But what's fascinating is we're sort of speed running the last 15 years now with GPUs, where we're figuring out how to make GPUs multi-tenant, how to make them load and unload models more quickly and driving the utilization of GPUs up substantially. And so that is still well below what we have with CPUs, but we see no reason that we can't get GPUs also up to that 70%, 80% utilization.”

Continuing to bring peak utilization rates higher and improving troughs should theoretically lead to faster processing times and an ability to handle more requests for customers, all while doing so for cheaper and at a higher margin.

A core advantage Cloudflare has is its serverless architecture spanning >13,000 networks globally with 449 Tbps of network capacity (up from 348 Tbps in January), letting the company shift workloads anywhere in the world where it has excess capacity. Prince says that while it is not always ideal, Cloudflare can move its smaller, free or low-end customers “to places across the network that have that free capacity, still give them a great performance. but then reserve the capacity that we have as close as possible to our largest customers.”

More importantly, Cloudflare does not believe it is capacity constrained akin to the hyperscalers, as again the company can shift workloads to wherever necessary and minimize or eliminate pain points where excess demand stalls one network point. Management also said that because they use off-the-shelf equipment with no customization, their “reaction time to deploy hardware where we need it is really, really fast,” letting them quickly stand up new networks whenever needed and quickly convert this to revenue.

Leveraging an Inference Advantage

Cloudflare’s network architecture and positioning at the edge gives it a strong advantage to offer high-performance, low-cost inference, yet the company continues to harp on the fact that inference remains de minimis to overall revenue – i.e., the growth curve of inference has not yet been felt in results. Cloudflare clarified that no inference customer is larger than 2% of revenue, while leading AI firms primarily tap Cloudflare for security rather than inference products at the moment.

While competition for inference workloads from the hyperscalers remains high, Cloudflare believes its key advantage lies in its TCO from handling workload optimization:

“It continues to be the model of do you want to do this work yourself and have to optimize yourself, or do you want to hand it off to Cloudflare. And I think in the cases where we're in the conversation, we're able to show that there's just a much better TCO, total cost of ownership, a much lower cost, much better performance when we manage that for you.”

CEO Matthew Prince also added that once customers test the platform and witness the TCO and optimization advantages, the platform becomes very sticky and can land those customers for the long-term. To this point, Cloudflare is continuing to bolster its platform for optimization, recently acquiring Replicate to integrate its expertise with containerized model building on a 50,000+ model catalog to facilitate AI deployments.

While it still may be early for inference, as more use cases pop up, Cloudflare is well positioned to capture inference-driven workloads. Again, this ties back into its network architecture, high utilization and proximity to users with ultra-low latency.

For example, management explained that “when you have human computer interaction, especially with something that seems almost alive when you're interacting with it, every millisecond counts, because it breaks that illusion if things slow down, especially as you get to things like voice communication and other things that need to have kind of a natural rhythm to them.” Management believes that while a lot of inference will run on handsets or in driverless vehicles, the next best place to run inference that can’t be run in those locations will be in the network, providing a structural tailwind to drive new workload wins.

Although it may be later in the future before some of these inference vectors and use cases materialize in full swing, and meaningfully contribute to Cloudflare’s revenue, the company can leverage this network advantage to remain a key enabler of the AI inference era.

Cloudflare to be Natively Available on Oracle Cloud

In mid-October, Cloudflare announced a partnership with Oracle’s Oracle Cloud Infrastructure (OCI) platform, making Cloudflare’s services natively available to OCI customers in hybrid, multi-cloud and OCI hosted environments.

Cloudflare says this gives it access to Oracle’s large pool of customers, and more importantly, an outlet to tap into OCI’s rapid growth runway through 2030. For example, Oracle is projecting a rapid 75% CAGR in OCI revenue, from $10 billion in FY25 to $166 billion by FY30, though OpenAI is projected to account for a majority of this, around $120 billion in FY30. Multi-cloud database revenue was a strong point for Oracle in fiscal Q1, rising 1,529% YoY, and Oracle is also projecting 8X growth in AI-powered database and AI platform revenue by 2030 to $20 billion.

However, the more important piece was management stating that both companies are aligned on a multi-cloud future, which requires ‘one consistent interface where they can apply security rules, have consistent network performance,” with Cloudflare the provider of choice.

A multi-cloud future could be a game-changer for both companies, with Oracle benefitting from incremental cloud workloads anchored by its extensive database integrations across AWS, Azure and GCP. In turn, Cloudflare benefits from its positioning as a ‘control plane’ offering unified security, performance and reliability across clouds, which will be likely increasingly important as AI proliferates. This positioning is anchored by Cloudflare’s R2 eliminating cross-cloud data sharing costs, thus addressing some of the main drawbacks of adopting a multi-cloud approach.

More on Act 4: Pay Per Crawl

Cloudflare discussed its new product, Pay Per Crawl, in more detail this quarter, aiming to solve an emerging pain point arising from growing LLM consumption – AI crawlers freely scraping websites for data. Reddit is a great example of this, as the site is a treasure trove of human-generated content perfect for improving AI models, yet it has seen AI companies scrape its site without consent.

For example, Cloudflare noted that a global web infrastructure platform signed a $1.2 million, 14-month contract for AI Crawl Control and Bot Management as they experienced a “massive surge in AI scrapers and malicious bots hitting their origin servers, inflating costs without revenue conversion and obscuring visibility into legitimate traffic.” Cloudflare noted it was “already exploring a much larger opportunity with this customer for Pay Per Crawl.”

Pay Per Crawl aims to put creators and publishers in control of who can access their content utilizing HTTP source codes. The feature will give creators three distinct options on regulating AI crawlers and unlock new monetization abilities: 1) allow full, free access to content, 2) block access entirely, or 3) require payment for crawling at a flat, per-request price.

Under the new feature, if a publisher decides to charge for crawling, they still retain the choice to let certain crawlers access the site for free, and can still negotiate other content-accessing deals separate from Pay Per Crawl. With the new service, Cloudflare’s relationship with customers strengthens significantly, as it is no longer simply an infrastructure vendor but now a revenue generator.

It is still extremely early for Act 4, but given the vast amount of data generated daily on the internet and the need for AI models to constantly crawl to retrieve up-to-date information, this holds potential to be quite an impactful product.

Financials

$3 Billion Revenue Run Rate by Q4 ’26, $5 Billion by Q4 ‘28

Cloudflare provided some insights into its near-term and medium-term revenue targets, with management expecting to reach a $3 billion annualized run rate in Q4 2026, and scale to a $5 billion run rate by Q4 2028.

At first glance, the $3 billion run rate forecast is not especially impressive, as it implies quarterly revenue of $750 million at the end of next year, whereas analyst estimates were $729 million prior to Q3’s report. This is just a 3% raise to consensus, and essentially signals that management is highly confident in maintaining a 27-28% YoY growth rate through the end of 2026.

To reach the $5 billion annualized target, or quarterly revenue of $1.25 billion by Q4 2028, Cloudflare would need to maintain this 28% YoY trajectory for the next three years, at a minimum. This is slightly higher than consensus through fiscal 2027 for 26% growth, while exceeding this to ~30% could see revenue reach more than $1.3 billion.

Other Key Metrics Strengthen

Billings growth accelerated sharply, from 33% in Q2 to 40% in Q3, rising to $624.4 million. Cloudflare said close rates had notably ticked up both YoY and QoQ in Q3 and bookings from partner-initiated opportunities doubled YoY.

Paying customer growth accelerated six points sequentially to 33% YoY, impressive at this scale considering paying customers now total 295,552. Growth was 10% QoQ, the highest on record since at least 2022. Cloudflare said the growth here was in part driven by customers graduating from free tier to small paid accounts during its AI Week and Birthday Week promotions.

Making Progress on Margins

Cloudflare made some progress on GAAP margins and nearly broke to positive territory on the bottom line on a GAAP basis; however, gross margins continued to contract.

GAAP gross margin was 74.0% in Q3, down 3.7 points YoY and 0.9 points QoQ. Adjusted gross margin was 75.3%, down 3.5 points YoY and 1 point QoQ, again impacted by increases in allocated costs from higher network traffic from paying customers. 

GAAP operating margin was (6.7%), up 0.5 points YoY and 6.4 points QoQ. Adjusted operating margin was 15.3%, up 0.5 points YoY and 1.2 points QoQ; for Q4, adjusted operating margin was guided to be 14%. Driving both a YoY and QoQ expansion on operating margin while gross margin contracts shows strong cost management while driving this revenue reacceleration, with opex up 24% YoY.

GAAP net margin was (0.2%), up 3.4 points YoY and 9.6 points QoQ. Adjusted net margin was 18.3%, up 1.4 points YoY and 3.6 points QoQ.

Earnings

Cloudflare reported a solid adjusted EPS beat in Q3, reporting 35% YoY growth to $0.27 versus the $0.23 estimate. GAAP EPS was on the brink of shifting to positive territory at ($0.00), versus the ($0.07) estimate.

For Q4, Cloudflare guided for adjusted EPS to be flat QoQ at $0.27, up 42% YoY. For fiscal 2025, Cloudflare raised its adjusted EPS forecast to $0.91, up from $0.85 to $0.86 previously. However, GAAP profitability is not expected on an annual basis until 2027.

Cash Flow Margins Strengthen

Cash flow margins strengthened in Q3, with operating cash flow margin up 11 points sequentially.

Operating cash flow was $167.1 million for a 30% margin, up from a 24% margin in the year ago quarter and a 19% margin in Q2. Free cash flow was $75 million for a 13% margin, up from 11% in the year ago quarter and 6% in Q2. Network capex was 14% of revenue.

Cash, equivalents and available-for-sale securities totaled $4.04 billion, while convertible notes outstanding totaled $3.26 billion.

Valuation

Cloudflare is second to only Palantir when it comes to elevated multiples in large-cap AI-exposed software, trading at 30.7x forward sales, more than 50% above its five-year average of 20x. Shares have pulled back quite sharply from nearly 42x forward sales at the end of October, its highest level since early 2022.

On the bottom line, Cloudflare is not yet GAAP profitable, but on an adjusted basis, it trades at 205x forward EPS, above its 147x average but below its 278x peak.

Cloudflare’s valuation presents the largest risk as the company is trading at the highest multiples in 3.5 years, with only one strong quarter under its belt to help confirm its AI-aided revenue reacceleration story. While key metrics are strong, the company still must prove that it can sustain >30% revenue growth through FY26 or the valuation may need to come to terms with a return to mid to high-20% growth.

Conclusion

There is a quiet strength in Cloudflare’s fundamentals and key metrics, and this became more evident in Q3, with revenue reaccelerating to nearly 31% YoY, its highest growth in seven quarters. Paying customer growth accelerated six points sequentially to 33%, DBNRR increased five points sequentially to 119%, and billings growth accelerated seven points sequentially to 40%. Cloudflare added a record number of >$1M and >$5M customers for a fourth consecutive quarter, with accelerating spending from these cohorts noted as a strong driver of the DBNRR expansion in the third quarter.

Damien Robbins, Equity Analyst at I/O Fund contributed to this analysis.

Cloudflare: Revenue Accelerates to >30%, Key Metrics Strengthen

Posted on November 28, 2025June 30, 2026 by io-fund

Material Evidence of Revenue Reacceleration, Driven by US and Enterprise Clients

Key Metrics Strengthen, Aided by Enterprise Transition

Moving forward, it will be important to see consistent strength in both DBNRR and RPO as further evidence that Cloudflare’s large customers can continue to support >30% revenue growth.

Bringing GPU Utilization up to 70-80%

Leveraging an Inference Advantage

While competition for inference workloads from the hyperscalers remains high, Cloudflare believes its key advantage lies in its TCO from handling workload optimization:

Cloudflare to be Natively Available on Oracle Cloud

Financials

$3 Billion Revenue Run Rate by Q4 ’26, $5 Billion by Q4 ‘28

Other Key Metrics Strengthen

Making Progress on Margins

Cloudflare made some progress on GAAP margins and nearly broke to positive territory on the bottom line on a GAAP basis; however, gross margins continued to contract.

GAAP net margin was (0.2%), up 3.4 points YoY and 9.6 points QoQ. Adjusted net margin was 18.3%, up 1.4 points YoY and 3.6 points QoQ.

Earnings

Cash Flow Margins Strengthen

Cash flow margins strengthened in Q3, with operating cash flow margin up 11 points sequentially.

Cash, equivalents and available-for-sale securities totaled $4.04 billion, while convertible notes outstanding totaled $3.26 billion.

Valuation

On the bottom line, Cloudflare is not yet GAAP profitable, but on an adjusted basis, it trades at 205x forward EPS, above its 147x average but below its 278x peak.

Conclusion

Damien Robbins, Equity Analyst at I/O Fund contributed to this analysis.

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Nvidia Q3: Largest QoQ Growth in 2 Years; Networking up 162%

Posted on November 20, 2025June 30, 2026 by io-fund

Nvidia’s Q3 showed the company’s GPU momentum return, delivering a substantial data center beat with 25% QoQ growth, surpassing an important $50 billion quarterly revenue milestone for the segment. More importantly, Nvidia’s guide pointed to this momentum continuing into the fourth quarter, implying that data center revenue could be on track to rise another $8 billion QoQ for 15% growth.

Yesterday I published an article entitled Why Nvidia Stock Could Reach $20 Trillion Market Cap by 2030 – a prediction that requires a 36% CAGR over a five-year period or about 8% growth QoQ. These two quarters alone meet the criteria for next year’s CAGR plus some.

Margins expanded sequentially, free cash flow sustained nicely, networking was up an impressive 162% and compute was up 56%. Management repeated they “currently have visibility to $0.5 trillion in Blackwell and Rubin revenue from the start of this year through the end of calendar year 2026.”

Below, we look at one other metric that hints that Blackwell Ultra can continue to deliver knockout earnings report while our sights are now set on Vera Rubin for H2 2026.

Nvidia Surpasses $50 Billion Quarterly Data Center Revenue

Nvidia surpassed the $50 billion quarterly data center revenue milestone in Q3, as it reported $51.2 billion in revenue for the segment, up 25% QoQ and 66% YoY. This is the highest QoQ growth rate for data center since fiscal Q4 2024. An impressive feat to deliver such strong growth at this scale considering the segment was just $18.4 billion at the time. On a dollar basis, data center revenue rose by $10.1 billion sequentially.

This sequential growth was driven by a strong inflection in Compute revenue, which surged 27% QoQ to $43 billion, its highest sequential growth rate since fiscal Q1 2025; however, this does come after a (1%) QoQ decline in fiscal Q2. Nvidia noted that Blackwell Ultra was ramping across all customer categories and became its leading architecture.

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

This would also correspond to a nearly $8 billion QoQ increase, meaning that if Nvidia maintains this growth cadence through mid-CY26, then it would reach our prediction for a $75 billion data center segment two quarters early. If this materializes, this would represent data center growth of 66% YoY, up from 56% last quarter.

It also could suggest Nvidia potentially reaching a $90 billion quarterly data center segment if this trajectory is maintained through the end of fiscal 2027. However, it is important to note that given the sheer scale of data center revenue, there is the potential for this inflection to be lumpy. Therefore, we are directionally bullish but not with too specific of a timeline; rather, these are milestones that tell us how quickly we could see $8 trillion market cap for example and then onward.

Blackwell Revenue Tops $100 Billion

As stated in our $20 Trillion pre-earnings writeup, after taking into account Blackwell revenue that will ship in FY2026, this should lead to a $320 billion data center segment next year. Here is what was stated in the $20 Trillion analysis: “Reading between the lines on Huang’s comments suggests strong upside to Nvidia’s data center revenue through 2026. Over the prior three quarters heading into fiscal Q3’s report, Blackwell revenue has totaled approximately $63 billion. Including Networking over that time frame, total revenue would rise to $78 billion, still a fraction of the total overall opportunity management is projecting. Thus, if we assume that Blackwell and Rubin ramp over the next five quarters, fiscal 2027 data center revenue could be nearly $320 billion, versus estimates for around $270 billion.”

Since we wrote that earlier this week, analyst estimates have been rising and now stand at $292 billion for next year. With information from this report, we look to be on track for a $317 billion data center segment next year (close to our original estimate this morning).

We calculated this from the prior three quarters heading into fiscal Q3’s report, Blackwell revenue has totaled approximately $63 billion. Now, Q3’s Compute revenue of $43 billion implies Blackwell has delivered around $104 billion in revenue in the past four quarters, assuming the only non-Blackwell revenue was the $2 billion disclosed from Hopper.

Including Networking and Q4’s guidance, Nvidia looks to be on track to generate $186 billion of its $500 billion opportunity in fiscal 2026. This would leave approximately $314 billion for fiscal 2027’s data center revenue to meet the $500 billion visibility, but if Nvidia can exceed that by 2-4%, it could be on track for $330 billion next year. Management sounded confident to achieve the $500 billion target and they hinted that they could exceed it as the CFO stated, “So there's definitely an opportunity for us to have more on top of the $500 billion that we announced.”

One Figure Says This Growth Inflection Will Continue

While we continue to hammer on the importance of Big Tech’s capex as the number one indicator for Nvidia’s data center growth continuing, there was potentially a more important, well overlooked figure in Nvidia’s report that signals this data center inflection will continue.

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

This is a notable increase from the prior five-quarter average of ~$30 billion, which is likely supporting the current ramp in data center revenue. This uptick in supply commitments, which is likely to translate into inventories and revenue over the coming four to six quarters, hints that Nvidia will continue ramping Blackwell output while preparing for Rubin’s production in the second half of 2026.

This also bolsters confidence in Nvidia’s order visibility to fill out and even exceed this cumulative $500 billion in Blackwell and Rubin revenue, as the company would not need to boost supply commitments by this degree if the demand signals were not there.

There is Global Demand for Nvidia’s GPUs

When hearing about an AI bubble, it’s important to remember there is global demand for Nvidia’s GPUs. The diversification across geographic regions, enterprises, startups – and of course, Big Tech, helps to insulate Nvidia should one customer or region slow their spending. Here is what was stated on the call:

“And then lastly, remember, we were just talking about the American CSPs. Each country will fund their own infrastructure. And you have multiple countries, you have multiple industries. Most of the world's industries haven't really engaged agenetic AI yet, and they're about to. All the names of companies that you know we're working with, whether it's autonomous vehicle companies or digital twins for physical AI for factories and the number of factories and warehouses being built around the world, just a number of digital biology start-ups that are being funded so that we could accelerate drug discovery. All of those different industries are now getting engaged, and they're going to do their own fundraising. And so don't just look at the hyperscalers as a way to build out for the future. You got to look at the world, you got to look at all the different industries and enterprise computing is going to fund their own industry.”

Commentary on Vera Rubin

If only a Nvidia investor could kick back and call it a day! Instead, given Blackwell Ultra now comprises 2/3 of revenue confirming a successful launch, our sights are now set on Vera Rubin commentary. According to management, Rubin is set for a fast ramp:

“The Rubin platform is on track to ramp in the second half of 2026. Powered by 7 chips, the Vera Rubin platform will once again deliver an X-factor improvement in performance relative to Blackwell. We have received silicon back from our supply chain partners and are happy to report that NVIDIA teams across the world are executing to bring up beautifully.

Rubin is our third-generation rack-scale system substantially redefined the manufacturability while remaining compatible with Grace Blackwell. Our supply chain data center ecosystem and cloud partners have now mastered the build to installation process of NVIDIA's rack architecture. Our ecosystem will be ready for a fast Rubin ramp.”

Financial Overview:

Strong Revenue Growth of 63%

Nvidia’s Q3 revenue grew by a solid 62.5% YoY and 22% QoQ to $57.01 billion. Revenue growth accelerated by 6.9 percentage points from 55.6% YoY growth reported in Q2. Revenue beat estimates by 3.5% and is the strongest beat in the last four quarters. The company’s strong revenue growth dispelled fears of an AI Bubble. Nvidia’s CEO Jensen Huang said, “Blackwell sales are off the charts, and cloud GPUs are sold out.”

The Blackwell revenue gained further momentum in the recent quarter. The GB300 sales were higher than the GB200 sales, notably accounting for 2/3 Blackwell’s revenue, driven by strong demand from cloud companies and hyperscalers. The Hopper platform contributed approximately $2.0 billion in revenue. While H20 sales were negligible at $50 million, management is working with the US and Chinese governments to ship products to China. Looking forward, Rubin is on track to ramp in the second half of 2026.

Management also provided a strong Q4 revenue guide of $65 billion at midpoint, representing a YoY growth of 65.3% and up 14% QoQ. It beat the estimates by 5.1%. Looking forward, analysts expect revenue to grow 40.5% YoY to $292.1 billion for FY2027 and 24.8% YoY to $364.6 billion for FY2028.

Networking Revenue Growth of 162%

The company’s networking revenue was an outlier, growing 162% YoY and 13% QoQ to $8.19 billion. Revenue growth accelerated by 84 percentage points from 78% YoY growth in Q2. Management stated in the earnings call that the company’s networking business is specifically built for AI and is now the largest in the world. The strong growth was primarily due to NVLink scale-up and robust double-digit growth across Spectrum-X Ethernet and Quantum-X InfiniBand.

Management stated in the earnings call that Meta, Microsoft, Oracle, and xAI are building gigawatt AI factories with Spectrum-X Ethernet switches, further highlighting the flexibility and openness of the company’s platform.

The company introduced Spectrum-XGS Ethernet in August, which will enable to connect distributed data centers into Giga-Scale AI Super-Factories. Nvidia is the only company with AI scale-up, scale-out and scale across platforms, reinforcing the unique position in the market as the AI infrastructure provider.

Q3 gaming revenue grew by 30% YoY and was down (1%) sequentially to $4.27 billion. Management mentioned that channel inventories have reached more normalized levels heading into the holiday season.
Pro visualization revenue grew by 56% YoY and 26% sequentially to $760 million. Colette Kress, CFO, said in the earnings call, “Growth was driven by DGX Spark, the world's smallest AI supercomputer, built on a small configuration of Grace Blackwell.”
Automotive revenue grew by 32% YoY and up 1% QoQ to $592 million. The CFO highlighted, “We are partnering with Uber to scale the world's largest Level 4 ready autonomous fleet built on the new NVIDIA Hyperion L4 robotaxi reference architecture.”
OEM and other revenue grew by 79% YoY and 1% QoQ to $174 million.

Margins

The company’s margins beat management guidance and are expected to expand in Q4.

Q3 gross profits grew by 60% YoY to $41.85 billion. Q3 gross margin was 73.4%, beating management guidance of 73.3% by 10 basis points. Gross margin was up 100 basis points sequentially and down 120 basis points YoY. Q4 gross margin guide is 74.8%, up 140 basis points sequentially and up 180 basis points YoY. Adjusted gross margin was 73.6%, beating the management guidance by 10 basis points. Management expects an adjusted gross margin of 75% in Q4, up 140 basis points sequentially and up 150 basis points YoY.
Looking forward, management mentioned in the earnings call that the input costs are increasing and are looking to hold gross margins in the mid-70s range for FY2027.
Q3 operating income grew by 65% YoY and 27% sequentially to $36.01 billion. The operating margin was 63.2%, beating the management guidance by 80 basis points. Adjusted operating margin was 66.2%, beating the management guidance by 50 basis points. Management has provided a strong operating margin guide of 64.5% and an adjusted operating margin guide of 67.3% for Q4.
Q3 net profits grew by 65% YoY and 21% QoQ to $31.9 billion with a net profit margin of 56% compared to 55% in the same period last year and 56.6% in Q2. Adjusted net profits grew by 59% YoY and 23% QoQ to $31.77 billion with an adjusted net profit margin of 55.7%, compared to 57% in the same period last year and 55.2% in Q2.

Adjusted EPS grew by 60.5%

Q3 adjusted EPS grew by 60.5% YoY and 23.8% QoQ to $1.30, beating estimates by 3.5%. GAAP EPS grew by 66.7% YoY to $1.30, beating estimates by 8.5%. GAAP EPS included $0.06 in gains in non-marketable and publicly held equity securities.

Analysts expect adjusted EPS to grow 61.2% YoY to $1.43 in Q4 and accelerate to 89.5% YoY growth to $1.53 in Q1.
Looking forward, analysts expect FY2027 adjusted EPS to grow 49.5% YoY to $6.83 and 26.7% YoY to $8.65 in FY2028.

Cash and Balance Sheet

The company has a strong balance sheet with solid cash flows primarily driven by strong revenue and profits.

Q3 operating cash flow grew by 34.7% YoY to $23.75 billion with an operating cash flow margin of 41.7%, compared to 50.3% in the same period last year and 32.8% in Q2.
Q3 free cash flows grew by 31.6% YoY to $22.09 billion with a free cash flow margin of 38.7%, compared to 47.9% in the same period last year and 28.8% in Q2.
The company’s cash and marketable securities have been steadily increasing and were $60.6 billion at the end of Q3, up from $56.8 billion in Q2 and $38.5 billion in the same period last year. Debt remained constant at $8.47 billion for Q3 and Q2.
The company returned $12.7 billion to shareholders in the third quarter through $12.5 billion of share repurchases and $243 million of cash dividends. The company expects to continue to use its strong future cash flows to buy back shares and invest in AI growth opportunities.
Inventories grew by 32% sequentially to $19.78 billion to support strong revenue growth.

Conclusion:

The $20 trillion prediction came from looking at the original $10 trillion prediction ahead of earnings and realizing I’d have to bump this up given the commentary around the $500 billion from the Blackwell-Rubin cycle. Although we had already slated next year for a $300 billion run rate and a $75 billion quarterly data center segment, it helped to hear last month that management agrees this is possible. Where the disconnect happens with analyst estimates is what will happen after next year as this is where analyst estimates show minimal growth through 2030 revenue with $437 billion whereas I am calling for double that by 2030. While Blackwell Ultra gets us to a new milestone of $50 billion to $75 billion quarterly revenue, quite a bit of my thesis depends on Vera Rubin, Rubin Ultra and the Feynman generations.

Although the next five years will be a marathon, the Q3 report is a step in the right direction. I don’t expect consistent QoQ growth every quarter, yet as stated, we are already exceeding my CAGR for next year in two quarters’ time. Crunching these numbers matters quite a bit as we are talking about the world’s most valuable company and Nvidia will have to put up consistent growth for the stock to inch upward. The days of a sudden spike in the stock price are likely behind us, yet if Nvidia remains consistent, the incessant market narratives will eventually tire.

Overall, this was an excellent report — and after two years of dissecting every angle of Blackwell, I’m excited to finally shift coverage to the Rubin generation of GPUs. Woohoo! This now marks the fourth GPU generation I’ve retired for I/O Fund Members — and we’re officially moving on to the fifth.

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

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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Why Nvidia Stock Could Reach a $20 Trillion Market Cap by 2030

Posted on November 19, 2025June 30, 2026 by io-fund

The statement that Nvidia stock could reach a $20 trillion market cap by 2030 will trigger plenty of emotion — it sounds fantastical, full of hype, or like a prediction made far too early in the AI cycle. Yet what I offer you below is a data-driven, fundamentally grounded case for how Nvidia can realistically reach a $20 trillion valuation by 2030.

When it comes to Nvidia’s AI story, I’ve offered the earliest and most consistent analysis, covering the company’s AI trajectory earlier than anyone on record. For instance, I told my premium stock research members in September of 2019 that Nvidia would become one of the world’s most valuable companies when it was only a $110 billion valuation (it’s now up 40X). I also publicly stated that Nvidia would surpass Apple when Nvidia had just one-fifth of Apple’s market cap — $550 billion versus $2.5 trillion — writing: “The conclusion to my analysis is the same as the introduction, which is that I believe Nvidia is capable of outperforming all five FAAMG stocks and will surpass even Apple’s valuation in the next five years.” Fast forward and Nvidia stock is up 8X since that analysis.

Last year, when Nvidia stock was valued at $3 trillion, I projected the stock would reach $10 trillion market cap by 2030 — a forecast that no longer looks aggressive now that the stock has briefly broken above $5 trillion. Today, with an even clearer view into the company’s product cadence, software moat, and AI systems dominance, my new, updated thesis is that Nvidia’s stock is on track to reach a $20 trillion market cap by 2030.

This is supported by Nvidia’s aggressive 1-year product roadmap, an impenetrable software ecosystem through CUDA, and its evolution into a full-stack AI systems provider. When these elements are modeled together — alongside the rapid expansion in global AI infrastructure capex — the path to $20 trillion becomes less sensational and more a reflection of compounding fundamentals.

Nvidia’s Data Center Needs to Grow at 36% CAGR to Reach $20T Market Cap

To get down to brass tacks, Nvidia will have to grow its data center segment at a 36% CAGR to reach a $20 trillion market cap if we assume its 5-year median sales valuation of 25 forward PS remains intact. This will put the company’s data center revenue at a run rate in the mid-$900 billion range.

Pictured above: Nvidia stock could see a $20 trillion market cap by 2030 based on a 36% CAGR in its data center segment

About eighteen months ago, I highlighted the importance of Nvidia reaching a $50 billion data center segment by year-end in the article, Here's Why Nvidia Stock Will Reach $10 Trillion Market Cap By 2030, stating:

In my analysis last month on the Blackwell architecture, I made the argument these estimates are too low and that my firm expects we will see a $200 billion data center segment by end of CY2025 propelled forward by the B100, B200 and GB200, including the following points: “Taiwan Semi’s CoWos capacity, which is essential for Blackwell’s architecture, is estimated to rise to 40,000 units/month by the end of 2024, which is more than a 150% YoY increase from ~15,000 units/month at the end of 2023. Applied Materials has boosted its forecast for HBM packaging revenue from a prior view for 4X growth to 6X growth this year.”

The data center segment for Nvidia of $320 billion by 2027 would result in 260% growth for Nvidia’s DC from where it stands today and up 120% from DC revenue estimates for end of CY2025.”

It’s highly probable that Nvidia will blow past the $50 billion data center segment mark this evening – one quarter earlier than my original prediction – which puts the company on the path for a $75 billion segment in Q4 of next year. Tracking these milestones is crucial as it helps support that Nvidia is well on its way to reaching my firm’s brand-new updated estimate for a $230 billion data center quarter by Q4 of 2030 or $930 billion for the full year.

Industry analysts have AI accelerators growing at 31.5% CAGR through 2033 with McKinsey putting out a prediction for $7 trillion in AI infrastructure spend through 2030 with $5.2 trillion going toward building data centers for AI workloads. Dr. Lisa Su and Jean Hsu echoed McKinsey’s projections, stating the AI data center market could be worth $1 trillion by 2030, referring to the addressable market of AI accelerators where AMD competes.

mid

Regardless of which way you dice it, industry estimates point toward AI spend exceeding current expectations. For example, Dr. Su originally had predicted a $500 billion market by 2028. Her updated forecast assumes 35% growth over the next three to five years – the same growth rate required for Nvidia to reach the assumptions underpinning my thesis for a $20 trillion market-cap scenario.

McKinsey’s $5.2 trillion AI infrastructure forecast implies roughly $1.5 trillion in annual AI spending by 2030. Under this framework, our assumptions are slightly on the aggressive side, as they imply Nvidia captures about 60% of total AI capex. Back-of-the-napkin math suggests Nvidia is currently capturing closer to 50% of AI spend, given today’s $405 billion capex run rate and Nvidia’s data center segment set to surpass a $200 billion run rate in this evening’s report.

Pictured above: Big Tech AI Capex expected to surge from $406B in 2025 to over $1.5 trillion by 2030, reflecting the massive growth in the AI data center market.

Offense is the Best Defense: Nvidia’s Rapid Product Road Map

The saying goes “the best offense is the best defense” and Nvidia is fully applying this philosophy by leading with its design prowess to ensure custom silicon cannot replace its lead in AI systems. There will certainly be a market for custom silicon as it excels at application specific workloads, which is attractive to Big Tech companies that can use custom silicon to optimize their recommendation engines, run inference at scale and optimize specific internal models. However, custom silicon cannot compete with GPUs and Nvidia’s CUDA software platform on general workloads, which excels at running every model, every framework and every new architecture.

The key reason that Nvidia can reach a $20 trillion market cap by 2030 is because the company is moving its GPU generation cadence to a rapid 12-18 month cycle compared to custom silicon, which is typically on a 3-5 year cycle. Even for Nvidia, the goal of releasing a new GPU generation every year was once unthinkable. Yet this offensive measure will be transformative, turning what was once a cyclical revenue profile into a consistent and compounding growth trajectory.

Source: Nvidia GTC Conference, March 2025 Last March, Nvidia revealed their plans for a 1-year product cadence, a key element to the I/O Fund’s thesis that Nvidia can reach $20 trillion market cap by 2030.

At this point, Nvidia is competing with itself with Blackwell offering 208 billion transistors compared to Hoppers 80 billion transistors. By combining 72 GPUs, the Blackwell systems offer 30X to 40X faster inference and are up to 2.5X faster on training. The memory capacity has increased to 192GB of HBM3e for Blackwell and 288GB for Blackwell Ultra. Energy efficiency is also improved by 25X. The 30X improvement in running AI reasoning models is primarily from leveraging FP4 format and fifth-generation NVLink at rack scale level. Blackwell arrived in H1 of 2025 and Blackwell Ultra is shipping now in H2 2025.

Vera Rubin increases the number of GPUs to 144, up from 72 GPUs, for 3.3X higher performance. Vera Rubin doubles the FP4 performance from 20 petaflops to 50 petaflops. The new architecture will offer HBM4 memory and sixth-generation NVLink. Rubin Ultra takes rack-scale to a new level with 576 GPUs compared to Rubin’s 144, with more details to be released in the coming months. Vera Rubin is expected to arrive in H2 2026 with Rubin Ultra in H2 2027.

From there, Feynman is expected to bring to market Gigawatt AI factories, which would be up about 8X from today’s peak cluster size of 150 MW (the largest cluster right now is Colossus at 150MW with plans to expand to 300MW soon). Feynman is expected to arrive in 2028.

5X Hopper: Jensen Huang Reveals $500 Billion Blackwell and Rubin Revenue Visibility

Nvidia laid out an eye-opening stat at the company’s GTC October conference, with CEO Jensen Huang revealing the company has visibility into an astonishing $500 billion in cumulative Blackwell and Rubin revenue through the end of 2026. This is ~5X the lifetime revenue of its Hopper GPUs from 2023 through 2025 which stood at $100 billion.

Huang’s projection calls for 20 million GPU shipments, with 30% of that, or 6 million, having already been shipped; however, considering both generations have two GPUs per chip, in reality, this corresponds to 10 million chip shipments with 3 million already shipped. Huang’s forecast also excludes China but is expected to include attached networking equipment such as Nvidia’s InfiniBand and NVLink.

Reading between the lines on Huang’s comments suggests strong upside to Nvidia’s data center revenue through 2026. Over the prior three quarters heading into fiscal Q3’s report, Blackwell revenue has totaled approximately $63 billion. Including Networking over that time frame, total revenue would rise to $78 billion, still a fraction of the total overall opportunity management is projecting. Thus, if we assume that Blackwell and Rubin ramp over the next five quarters, fiscal 2027 data center revenue could be nearly $320 billion, versus estimates for around $270 billion.

This forecast is supported by the accelerated progression in GPU cluster sizes, scaling quickly from 10K clusters just two years ago to hundreds of thousands over the next few years. The first 10K Hopper GPU clusters came online in 2023 and 2024, before scaling 10X to 100K clusters by year-end 2024. Blackwell is picking up where Hopper left off, with clusters expanding from 100K to the hundreds of thousands through 2026 and 2027, such as for Microsoft’s new Fairwater data centers and xAI’s Colossus 2. This scale out of 8-10X growth to reach 1 million GPU clusters over the next few years underpins millions of GPU shipments over the coming quarters.

Consensus Estimates Still Below Nvidia's $500B Target for FY26/27

Even with the commentary for half a trillion in revenue potential for Blackwell and Rubin GPUs, consensus estimates for fiscal 2026 and 2027 still remain below $500 billion combined. This also comes despite numerous analysts pointing out that Street estimates are too low and citing substantial upside potential for data center revenue.

Source: YCharts

Current consensus estimates point to $207.6 billion in revenue in fiscal 2026, before rising to $290.5 billion in fiscal 2027, with next year seeing only a $13 billion (5%) upward revision following the $500 billion forecast. It’s important to note that some of fiscal 2026’s revenue came from the Hopper generation, which contributed ~30% of Compute revenue in fiscal Q1, or more than $10 billion.

However, analysts from Cantor, UBS, Melius and others believe estimates are too low moving through calendar 2026. New Street says the $500 billion forecast “implies a nearly doubling of Nvidia's data center revenue in 2026,” while Wolfe Research estimated that data center revenue "could be $60 billion over prior calendar 2026 estimates.”

This suggests that the Street remains cautious about this order visibility materializing in full, as current consensus estimates would project data center revenue of ~$445 billion assuming ~90% share of total revenue.

AI Buildout Accelerates: Big Tech Capex Headed for $405 Billion

Big Tech Capex grew by 75% YoY and 19% sequentially to $113.4 billion in Q3. In fact, capital spending for the AI buildout has risen 44.6% from our initial estimates. A substantial jump considering the scale already measured in hundreds of billions. This time last year, the expectations were $280 billion in Big Tech capex.

Morgan Stanley later forecast $300 billion in Big Tech capex for 2025. Capex estimates stood at $365 billion heading into Q3, and now we believe 2025 capex is on track to surpass $405 billion, representing YoY growth of 62%. This spells good things for the I/O Fund’s projected 36% CAGR for Nvidia’s data center to materialize.

Overall, analysts have clearly underestimated the growth in capex and future AI opportunities. This is also evident when AMD’s CEO Lisa Su recently increased the company’s AI total addressable market to $1 trillion in 2030, up from the previous forecast of $500 billion by 2028.

In terms of what the opportunity looks like moving forward, McKinsey is predicting 3.5X growth in gigawatts for AI data centers between 2025-2030. The costs associated with AI data centers range from $3 trillion to $8 trillion, or about $5.5 trillion at the midpoint. This correlates to about 3X growth if we assume the current run rate to 2030 is $1.8 trillion at the current capex of $405 billion.

UBS recently upgraded the AI capex estimates from the previous $375 billion to $423 billion for 2025. For the next year, they have increased the estimates from $500 billion to $571 billion, a solid 14% increase. By the year 2030, UBS expects overall spending to hit $1.3 trillion, implying a 25% compound annual growth rate (CAGR) over the next five years – or about 11 points lower than our estimate for 36% CAGR – although I still have five years to go for analysts to raise their estimates, which judging by what we’ve seen in capex estimates, could very well be doable.

Another point as to why AI spending estimates may be too low is they are still modest to global GDP. According to IMF estimates, the $1.3 trillion capex estimate would only account for 1% of GDP, whereas some of the previous investment booms like railroads, computers, telco, etc. – ranged from 1.5% to 4.5% of global GDP.

Nvidia’s Deals with OpenAI and Microsoft Fuel Insatiable GPU Demand

If a $20 trillion market cap sounds outlandish, consider the deals worth hundreds of billions that are pouring in. Not only does Nvidia have the $500 billion Stargate project underway for OpenAI, but the ChatGPT parent also committed to an additional $250 billion of compute from Azure as part of its for-profit restructure.

Additionally, Nvidia signed a partnership with OpenAI, which will see it deploy up to 10GW of Nvidia GPUs in data centers. Under the deal, Nvidia is investing up to $100 billion in OpenAI progressively as each GW is deployed. The first GW of GPUs under Nvidia and OpenAI’s agreement will be deployed in the second half of 2026 on Nvidia’s upcoming Vera Rubin platform. While there was no set timeline for the remaining nine GWs of chips, CEO Jensen Huang told CNBC that the entire deployment would represent around four to five million GPUs.

In terms of the total opportunity for Nvidia, Bank of America estimates this partnership could generate $300 billion to $500 billion in revenue overtime at full deployment. This aligns with expectations from other analysts that Rubin and Rubin Ultra will cost $30 to $35 billion per GW, with 10-15% increases per GW per each generation.

Microsoft also contracted approximately 200,000 GB300s from British startup Nscale in a deal said to be worth $14 billion, with the first smaller-scale deployment starting in Q1 followed by a 104,000 cluster in Q3 2026. This builds on Microsoft CEO Satya Nadella hinting last weekend that Microsoft is bringing online more than 100,000 GB300s this quarter, or approximately 1,389 NVL72 racks worth ~$4.17 billion at a $3 million estimated ASP.

Deals like these that continue to pop up across the industry hint that demand for GPUs remains insatiable to meet high demand. It also suggests current capex estimates may be too low as hyperscalers continue to pour tens of billions each quarter to data center infrastructure via whatever avenue possible.

Conclusion:

When you step back from the noise and look at the data, the path to $20 trillion is built on compounding fundamentals that are already surpassing the most aggressive forecasts from a year ago. Analysts continue to revise capex expectations higher, AI infrastructure projections have doubled, and Big Tech is racing to deploy unprecedented levels of compute.

The data center segment growing 36% CAGR is a tad ambitious, yet it does not factor in markets such as robotics, agentic systems and simulation. Also consider we are seeing 5X growth from the Hopper cycle to the Blackwell-Rubin cycle in the data center segment. At the end of 2026, we will need only 3X growth to deliver on my prediction of a $930 billion data center segment.

Today, my updated thesis is clear: Nvidia has a credible path to reach a $20 trillion market cap by 2030 with an aggressive product road map for Blackwell, Rubin, Rubin Ultra and eventually Feynman’s gigawatt-scale AI factories. Just as with my earlier calls on Nvidia’s stock, the data increasingly supports an outcome that was once considered impossible.

As AI accelerates into the largest technology buildout of our lifetime, we believe Nvidia remains one of the strongest beneficiaries. Our portfolio is also positioned with many of Nvidia’s lesser-known AI networking suppliers and AI energy stocks. To view the I/O Fund portfolio plus my 43-page Top 15 AI Stocks list, sign up below.

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Our cumulative return of 210% would place us as #2 if we were a hedge fund and #5 if we were an ETF. Our entries and exit are sent in real-time including one entry as low as $3.15 on Nvidia in 2018 and 9 alerts sent under $20 in 2021 – 2022. This year, we have an AI energy position up over 500% and others up over 100% in AI energy and AI networking. Learn more here.210% would place us as #2 if we were a hedge fund and #5 if we were an ETF. Our entries and exit are sent in real-time including one entry as low as $3.15 on Nvidia in 2018 and 9 alerts sent under $20 in 2021 – 2022. This year, we have an AI energy position up over 500% and others up over 100% in AI energy and AI networking. Learn more here.

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Big Tech’s $405B Bet: Why AI Stocks Are Set Up for a Strong 2026

Posted on November 13, 2025June 30, 2026 by io-fund

AI accelerators such as GPUs and custom silicon need no introduction. Compute has led the AI boom; a trend so powerful, it is displacing the FAANGs of the last decade with Nvidia firmly the world’s most valuable company and infrastructure suppliers like Broadcom has pushed past legacy peers such as Meta in market cap.

As the market weighs the so-called AI bubble, there are many disparate facts thrown at investors: dot-com analogies, tariff headlines, short-term stock pullbacks, and circular investments from companies such as OpenAI. What matters far more for the AI trade than all of these combined is Big Tech capital expenditures.

The cumulative amount that Big Tech is spending far outweighs the importance of earnings reports, fiscal year guidance, Nvidia’s networking growth or their product roadmap, if AMD has a new deal from OpenAI, Oracle’s insane RPO, Broadcom’s networking chips and custom silicon announcements – all of the above is being single-handedly driven by Big Tech’s large capital expenditure (capex) budgets.

The latest quarter showed a 19% QoQ increase in Big Tech spending, confirming continued conviction in the build-out of AI infrastructure. Each tech giant is dedicating tens of billions toward AI systems, confident in the growth and customer value these services generate. As we look toward 2026, the direction of AI stocks will continue to follow the trajectory of Big Tech CapEx — and right now, that trajectory is pointed higher.

AI Capex Forecasts Keep Accelerating: The $405 Billion Reality

One of the most persistent patterns since the AI boom began is that analysts have been behind the curve on capital-spending forecasts. As you’ll see below, expectations have risen quarter after quarter as Big Tech’s actual investments repeatedly outstrip projections. What started as a $250 billion estimate for AI-related CapEx in 2025 now sits above $405 billion. The scale and urgency of hyperscaler build-outs suggest that even today’s elevated numbers could again be revised higher in 2026.

In fact, capital spending for the AI buildout has risen 44.6% from initial estimates, a substantial jump considering the scale already measured in hundreds of billions. This time last year, the expectations were for $280 billion in Big Tech capex.

It’s easy to tune out the words “big tech capex” at this point but zoom out for a minute and consider that Big Tech’s TTM capex was $24B at the start of 2015, or up 15X over ten years. Where we end up by the end of the decade on capex spending will likely represent the biggest “boom” in history.

On a more near-term basis, Goldman Sachs sees hyperscaler capex increasing sharply through 2027 – capex is projected to be $1.15 trillion from 2025 through 2027, more than double the $477 billion spent from 2022 through 2024.

Going back to the first point, analysts thus far have missed the mark in their estimates. Every quarter, sell side analysts rush to update their models. Therefore, the I/O Fund is penciling in that 3x is a baseline to work with over a 5-year time frame.

Big Tech AI Capex Jumps 75% YoY in Q3 to a Record $113.4 Billion

Big Tech Capex grew by 75% YoY and 19% sequentially to $113.4 billion in Q3. Most importantly, Q3’s 75% growth rate was the strongest growth so far this year, accelerating 12 points from 63% growth in Q2. This spells good things for key suppliers in the coming quarter.

Big Tech Capex increased by 75% YoY to $113.4 billion in Q3 2025.

Amazon’s Raises Annual Capex Guidance to $125 Billion

When listening to commentary on earnings calls, in sharp contrast to concerns over an AI bubble, what we hear from Big Tech management teams is a sense of urgency. From Amazon’s Andy Jassy last quarter: “The faster we grow, the more CapEx we end up spending because we have to procure data center and hardware and chips and networking gear ahead of when we're able to monetize it. We don't procure it unless we see significant signals of demand.”

This sense of urgency was echoed again in Q3: “You're going to see us continue to be very aggressive investing in capacity because we see the demand. As fast as we're adding capacity right now, we're monetizing it.”

mid

This boots-on-the-ground commentary implies that Amazon has direct visibility into how quickly capacity is selling out and the level of demand that can be met with accelerated capex investments. This is further supported by monetization trends in Amazon’s custom silicon business, Trainium, which reached a multi-billion dollar run rate, up 150% QoQ this quarter.

Amazon’s capex in Q3 rose 55% YoY to $35.1 billion, with the company raising the 2025 capex guidance to $125 billion, up 51% YoY. This represents more than 88% of projected operating cash flow for the company and more than 17% of revenue.

By spending more than its hyperscaler peers, Amazon was able to add 3.8 GW of capacity over the past 12 months, the most out of the group.

Microsoft’s Q3 Capex Sees 75% Increase YoY

Microsoft’s capex in Q3 was $34.9 billion, an increase of 75% YoY from $20 billion in the year-ago quarter. Sequentially, it grew by 44% YoY from $24.2 billion in the previous quarter. The company’s strong capex growth was primarily driven by increasing demand for its Cloud and AI offerings. This quarter, approximately half of the capex spend was on short-lived assets, primarily GPUs and CPUs, to support the Azure platform, first-party apps at AI solutions, and accelerating R&D activities. The remaining spending was for long-lived assets that will support monetization in the long term.

With strong accelerating demand, Microsoft is increasing its spending on GPUs and CPUs. Therefore, total spending is expected to increase sequentially in the next quarter and now expects the FY 2026 growth rate to be higher than FY 2025. To provide context, FY2025 ending June capex grew by 58% YoY to $88.2 billion.

Big Tech is set to spend $405 billion building the AI infrastructure of the future — and we invest in the companies set to benefit most. Discover how the I/O Fund tracks, analyzes, and identifies beneficiaries of this unprecedented CapEx cycle. Learn more here.Learn more here.

Alphabet Guides 2025 Capex Growth of 75%

The company’s capex grew by 83% YoY to $23.95 billion. Sequentially, it grew by 7% from $22.4 billion in the previous quarter. Most of the capex was spent on technical infrastructure with approximately 60% of that investment in servers and 40% in data centers and networking equipment. Management stated in the recent earnings call that they are witnessing positive returns on AI investments. “I would say it's not just early signs because we're seeing returns, obviously, in the Cloud business. You've heard us talk about the fact that we already are generating billions of dollars from AI in the quarter.”

Looking forward, the company expects to invest aggressively due to the strong demand from cloud customers as well as the growth opportunities across the company. Management now expects the 2025 capex to be in the range of $91 billion to $93 billion in 2025, up from the previous estimate of $85 billion. It represents a YoY growth of 75% at midpoint. The capex is further expected to increase in 2026, which further supports our view that AI stocks will benefit in 2026.

Meta Increases Capex Guide to 81% Growth

Meta’s Q3 capex was $19.4 billion, up 111% YoY from $9.2 billion in the same period last year. Sequentially, it grew by 14% from $17 billion in the previous quarter. The strong growth was primarily driven by investments in servers, data centers, and network infrastructure.

Management also increased the 2025 capex to a range of $70 billion to $72 billion, up from the prior outlook of $66 billion to $72 billion. It represents a YoY growth of 81% from the prior year. Due to the continued investments in AI infrastructure, Meta expects next year’s capex to be significantly higher than in 2025, particularly as their compute needs are higher than their expectations. Management stated in the earnings call, “As we have begun to plan for next year, it's become clear that our compute needs have continued to expand meaningfully, including versus our own expectations last quarter. We are still working through our capacity plans for next year, but we expect to invest aggressively to meet these needs, both by building our own infrastructure and contracting with third-party cloud providers.”

Big Tech Capex Increase Provides a Boost to AI Stocks in 2025

Since the beginning of the year, Big Tech Capex estimates have increased from $280 billion to $405 billion, an impressive 31% positive revision. Alphabet witnessed the highest positive revision of 47%.

Big Tech Capex revisions boost AI stocks

As seen in the chart below, AI stocks have outperformed the broader Nasdaq-100 index by a wide margin. We believe that this trend will continue in 2026 as Big Tech Capex continues to expand and the numerous earnings calls from companies indicate that demand far outweighs supply.

AI Stock Micron returned 188% YTD in 2025.

Source: YCharts

Key Reasons Why Capex Spending Won’t Slow Down Anytime Soon

To be objective, there are analysts calling for a stock market crash based on the risks around the consumer and a GDP that is propped up by capex spending.

Stifel stated in August: “While the capex boom around AI temporarily supports GDP and asset prices, Stifel forecasts this bump will fade as corporate tech spending plateaus. Such a build-out, after all, occurs only once, while consumer spending power is entering a lull that could expose markets to abrupt correction.”

There is weight to what Stifel is describing, which is why tariffs remained a risk on our last Top 15 AI stocks report and remain a risk for our latest report, as well. You can read more here about how the consumer is fairly weak under the hood, and how capex spending is creating a false impression that GDP is stronger than it is.

Where I disagree with Stifel is the idea that “such a build-out, after all, occurs only once” AI infrastructure is not a fixed achievement — rather it is an evolving architecture with ambitions that expand each year. Each leap in model complexity and compute performance forces hyperscalers to re-architect their data centers roughly every one to two years. Power, cooling, memory bandwidth, and networking standards must all scale in tandem with new architectures such as Nvidia’s Blackwell and AMD’s upcoming MI400s. This constant cycle of upgrade and expansion makes AI CapEx structurally recurring, rather than a one-time boom, and illustrates why I view hyperscaler spending as a durable driver of AI semiconductor and infrastructure stocks.

Although cloud was also architecture-driven, it reached its end goal rather quickly in terms of driving down costs and improving productivity, allowing companies to quickly scale while providing pay-as-you-go compute and services to disrupt the significant up-front costs from on-premise servers. The end goal for AI is far more ambitious, as it could take a decade or more before Big Tech accomplishes commercially viable AGI (general artificial intelligence).

Early Signs of Heavy Debt Load from AI Buildout

Over the last few years, capex was funded by cash flows and cash on the balance sheet of companies. However, this is now changing. There is a growing concern that the robust AI demand is fueled by significant levels of debt.

Bank of America data shows that companies borrowed $75 billion in the last couple of months for spending on AI data centers. This is more than double the annual average issuance over the past decade. One of the reasons companies issue debt is that their capex exceeds their operating cash flows. The capex, excluding dividends and share repurchases, is reaching extreme levels of 94% of operating cash flows in 2025, up 18 percentage points from the 2024 levels.

According to J.P. Morgan estimates, the build-out of data centers will require a staggering $1.5 trillion in investment-grade bonds over the next five years. They believe that every market, including both government and private credit markets, needs to be tapped to close the funding gap. What will happen if this original estimate is too low, as well?

Analysts already project that $300 billion of high-grade bonds will be issued to fund AI data centers next year. Additionally, Barclays believes that AI-related tech debt issuance is a key determinant of potential credit market supply in 2026. Meanwhile, the Street is already concerned there is not enough revenue or profits to show for the capital already allocated, let alone the increase in capital we will see beyond 2026 plus the increasing costs of debt.

Cash Leaders and Laggards

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Which Big Tech stocks have stronger cash flows and balance sheets able to support high capex.
Promising AI stocks that are weighed down by negative free cash flows owing to high capex.
One major AI player and large cap stock with a rising debt problem.

Companies like Microsoft and Alphabet have a broad-based revenue stream, a strong balance sheet, and stable cash flows to support long-term capex growth. Microsoft has cash and short-term investments of $102 billion and debt of $43.2 billion, with a net cash position of $58.8 billion. The company reported strong operating cash flows of $45.1 billion and free cash flows of $25.6 billion in the recent quarter. It has a low capex as a percentage of operating cash flow of 43%, as shown in the chart below.

Similarly, Alphabet has a stable balance sheet of cash and marketable securities of $98.5 billion and debt of $21.6 billion. The company also reported strong operating cash flows of $48.4 billion and a free cash flow of $24.5 billion in the last quarter. The company also has a low capex as a percentage of operating cash flow of 49%, which suggests that the company can easily support capex with the operating cash flows.

Meta has a stable cash flow and balance sheet. However, the company is on the threshold as it has a higher capex to operating cash flow percentages compared to Microsoft and Alphabet. It also entered a complex financing structure with Blue Owl Capital that would help to keep debt off its balance sheet but might not eliminate the concern of using debt to fund AI buildout.

Meta had cash and marketable securities of $44.45 billion compared to debt of $28.8 billion at the end of Q3 2025. The company reported operating cash flow of $30 billion and free cash flow of $10.6 billion after deducting $19.4 billion of capex. Meta recently used hybrid debt by entering a $27 billion joint venture with Blue Owl Capital to fund its development of Hyperion Data Center. The complex financing structure will help the company keep debt off its own balance sheet.

Note: To ensure an accurate comparison our 43% and 63% calculation for Microsoft and Meta excludes financial leases, which management includes while discussing capex.

Source: Company IR

On the other hand, a surge in the credit default swaps (a form of insurance against default for bondholders) of Oracle indicates that investors are worried about its debt levels. Oracle has $10.5 billion in cash and a high debt of $91.3 billion at the end of the August quarter. The company raised an additional $18 billion following its results. The company reported operating cash flows of $8.1 billion in the recent quarter. However, due to the high capex of $8.5 billion, the company reported a negative free cash flow of ($362 million). The company has a high capex to operating cash flow percentage of 104%.

CoreWeave is a leading AI infrastructure stock. However, high capex is leading to negative free cash flows. The company has cash of $2.5 billion and a high debt of $14 billion at the end of Q3 2025, with a net debt position of $11.5 billion. The debt has increased from $8.7 billion in Q1 to $11.1 billion in Q2 and further increased $3.0 billion in the recent quarter.

Similarly, Nebius has an extreme high capex to operating cash flow percentage of 1185%. The company reported an operating cash flow of ($80.6 million) and a free cash flow of ($1.04 billion) owing to high capex of ($0.96 billion) primarily driven by purchases of GPUs and GPU-related hardware, and the data center expansion activities.

Conclusion

For years, the I/O Fund has been a pioneer in identifying winners by recognizing the positive correlation between AI stocks and the increase in Big Tech Capex. While many are busy debating whether Big Tech’s AI spending will translate to revenue and profits, and more recently concerned about the useful life of servers. Meanwhile, during those years, the I/O Fund has been laser focused on where that AI capital is actually being allocated. Rather than thinking of our approach as the picks and shovels for those chasing a gold rush, we think of it as an “AI stack” strategy—investing in the lesser-known layers and components that are driving forward an ecosystem capable of massive GDP.

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

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TeraWulf Q3: Fluidstack/Google Deal Expands yet Debt Surges and Power Remains an Industry-Wide Bottleneck

Posted on November 12, 2025June 30, 2026 by io-fund

In our previous coverage on TeraWulf, we estimated the value of the Fluidstack deal to be $700 million in annual revenue. Management stated the lease was worth approximately $670 million with net operating income worth $565 million. The inflection point for this stock is fairly evident given the company recognized its first HPC leasing revenue in the third quarter of just $7.2 million, or more than 14% of revenue. This represents HPC capacity of 60MW by year-end that will expand roughly 6X to 366MW by end of 2026.

In the most recent report, an additional 168+ MW was announced with Google backstopping $1.3 billion in lease obligations in similar fashion to Terawulf’s existing deals. The deal may complicate the income statement as TeraWulf owns 50.1% of the JV, therefore, it’s possible the company recognizes 100% of the revenue yet sees about half of the net operating income. It comes with the added benefit of seeing lower capex costs, which may be the motivating factor behind the deal terms. For investors, if the company does not announce the deals on the attributable basis, then it requires an additional step to recalculate at 50.1%.

The debt for TeraWulf is rising quickly as the company had $712.8 million in cash and equivalents with debt of $1.5 billion by quarter end. However, debt has increased $4.2 billion in October alone to fund the upcoming data center buildouts. Here was the most recent update: “Turning our attention to the balance sheet. As of September 30, we held $712.8 million in cash and restricted cash with total assets amounting to $2.5 billion and total liabilities of $2.2 billion. In October, we closed over $4.2 billion in capital markets transactions, including $3.2 billion of 7.75% BB-rated senior secured notes due 2030 and $1.025 billion of 0% convertible notes due 2032.”

TeraWulf Optimistically Outlines 2GW Pipeline by 2028

As of August, TeraWulf outlined a pipeline of just 1.15 GW of gross capacity through 2030, with 522.5 MW of that capacity contracted out to Core42 and Fluidstack (excluding the recent JV).

Source: TeraWulf

This projection resulted in 600-650MW of available capacity through 2030, with TeraWulf laying out a framework to add ~175MW per year starting in 2027 to culminate in the full 600-650MW coming online by 2030, or 48+ months away. For the miner thesis that is built upon speed of power delivery, this projection does not appear as attractive to peers who could potentially deliver gigawatt scale sites over the same period.

As such, TeraWulf provided an updated, more aggressive and accelerated pipeline projection in Q3’s update, now targeting as much as 2GW of capacity by 2028 in an optimistic scenario. The updated projection below assumes the 1.1GW could come as early as next year, before scaling to 1.1 to 1.6GW by 2027 and potentially as high as 2GW by 2028. TeraWulf added that future capacity includes other potential joint venture sites, another 500MW of owned capacity, and a 1GW+ pipeline.

Source: TeraWulf

TeraWulf CEO Paul Prager said that he “would not be surprised if by year-end, we announced at least one, possibly two additional sites,” while CFO Patrick Fleury added that there were a handful of sites in consideration that could fulfill that 1GW pipeline.

Building on this, Prager said that TeraWulf “recently increased our annual target for new HPC signings from 100 to 150 MW per year to 250 to 500 MW per year [which] reflects the tangible progress we've made in advancing our development pipeline and the strength of customer demand.” This suggests that TeraWulf is looking to accelerate the development of this pipeline and quickly add this GW to its portfolio, yet the main question is how the company will be able to do so given its current developments are burning quite a big hole in its pocket.

Breaking Down TeraWulf’s Capacity and Timeline

In our previous coverage, TeraWulf stated CB-1 would generate revenue by end of October, CB-2 by the end of the December quarter and CB-3, CB-4 and CB-5 are on a tight timeline with the goal of being delivered within a year.

Here is the update:

As stated in the intro, the first HPC revenue was reported from CB-1 (on time)
CB-2 is on track for near year-end “subject, of course, to tenant fit-out requests, which will complete our delivery of 60 megawatts of critical IT for Core42.” (slight tone change as previously it was by end of December quarter)
Regarding CB-3, CB-4 and CB-5, the update was more vague stating “CB-3 is more than 50% directed and the structure will be fully enclosed before year-end" with “CB-4 and CB-5 are already well underway with underground work beginning next week, field deliveries arriving in early December and building erection expected to begin before Christmas”

According to the investor’s presentation. CB-2 is expected to be operational and contribute to results in the December quarter for Core42, with Fluidstack’s 450MW at CB-3, CB-4 and CB-5 layering in through 2026. However, as you can see above, the commentary on the earnings call was less concrete.

The Risk for Bitcoin Miners is Execution – But Especially in Procuring More Power

The company increased the annual target for new HPC signings “from 100 to 150 megawatts per year to 250 to 500 megawatts per year” – which is stated as “HPC signings” and does not address the timeline around delivery.

Investors must essentially take the Miners at face value they will deliver with very little prior experience executing (and arguably, the challenges around executing will only get harder given it will be energy related – outside of their control):

“I'm not terribly worried about the HPC side. I feel pretty good about that and procurement capability and supply lines aren't what they were. I feel very good about that. I think that the key is going to be our ability to meet schedule and price. That's what the Street is looking for. That's what our customer wants. That's what we promised to our shareholders. So I'm very comfortable at 250 to 500. And as we grow, listen, we're building, as Patrick used to say, serial model # 6. As we get down to 10 or 11 and we find more efficacious ways to do this and needer ways to scale, then we could grow from there. But I think 250 to 500 is the right way to think about us for the coming year.”

An interesting exchange occurred when an analyst asked TeraWulf how they plan to get power for the 250 to 500MW annual delivery schedule. Initially, management sidestepped the question, and when pressed, their answer underscored that energy availability lies largely outside of their control.

This is a crucial point: even as TeraWulf scales its EPC and site-development capabilities, the real bottleneck remains interconnection and power procurement — both dictated by utilities, grid regulators, and the slow cadence of transmission upgrades. Management’s confidence in build execution (“the EPC side”) contrasts sharply with their limited influence over when and where new megawatts will actually be energized.

“John Todaro
Needham & Company, LLC, Research Division

Great. That's super helpful. And then second question, if we do just take a step back, I guess, how are you guys able to add more of the power pipeline? Like some of the stuff was procured pretty quickly like Abernathy. I would just have to think major hyperscalers, Neo cloud, maybe private equity, everyone is competing now. Just, I guess, give us — frame it up a little bit more for how you guys are able to win that.

Paul Prager
Co-Founder, Chairman & CEO

Yes. I'm not sure I understand the question. I mean — Abernathy didn't — I wouldn't look at that as came on real quickly. I would — again, we've had a long-term relationship now with Google and Fluidstack. And so we are aware of the strategy here, and they decided that bringing us alongside would be additive to the overall effort. But I'm not sure I understand the balance of your question.

John Todaro
Needham & Company, LLC, Research Division

I guess just the main crux of it is if we take a step back and there's such a power constrained environment, one of the biggest questions we get from investors is just how these guys are able to continue to procure capacity like that 250 to 500 megawatts you talked about when we are in still a constrained environment, and there's just likely so many bidders for these assets.

Paul Prager
Co-Founder, Chairman & CEO

Yes. I think the answer is — so some of them are looking at island generation where they bring their own power. Some of them are looking at high electrification sites that had former industrial uses and they're looking at repositioning them into data centers. And some of them are talking to utilities about figuring out if there's a way that they could work out a deal like the NextEra transaction.

I think they're following multiple strategies to get to the answer of they have long-term demand, and it's near term in terms of its immediate urgency, but they're looking at the 25- and 30-year deals. If you take a look at the Abernathy deal, it's 25 years.

So I'm — I can't tell you or opine to what the long-term answer is other than United States needs to build more generation. But I think everyone's figured that one out. The question is, are there sites that one can discover in the right regulatory frame set and from an environmental perspective, not too injurious to a customer that could enable a high-quality credit to come along and be a customer. And I think the answer is yes, but you got to know where to look.

I guess I should emphasize TeraWulf where to look, which is why I think prior to year-end, we'll be bringing on at least one, maybe two other sites.”

In perhaps the most interesting comment of the earnings call, TeraWulf’s management stated other Miners are providing “fictitious pipelines” – an important warning to investors that talk is cheap compared to what is required to stand up powered shells: “And again, I think unlike some of our peers, we're not telling you a fictitious pipeline of thousands of megawatts all in the same region. We're telling you about stuff when it's literally imminent and ready to go.”

There was another interesting comment on the call from management stating it could take 3-4 years in some instances to get power to some of the sites being covered as announced deals: “Demand is real, and it's a constant. And I think that — listen, I think there was a site out in Ohio the other day. They got a letter from AEP saying they were in the queue and they were in the queue for '26. And now you should probably not think about that power in '26, but you should think about it for like '29 and '30. And that is a way of saying that you've got to pick your sites really carefully. You have to understand what the grid is capable of. Are you in an area where the whole grid is only X and the demand is 3x that.

So it goes to the notion that you've got to have a very good handle where you site these things. But that then — when you go back to the customer and you say, hey, how do you want to think about it if you want to be in this region, you're okay moving from '26 to '27. The answer has been yes, universally. The answer from '27 to '28 is yes. I don't think you get the power problem solved by then. You've got hyperscalers now looking at island generation, which means they're going to bring their own power to the table, and that's at least four to five years away.”

>$5 Billion in Debt, Convertibles Raised Recently

Since August, TeraWulf has raised $5.2 billion in secured debt and convertible notes, including a major $3.2 billion raise, to help fund its data center expansion. In total, these three raises are equivalent to approximately 91% of TeraWulf’s current $5.7 billion valuation.

The two convertible note raises in late August and the end of October were both for ~$1 billion, with one a 1% coupon due in 2031 and the other a no-coupon due in 2032, giving TeraWulf time to scale operations and expand its data center business accordingly with minimal interest expenses associated with the funding.

However, the $3.2 billion in secured debt the company raised in mid-October came at a hefty 7.75% rate, meaning TeraWulf will face nearly $250 million in annual interest payments through 2030.

Cash flows and debt are rapidly coming into focus for AI data center stocks, as names like Oracle have recently come under pressure for the enormous debt load the company is expected to inherit to fund the its ambitious data center plans. For example, there is rumored to be a $38 billion debt offering as soon as next week, with Morgan Stanley stating the figure could be as high as $55 billion to $75 billion. For TeraWulf, the company is quickly taking on a high debt load to expand its data center business, yet post-sweep cash flows through 2030 are projected to be minimal.

Illustrative Revenue, Cash Flow Projections

TeraWulf is expecting a rather sharp revenue ramp through 2026 into 2027 as its capacity for Fluidstack comes online, with the company currently projecting CB-3 to be operational in Q1 2026, followed by CB-4 in Q3 and CB-5 in Q4 2026. TeraWulf’s current internal estimates point to 3x growth from $210 million in 2026 to $653 million by 2027.

Once the three buildings are operational, revenue is expected to flatline and increase per the annual escalators under the deal, with growth of just $23 to $25 million YoY (~3%) from 2028 through 2035.

Cumulatively, TeraWulf is roughly projecting revenue of ~$3.06 billion from 2025 through 2030 from data center hosting, with net operating income of $2.65 billion, an ~86.5% margin. However, despite the strong NOI generation, cash flows post-sweep (minus mandatory amortization, debt interest expense and a 50% sweep) are minimal.

TeraWulf is currently estimating cumulative post-sweep cash flows of $281 million through 2030, not even 10% of cumulative revenue. This is because TeraWulf is facing high mandatory amortization, from $281 million to $308 million from 2027 to 2030, and high interest payments on debt. This would leave TeraWulf with limited cash flow to fund additional data center projects or accelerate deployment timelines on its own.

Financials Overview

Revenue

TeraWulf announced preliminary Q3 revenue of $48 million to $52 million, up approximately 84% YoY and coming in shy of the $56.3 million consensus estimate. Actual revenue for the quarter was $50.6 million, up 87% YoY and slightly ahead of the midpoint of the preliminary guide.

The company’s first HPC data center, CB-1, was operational in August, making Q3 the first quarter blending both BTC mining and HPC revenues, which were just $7.2 million in Q3.

AI Revenue

TeraWulf recognized its first HPC lease revenue of $7.2 million in Q3, accounting for 14.2% of revenue. HPC lease revenue has a visible path to increase sequentially in Q4 as the 22.5MW CB-1 lease is now active and has a full quarter of contribution, and the 50MW CB-2 is nearing completion with operations expected before year-end.

HPC’s adjusted net operating income margin was $5.2 million, or ~72%, which was below the ~85% guided due to partial lease revenue recognized in Q3 and development costs incurred at Cayuga. This is expected to normalize in Q4 to around the 85% level.

Margins and EPS

Margins show little improvement down the line from last year, though this is to be expected considering TeraWulf is still ramping capacity through 2026.

GAAP gross margin (excl depreciation) was 66.1%, up from 53.6% last quarter and 45.8% in the year ago quarter. Adjusted gross margin (incl depreciation) was 13.7%, down from 14.2% last quarter but up from (12%) in the year ago quarter.

GAAP operating margin was (48.8%) in Q3, widening from (32.7%) last quarter but improving from (58.1%) in the year ago quarter.

GAAP net margin was (899.7%) in Q3, impacted adversely by a ($424.6 million) change in warrant and derivative liabilities. Thus, GAAP net loss was ($1.13), not comparable to the ($0.05) estimate.

Preliminary adjusted EBTIDA for Q3 was forecast at $15 to $19 million, or a 34% margin at midpoint. Actual adjusted EBITDA was $18.1 million for a 35.8% margin, at the higher end of the preliminary range.

Cash Flows and Balance Sheet

TeraWulf reported $713 million in cash and equivalents, with current convertibles outstanding of $1.06 billion, though this does not include the recent ~$4.2 billion raised in October. However, TeraWulf expects to use all of the recent funding for the Fluidstack and CB-2 buildouts through 2026.

Pro-forma liquidity projected for 2026 is expected to be approximately $1 billion, including cash on the balance sheet; however, this is expected to go towards the joint venture and pipeline M&A, leaving little left over to build on more sites through 2026 without additional funding.

Operating cash flow was ($36.7 million) in Q3 for a (48.8%) margin, while free cash flow was approximately ($268.3 million) for a (530.4%) margin. Put another way, TeraWulf spent more than 5X its revenue on PP&E in the quarter.

Conclusion

TeraWulf is progressing with its HPC pivot as the company is now recognizing HPC related revenue, while eyeing a strong ramp in HPC revenue through 2027 as substantial capacity for Fluidstack comes online. Notably, execution risks for all Bitcoin Miners remain front and center as the bottleneck around power will intensify.

Despite the sharp revenue ramp over the coming eight to ten quarters, amortization and debt interest payments will keep post-sweep cash flows minimal, while future development of a 1GW pipeline or accelerated deployments will likely require more cash.

As you’ll see, there is a common theme to where many of the AI infrastructure plays will require the market being in an optimistic mood as the opportunity is immense yet the path to execution is tricky. We will participate when the correct setup materializes, but we will also step aside if needed.

Damien Robbins, Equity Analyst at I/O Fund contributed to this analysis.

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CoreWeave Q3: Timing Miss yet Backlog up 2X QoQ and up 4X YTD

Posted on November 11, 2025June 30, 2026 by io-fund

CoreWeave reported growth of 134% YoY for $1.4 billion in revenue yet missed fiscal 2025 revenue guidance due to a timing miss with a major hyperscaler. The revenue will now be recognized in Q1 due to a delay in the powered shell: “As mentioned, the delays in powered-shell delivery associated with the data center provider will have an impact on our fourth quarter results. These delays are temporary, and as Mike noted, the affected customer has agreed to adjust the delivery schedule to preserve their capacity for the full duration and the total value of the original agreement.”

The new fiscal year guidance is for revenue of $5.05 to $5.15 billion compared to previous guidance for revenue of $5.15 to $5.35 billion. The timing miss also caused the company to reduce capex by 40% to $12-$14 billion compared to the previous guidance of $20-$23 billion. This will represent revenue growth of 165.6% compared to previous expectations for growth of 173.4%.

AI investors may want to get comfortable with delays in recognizing revenue due to power constraints. We’ve been preparing for this with ample exposure to AI data center energy in our portfolio.

CoreWeave’s fundamental profile has some puts and takes. The margins are strong yet the cash remains troublesome. For example, CoreWeave is a recent IPO that is already GAAP positive on operating margin at 4% and reported an adjusted EBITDA margin of 61%. However, the company reported negative free cash flow of ($1.6 billion) with $14 billion in debt and $2.5B in cash on the balance sheet. This leaves net debt of $11.5 billion – yet this is mild given what the company plans to spend in capex next year (expect the debt to go up rapidly).

Overall, the buildout that AI requires will need the market to be in high spirits as there is a glass half-full and a glass half-empty exercise to many of these high growth names that are reporting high debt leverage ratios. The backlog of $55B represents nearly double Q2 and is approaching 4X YTD yet the debt is also up 2X YTD. There are no new major red flags in this report; rather CoreWeave is on a trajectory of high growth-high debt for the foreseeable future.

For additional context, you can read our previous coverage on CoreWeave, where we outline the broader opportunity and what makes the AI infrastructure company unique despite having large competitors.our previous coverage on CoreWeave, where we outline the broader opportunity and what makes the AI infrastructure company unique despite having large competitors.

Backlog Soars yet Powered Shells are the Bottleneck

The company stated the backlog grew by $25 billion to $55.6 billion, up from $30.1 billion for growth of 85% QoQ. Although backlog helps to illustrate that we are years away from AI being a demand problem, one has to wonder if backlog and RPO key metrics are really all that useful given power-related bottlenecks are led to a miss in fiscal year guidance.

Overall, key metrics that illustrate supply are preferred – such as CoreWeave stating their active power footprint grew by 120MW sequentially to approximately 590MW with contracted power capacity growing over 600MW to 2.9GW. That represents 25.5% QoQ growth. Management expects to end the year with over 850 megawatts of active power.

According to management: “And as Nitin said, we expect the overwhelming majority of that 2.9 gigawatts of power to be brought into service over the next 12 to 24 months.” That would imply nearly 400% growth over a two-year period from 590MW to 2.9GW, if all else remains equal.

Analysts asked what led to the timing delay with the CEO leaning into the issue by stating they expect to see powered shells leading to more delays in the near future: “So you're going to be hearing this theme repeated again and again as you talk to not just CoreWeave, but you talk across the space. And it is a real challenge at the powered-shell level. It's not a challenge for power, right? There's plenty of power right now, and we believe that there will be ample power for the next couple of years. But really where the challenge is, is the powered shell.”

Note, we listen to many earnings calls and although CoreWeave is connecting dots that the bottleneck can persist beyond simply securing power, the widespread issue is certainly related to the availability of power. However, the sentiment is the same as I believe CoreWeave is communicating that even after a customer secures power, there is still more work to do and potential delays before they can recognize revenue. For example, delays could be regulatory in nature to where states like Texas require extra steps, etc.

There are no major red flags from this delay as management assured investors that the customer agreed to extend the expiration date with CoreWeave maintaining the total value of the original contract.

Financials

Strong Revenue Growth of 134%

CoreWeave’s Q3 revenue grew by 133.7% YoY and 12.5% QoQ to $1.37 billion. The company beat analyst consensus estimates by a solid 6.6%, driven by continued strong demand for the company’s AI cloud infrastructure services.

While the underlying business momentum remains strong, the company reduced its full -year revenue guidance by $150 million at the midpoint due to a timing miss with a major hyperscaler. The revenue will now be recognized in Q1 due to a delay in the powered shell. The new fiscal year guidance is for revenue of $5.05 to $5.15 billion, compared to the previous guidance of $5.15 to $5.35 billion. It would imply that the Q4 revenue of $1.54 billion, representing a YoY growth of 106% and 12.8% QoQ. They were below the analysts' estimates of $1.79 billion.

Management stated in the earnings call, “Now turning to guidance. As mentioned, the delays in powered-shell delivery associated with the data center provider will have an impact on our fourth quarter results. These delays are temporary, and as Mike noted, the affected customer has agreed to adjust the delivery schedule to preserve their capacity for the full duration and the total value of the original agreement.”

Looking ahead, analysts expect 2026 revenue to grow 132% YoY to $12.23 billion, and these estimates will be increased due to the push-out caused by the delay in Q4 revenue recognition to Q1. For 2027, revenue is expected to grow 49.4% YoY to $18.27 billion.

Product innovations included the launch of CoreWeave AI Object Storage. It is a fully managed storage service that eliminates the friction of moving data between regions, clouds, and tiers, with zero egress or transaction fees. Management also highlighted that CoreWeave's AI Object Storage delivers the highest throughput for AI workloads while cutting customers' costs by more than 75%.

Robust Backlog of $55.6 billion

The company’s Q3 backlog grew by 85% sequentially to $55.6 billion. Management stated: “Demand remains robust for not just the Blackwell platform but across our GPU portfolio. In the third quarter, we signed a number of deals for older generations of GPUs, adding new customers and recontracting existing capacity.” Management also highlighted that they reached $50 billion in RPO, faster than any cloud in history.

Broad-based growth is positive as it will help the company reduce customer concentration. Currently, the largest customer accounts for 35% of the revenue backlog, down from 50% in the previous quarter and 85% at the beginning of the year.

In Q3, the company executed large-scale compute contracts with many of the largest customers, including Meta and OpenAI. We have discussed it in our analysis here. The company entered a $14.2 billion multi-year deal with Meta and expanded the OpenAI partnership with a $6.5 billion deal, bringing total commitments to up to $22.4 billion.

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. It also represents a significant expansion of existing relationships and a diversification away from reliance on any single customer. No single data center provider represented more than 20% of the contracted power portfolio.

The company also entered the US federal market, which should further help to diversify its customer base. CoreWeave will provide secure, compliant, high-performance AI cloud services to US government agencies and their key partners, including the Defense Industrial Base. NASA already uses its services to advance scientific exploration at its Jet Propulsion Lab.

Margins

The company is investing heavily in data center and server infrastructure to meet robust AI demand from its customers. The operating expenses are front-loaded, resulting in a short-term impact on margins.

Q3 gross profits grew by 126% YoY to $995.85 million with a gross profit margin of 73%, down 200 basis points YoY and 100 basis points sequentially.
Q3 operating margin was 4%, down from 20% in the same period last year and up 200 basis points sequentially. The operating expenses increased 181% YoY to support strong growth. The adjusted operating margin was 16%, compared to 21% in the same period last year. However, it was better than the management guide of 14% primarily due to higher revenue, lower costs due to timing of data center deliveries from third-party partners, and improved fleet efficiencies.
The company’s adjusted operating margin guide for Q4 is expected to decline to 8%. Management stated: “In Q4, we will be bringing online some of the largest scale deployment in our company's history. This will have a near-term impact on adjusted operating margin due to the timing difference between when data center costs are first incurred and when we start recognizing revenue.”
Adjusted EBITDA grew by 121% YoY to $838.1 million with an adjusted EBITDA margin of 61% compared to 65% in the same period last year.

EPS

Q3 GAAP EPS was ($0.22) compared to the analysts' estimates of ($0.51). However, the strong beat was due to a one-time noncash tax benefit of $0.25. Excluding the one-time benefit, the company would beat estimates by $0.04.

Looking forward, analysts expect GAAP EPS of ($0.84) in 2026 and to be GAAP profitable in 2027 with an EPS of $1.63.

Cash Flow and Balance Sheet

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.

Free cash flow was ($1.6 billion) compared to ($573.9 million) in the same period last year and ($2.7 billion) in the previous quarter.
The revenue timing miss also caused the company to reduce its full-year capex by 40% to $12-$14 billion compared to the previous guidance of $20-$23 billion. Most of the remaining capex that was previously anticipated in Q4 will now be recognized in Q1. Management expects capex in 2026 to more than double from 2025.
Cash was $2.49 billion, and debt was $14.03 billion compared to cash of $1.7 billion and debt of $11.05 billion in the previous quarter.

Conclusion:

Increasingly, management conversations for AI buildouts are about credit terms – more so than compute, and perhaps equal to the discussions on energy. We do an extensive checklist after each earnings report to remove emotion from our portfolio decisions and the fact is that CoreWeave has a debt ratio that is 5-6X EBITDA – and this will only get steeper.

Compare that to Nvidia at 0.1X (or negligible). There are lower risk ways to participate in AI, yet the positioning CoreWeave offers is second to none. The company is in the “build” phase but will eventually be in the “yield” phase.

In the interim, we expect to approach this name tactically, as performance is likely to hinge more on market temperament than on a fundamental change in the AI hyperscaler’s long-term prospects.

The yield phase is one we intend to participate in. To illustrate the yield CoreWeave could be capable of, consider the company reached $50 billion in RPO – faster than any cloud provider in history. This, along with other execution metrics, suggests the company could be laying the foundation for a long and meaningful runway in AI infrastructure.

I/O Fund Equity Analyst Royston Roche contributed to this analysis.

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Innodata on Pause until 2026 Story Develops Further

Posted on November 7, 2025June 30, 2026 by io-fund

Innodata’s AI segment slowed from 99% YoY growth last quarter to 22.6% YoY growth this quarter, although on a QoQ basis there was some improvement with 8.3% growth compared to essentially flat last quarter.

However, the company is twiddling its thumbs (so to speak) until the next deal is announced. With nothing concrete to add this quarter, there was instead vague talk around their biggest customer expanding “based on verbal confirmation.” Management does believe 2026 will be stronger with $26 million in pre-training data wins expected to be signed “very soon” and “new partnerships emerging with key AI and sovereign AI players, which we expect to be announcing in 2026.”

According to management, there are eight potential customers with five expected to contribute meaningfully in 2026. In terms of how much revenue they can contribute, the following was shared: “Three of these new five, we believe, are positioned to allocate up to hundreds of millions of dollars annually to generative AI data and evaluation, and we believe we’re well-positioned to capture a share of that spend. It is worth noting that two of these are global leaders in commerce, cloud, and AI.”

Overall, it’s difficult to sit in the waiting room on any AI stock right now. With a name like Innodata, we prefer to remain balanced and to wait for more tangible evidence that new deals are materializing. Opportunity cost comes to mind when there are other AI names already showing clear acceleration in deal flow and revenue contribution today.

Q3 Revenue Beat by 4.6%

Revenue grew by 19.8% YoY to a record $62.6 million, beating estimates by 4.6%. Revenue growth decelerated from 79.4% in Q2, which was expected. It grew by 7.1% sequentially and was better than flat in the previous quarter.

Management reiterated the annual guidance of 45% or more growth for the full year. They stated: “We reiterate guidance we provided last quarter of 45% or more year-over-year organic revenue growth in 2025, and we anticipate continued transformative growth in 2026 based on new wins and strong momentum.”

Looking ahead, analysts expect revenue to grow 22.8% YoY to $303.8 million in 2026 and 3% growth to $313 million in 2027. These estimates could be revised higher based on the new deals in the pipeline.

Innodata Federal Business Unit Launched

The company also announced the launch of Innodata Federal, a dedicated government-focused business unit designed to deliver mission-critical AI solutions to U.S. defense, intelligence, and civilian agencies. Management expects this business unit to be a material revenue generator for the company in 2026 and beyond. The business unit has won an initial project with a new high-profile customer. They anticipate that the initial project will generate approximately $25 million in revenue, primarily in 2026.

The company has additional projects under discussion with the customer, and they anticipate that these projects will be substantial. Management expects to issue a press release regarding the relationship prior to the end of the year. These projects are expected to be a potential game-changer for the next phase of growth. The new partnership is strategically significant, representing a material top-line opportunity.

AI Segment grew by 23%

Innodata’s Digital Data Solutions (DDS) segment grew by 22.6% YoY to $54.8 million. This AI segment slowed from 99% YoY growth last quarter, although on a QoQ basis, there was some improvement with 8.3% growth compared to essentially flat last quarter. Also, it had tough comps as the company reported a strong YoY growth of 179% in the same period last year.

Management was also optimistic about the enterprise AI opportunity and mentioned that it was also gaining traction and holds promise for 2026. Innodata provides full-stack support to help enterprises integrate generative AI into products and operations.

Synodex segment revenue was down (14.6%) YoY to $1.65 million compared to a 4% growth in the previous quarter.
Agility segment revenue grew by 9.3% YoY to $6.1 million compared to an 11.5% growth in the previous quarter but was up 6.4% sequentially.

Margins

The company’s gross profits grew by 19.6% YoY to $25.5 million with a margin of 40.8%, which was flat YoY and up 80 basis points sequentially. The adjusted gross margin improved by 40 basis points YoY and 130 basis points sequentially to 44.2%.

Operating income was up 3% YoY to $11.8 million. Operating margin was 18.8%, down 310 basis points YoY, but was up 350 basis points sequentially. The operating expenses increased by 38.7% YoY to $13.7 million, primarily due to new hires. Management expects operating expenses to increase to support strong expected growth.

Net income was $8.3 million compared to $17.4 million a year ago. The decrease was primarily due to the tax benefit arising from the utilization of net operating loss carry forward in the same period last year.

Adjusted EBITDA grew by 16.9% YoY to $16.2 million with an adjusted EBITDA margin of 25.9%, down 60 basis points YoY and up 320 basis points sequentially.

The DDS segment adjusted EBITDA margin was 27.8%, up 70 basis points YoY.
Synodex segment adjusted EBITDA margin was 8.2%, down 19.2 percentage points YoY.
Agility segment adjusted EBITDA margin was 14%, down 8.1 percentage points YoY.

EPS beat by 75%

The company’s GAAP EPS came at $0.24, beating the analyst’s estimates by 75.2%. Analysts expect GAAP EPS of $0.21 and $0.24 in the next two quarters.

Looking forward, analysts expect GAAP EPS to grow 40.8% YoY to $1.07 in 2026 and 21.5% YoY to $1.30 in 2027.

Cash Flow and Balance Sheet

The company has a healthy balance sheet.

Q3 operating cash flow was $18.77 million or 30% of revenue compared to $11.37 million or 21.8% of revenue in the same period last year. The company also benefited from an $8.0 million cash payment received in the recent quarter, which would have otherwise been received by the end of Q2.
Q3 free cash flow was $14.5 million or 23.2% of revenue compared to $9.92 million or 19% of revenue in the same period last year.
The company’s cash was $73.86 million at the end of the quarter, up from $59.8 million at the end of the previous quarter. The company has no debt.

Conclusion:

As stated above, it’s difficult to sit in the waiting room on any AI stock right now. With a name like Innodata, we prefer to remain balanced and to wait for more tangible evidence that new deals are materializing. Opportunity cost comes to mind when there are other AI names already showing clear acceleration in deal flow and revenue contribution today.

I/O Fund Equity Analyst Royston Roche contributed to this analysis.

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Market Cycles, Not Headlines: What History Says About the 2025 Rally and What Comes Next

Posted on November 6, 2025June 30, 2026 by io-fund

Despite how it may seem, modern-day narratives rarely drive market swings. Tariffs, political headlines, niche trends like rare earth materials, or speculation about which company OpenAI partners with next — these stories dominate the news cycle, but they do not reliably move markets, as the consensus believes. If they did, investing would be much easier.

Numerous well-known studies have come to this conclusion. One of the most famous is “What Moves Stock Prices?” by Harvard and MIT economists Cutler, Poterba, and Summers. Their goal was to model how news and macroeconomic events might predict stock market movements. To their surprise, they found that only about one-third of major price swings could be linked to identifiable news events.

This finding was later reinforced by Yale economist Ray Fair in his groundbreaking paper, “Events That Shook the Market.” Fair examined major one-day movements in the S&P 500 from 1950 to 1999 in search of their causes. He concluded that neither news, earnings, nor data releases could explain most of these large jumps. As Fair put it, “It is difficult to find any news that corresponds to many of the largest daily changes in stock prices.”

We’ve seen this phenomenon play out in real time. The COVID crash was perhaps the most striking example. Economic data went off the charts: 26 million Americans filed for unemployment within five weeks, as GDP fell 31.4% annualized — the steepest drop since World War II. Yet the stock market bottomed at the height of this deterioration and uncertainty, staging a V-shaped recovery that was impossible to justify by the data alone.

There are many forces that shape markets — liquidity, growth, and monetary and fiscal policy among them. But there are also powerful, less tangible forces that economics struggle to explain. One of these is herd sentiment, which we explored in last week’s report, Decoding the S&P 500: When Human Sentiment Meets Artificial Intelligence.

This week, we’ll turn to another underappreciated but potent influence on markets – cycles. Much like natural phenomena, financial markets move in rhythmic, repetitive patterns that can be observed, analyzed, and applied to better understand broader trends.

Understanding market cycles is essential for anyone seeking to interpret market behavior beyond the noise of daily headlines. While news and data provide short-term context, the deeper rhythm of expansion, contraction, and renewal has repeated throughout centuries of market history. These cycles reflect the underlying forces of liquidity, sentiment, credit, and innovation that collectively drive long-term trends. By studying them, investors can gain perspective — identifying where we may be in the broader sequence of optimism and fear — and making decisions grounded in historical precedent rather than emotion.

In this report, we will look at two dominant cycles that closely align with the price action in 2025. Both suggest a potential year-end rally, followed by the potential for volatility into Q1 of 2026. We’ll then line these cycles up with the broad market to outline what levels must hold, and what targets this uptrend is hitting, as we push higher.

The Gann Cycle Framework: Predictable Rhythms Behind Market Movements

The concept of market cycles gained mainstream attention through Neil Howe and William Strauss’s theory The Fourth Turning, which proposes that history unfolds in recurring 80–100-year cycles based on generational shifts. Each “turning” reflects a distinct societal mood—ranging from confidence and expansion to crisis and renewal—that repeatedly shapes political, economic, and market behavior.

However, the study of cycles long predates Howe and Strauss. In 1862, economist Karl Juglar identified what became known as the Juglar Cycle—an 8 to 11-year rhythm of expansion and contraction that still appears in modern market data. Juglar’s work established the foundation for viewing markets not as random systems, but as recurring patterns driven by predictable phases of human and economic behavior.

Decades later, W.D. Gann advanced this concept into one of the most comprehensive frameworks for understanding market structure. Gann demonstrated through decades of analysis that market movements often unfold in rhythmic, repeating patterns tied to both human psychology and natural law. His research suggested that the same behavioral and structural forces that shaped past bull and bear markets continue to influence markets today.

Gann identified several “master cycles”—notably the 100-year, 90-year, 60-year, 52-year, 45-year, and 30-year cycles. At any given time, one or more of these cycles, as well as divisions of these cycles, tend to influence the prevailing market trend. He used these relationships to issue remarkably accurate forecasts, many of which have held up over time.

While this may sound abstract, it holds historical merit. For example, 90 years back from the 1929 market top takes us to the end of the 1839 speculative boom, which ended in the Panic of 1839. Counting 90 years forward from 1929 brings us within months of the COVID top in 2020—an equally significant inflection point.

Another example is Gann’s 60-year “Great Cycle.” When we overlay the S&P 500 from 1962 onto today’s market starting in January 2022, the patterns align with remarkable similarity. While cycles can invert or distort temporarily, they consistently identify key inflection points and general directional bias.

How the S&P 500 (2022–2025) Aligns with the 60-Year Historical Market Cycle

Chart by I/O Fund

Because sentiment moves in waves, the emotional extremes of fear and greed remain timeless. While technology, policy, and liquidity conditions evolve, the human response to opportunity and risk does not. Even if equities rise in 2025 on optimism surrounding AI, investor psychology mirrors that of prior generations—driven by the same patterns of exuberance and denial.

To see how these long-term cycles manifest in real markets, let’s look at two historical periods that mirror 2025 with uncanny precision.

With this in mind, we examined historical precedents for 2025—a year defined by a rapid 20% decline in Q1 that erased nearly all of 2024’s gains, followed by a strong seven-month rally with limited pullbacks. These conditions—a liquidity shock followed by a sharp rebound—are rare. Over two centuries of data, only two market periods fit this mold: 1980 and 1998. Interestingly, both align with significant Gann cycles—the 45-year (half of the 90-year) and the 26-year (half of the 52-year) cycles.

To summarize: History may not repeat — but it often rhymes.

The 45-Year Market Cycle: How 1980’s Policy Shock Is Repeating in 2025

The market in 1980 has a striking resemblance to what we’ve seen unfold in 2025. In both periods, a swift and unexpected policy shock triggered a sudden liquidity event that sent markets sharply lower, followed by a rapid V-shaped recovery that defied expectations.

In early 1980, the Federal Reserve—newly under the leadership of Paul Volcker—launched an aggressive campaign to control inflation. The Fed pushed interest rates to nearly 17% in February, an unprecedented move that instantly drained liquidity from the system and sent equity markets into a sharp correction.

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Similarly, in early 2025, the executive branch imposed an unexpected increase in tariffs, creating a sudden liquidity squeeze that rippled across U.S. markets. The February decline that followed erased much of the prior year’s gains in a matter of weeks.

In both years, the shock proved temporary. Political pressure and a seizing credit market forced Volcker to reverse course in 1980, cutting rates back to roughly 9 percent. The result was an eight-month recovery that lasted through late November. Likewise, in 2025, just days after Liberation Day, the bond market began a disorderly unwind that pushed yields higher than the government could sustain. The policy reversal that followed restored liquidity and fueled a seven-month rally that continues today.

If this historical rhythm continues to guide market behavior, the current advance could extend through December, leading to a secondary high in mid-January followed by a period of elevated volatility into the second quarter of 2026.

How the S&P 500 in 2025 aligns with the 45-year cycle

Chart by I/O Fund

The 26-Year Market Cycle: How 1998’s Global Crisis Echoes Through 2025’s Rally

When we align the 26-year cycle with the 2025 decline, the parallels are difficult to ignore. The 1998 correction was sparked by a sudden global liquidity crisis that rippled through international markets. It began with the Asian Financial Crisis, as currencies in Thailand, Indonesia, and South Korea collapsed under the pressure of capital flight. The shock then spread to Russia, which defaulted on its domestic debt, setting off a global contagion.

One of the largest casualties was Long-Term Capital Management, a highly leveraged hedge fund managed by Nobel laureates and veteran Wall Street traders. As LTCM’s positions unraveled, liquidity evaporated across credit markets. Within two months, U.S. equities had dropped roughly 20 percent, forcing the Federal Reserve to intervene and backstop the system.

The Fed’s swift action reignited risk appetite, setting off one of the most powerful rallies in modern market history. Fueled by speculation about the transformative potential of the internet, investors poured into technology and growth stocks, propelling the market into the final and most euphoric phase of the dot-com boom.

While today’s AI leaders—such as Nvidia—are built on far stronger fundamentals than the speculative favorites of 2000, like Cisco and Pets.com, the behavioral pattern is strikingly similar. Both eras were defined by optimism surrounding an emerging technology with vast, untested potential and by investors’ willingness to price in future revolutions before they materialized.

If this 26-year cycle continues to guide the market, the current uptrend could extend through December and into the first quarter of 2026 before encountering the first meaningful correction. Unlike the 45-year cycle, however, this correction would likely be brief—more of a consolidation within a broader advance that carries into late 2026.

How the S&P 500 aligns with the 26-year cycles (1998)

Chart by I/O Fund

Interestingly, both cycles suggest continued strength into December, and both cycles suggest some period of volatility in Q1 of 2026. What separates the two is how far this uptrend pushes into Q1. While the 45-year cycle suggests a top in mid-December and lower high into mid-January, the 26-year cycle suggests a continuation of the aggressive uptrend into mid-Q1 of next year before seeing a small period of volatility.

Broad Market Levels

If we take the general direction of the above cycles and place it within the context of developing price patterns, there are two counts that best fit:

Subscribe for Free Below to see our updated game plan, which includes: 

The two scenarios we are tracking that best fit the potential cycles discussed in this report.
Critical support levels that must hold for a year-end rally to continue.
What the overhead targets are if we do see a rally into year-end.

One of these scenarios is starting to take shape — read this timely analysis below.

Blue – We are in the final swings of the rally off the April 2025 low. As long as any weakness holds SPX 6,552.50 – 6345, then we should see this rally continue into year-end, before seeing any notable volatility unfold into Q1 of 2026.
Green – This path follows the blue path above. The difference is that the Q1 period of volatility will likely only be a correction within a larger uptrend, which would then continue into 2026.

S&P 500 Elliott Wave Outlook: Key Scenarios Into Year-End 2025 and 2026

Chart by I/O Fund

In conclusion, as with all cyclical analysis, no one can say with certainty why a particular cycle takes hold or how long it will remain dominant. Markets often follow one rhythm until it loses influence, at which point a new cycle emerges and becomes the primary driver. The task for us as analysts is to identify which cycle is in control and the conditions that will sustain it.

At this stage, the 45-year and 26-year cycles appear to be the prevailing forces. As long as the SPX holds between 6,552.50 and 6,345 on any near-term weakness, the market is likely to continue tracking these patterns, both of which point toward the potential for continued strength into year-end.

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