Nvidia’s earnings report can best be described by a Shakespeare line in Henry IV: “Heavy is the head that wears the crown.”  When it comes to stocks, being on top is harder than it looks. You are no longer afforded the element of surprise, and particularly important for Nvidia, you must produce new catalysts that can contend with the previous, hard-hitting catalyst that drove the company’s historic growth in previous years. 

The catalysts on the horizon are imperfect, whether it’s custom silicon gaining traction as inference scales or the attach rate on CPUs-to-GPUs shifting as agentic AI requires more orchestration. Nvidia is also seeing heightened supply-related commitments, likely due to steep HBM and NAND pricing. The company is also changed its reporting segments, and below, I discuss why that raises concerns. 

However, on the positive side, Nvidia is a beast on the bottom line. Apple is firmly in the rear-view mirror when comparing profits and cash flows. Nvidia’s operating income is north of $50 billion compared to Apple’s $36 billion, plus cash flows that are nearly 2X Apple’s at $48.6B versus $28.7B. 

To be picky about its growth status, there is a deceleration in QoQ growth as the guide is for 11.5% QoQ growth compared to the previous three quarters, which all reported 19.5% to 22% QoQ growth. If we look a bit further ahead, analyst estimates are calling for flat-ish QoQ growth in the September quarter and then a leveling off to 7% and 6% QoQ growth. All of that will clear up when Rubin ships in volume, although as you’ll see below, the company left an out for themselves on the timing. 

I always enjoy covering Nvidia, because although the stock is well-covered, I think the I/O Fund continues to surface key details you don’t typically hear elsewhere. My strong Nvidia streak is slowing somewhat as I turn my focus to other opportunities across the AI trade, yet understanding the juggernaut is non-negotiable for all AI investors. 

Below, I take a closer look at what was communicated last night. 

The AI Demand Signal is Extraordinary 

As you’ll see below, Nvidia’s positioning is becoming more challenged by both custom silicon and CPUs. However, before we go into those details, the 10,000-foot view is fairly clear – which is that AI demand is parabolic. Collette Kress, the CFO, pointed out in the opening remarks that analysts expect hyperscale capex to exceed $1 trillion in 2027 with AI infrastructure reaching $3T to $4T by the end of the decade.  

This year, analysts are expecting capex to grow between 90% and 100% with Nvidia exceeding this growth rate with data center growth of 120%. As pointed out on the call, this is because Nvidia serves two major customer groups; the first being well-known hyperscalers and the second being neoclouds and enterprises. Whether it’s Nvidia specifically or the AI infrastructure market more broadly, the point Huang made on the earnings call is that far more than just 7 companies will support this market over the next few years: 

“The second category is all of the AI native clouds. They're regional, they're all over the place, they're start-ups all over the world, supporting those companies. They're enterprise, 250,000 enterprise companies around the world, many of them will have to build or want to build AI factories for themselves to operate. Many industrial companies, there's no choice but to put the computer where the context is, where the action is, you can't put that in the cloud. It has to respond reliably, quickly every single time, can't imagine a chip plant, a chip fab being connected to a cloud service provider, doesn't make any sense. And so the second category and the sovereign AI clouds. And so there's a whole category of data centers that semi-custom chips just don't apply because these data centers want to buy systems, they want to operate systems, they don't want to design, they don't want to build it themselves.” 

The point being made is two-fold. On one hand, it helps investors to see the diversity of customer base driving the AI market. On the other hand, it’s self-serving as Nvidia is likely preparing the market for a time when hyperscaler capex is more concentrated in custom silicon. We covered this in the free article recently, stating: “Counterpoint Research believes that by 2028, custom silicon will cross the 15-million mark to surpass GPU shipments as the top 10 hyperscalers will have deployed 40 million AI server compute ASIC chips cumulatively during 2024-2028.” 

Nvidia Changes Segment Reporting to Breakout Hyperscalers from Neoclouds/Enterprises 

If we operate under the assumption that custom silicon will become a fierce contender to GPUs within hyperscaler budgets, then the appropriate defensive move for Nvidia is to breakout the line item that shows they have a diverse set of customers.  

Pictured above: NVIDIA is transitioning to a new reporting framework that better reflects its current and future growth drivers. NVIDIA will have two market platforms — Data Center and Edge Computing. Within Data Center, NVIDIA will report two sub-markets, Hyperscale and ACIE, which incorporates AI Clouds, Industrial and Enterprise. 

The strong revenue trajectory in ACIE is communicating that Nvidia has other avenues for growth should we see a reduction of GPU-related capex spending. As stated above, Nvidia believes there is about 250,000 companies as the potential SAM for that segment, with the following granularity offered: “The second segment is AI natives, enterprise on-prems, industrial on-prems and that — and sovereign AI. That segment is growing incredibly fast because everybody needs AI, and we're going to see AI being adopted by every industry, every country, every company. And so everybody wants to build it in a different way. And the fact that we provide the entire solution, it makes it much easier, makes it possible at all for people to be able to build these things. And then, of course, the robotic edge today.” 

Overall, investors should be prepared for an expanding AI market to meet decreasing market share for Nvidia during the inference phase. Which brings me to my next two points. 

Nvidia’s Market Share in Question for the Inference Market 

Over the years, I’ve grown to have a keen ear for the commentary on earnings calls, and I do believe there was a mis-step last night with one Q&A exchange.

An analyst asked Huang: “How do you see Vera Rubin in your extreme co-engineering impacting your share of the inference market as we look into late '26, '27?”

In my opinion, management did not directly address the question. Instead, it redirected toward Nvidia’s growth in inference deployments, while mixing up an important distinction between growth versus market share.  

Of course, Nvidia is growing inference revenue and inference capacity. In the excerpt below, companies like Anthropic, Azure, AWS and CoreWeave are cited as evidence of this growing “share.” That wasn’t the question though. The question the whole market is wondering is whether Nvidia is gaining market share relative to the inference market.  

As you know, the market’s biggest concern is whether custom silicon will take a larger share of inference as workloads become more repetitive and cost-sensitive. The answer did not resolve that concern, and to me, it appeared the word “share” was being redirected to descriptions around “growth.”  

For example, Anthropic is deploying gigawatt-level inference workloads with custom silicon providers like Amazon/Trainium and Google/TPUs, therefore, to cite that Anthropic was “largely 0 until recently” does not translate to gaining share on Anthropic workloads as it actually means Nvidia is under-indexed or lagging on this very large inference customer. That’s one of a few inconsistencies in this critical Q&A exchange, with the main one being interchanging the words “share” with “growth” 

“Jen-Hsun Huang, Co-Founder, CEO & Director: 

Well, we are growing share in inference, and we're growing share in inference very, very quickly. And the reason for that is this year, the number of frontier model companies grew. And so there's Cursor and Perplexity and there's some new model companies, TML and Reflection, and the list goes on. And so the number of frontier model companies has grown, and we added Anthropic to our partnership this year. They're expanding incredibly fast. We've partnered with them to secure computing capacity across Azure, AWS, CoreWeave. I forget who else we've already announced, but there's a whole list of others that we are bringing online for them. And so the amount of capacity that we're going to bring online for Anthropic this year and next year is going to be quite significant, very significant.   

And so we're growing and our coverage of Anthropic has been largely 0 until just recently. And so we're gaining share tremendously fast in inference. Vera Rubin is going to be even more successful than Grace Blackwell at this point. Every single, I can't think of one. Every single frontier model company will jump on Vera Rubin from the get-go, and that wasn't true before on Blackwell. And so Vera Rubin is off to a tremendous start and it will surely be more successful than even Grace Blackwell.   

So I think the end of your answer, C.J., is that we're gaining share in inference. Let me go back again to the question that Ben was asking. Remember, so far, everything that I've just explained in the inference question is really focused on hyperscale. Remember, there's a whole second category of AI data centers that we serve almost uniquely. Now this segment is very fragmented, requires a fairly integrated — a really well-integrated platform solution and a very large go-to-market. And that segment, all of the inference, 100% of that — the vast majority of that is NVIDIA.” 

CPU-to-GPU Attach Rate is Increasing; What that Means for GPUs 

We covered the rising importance of CPUs in a recent analysis on Arm, stating: “In agentic workflows, the GPU still handles inference, but between each inference call, the CPU is doing the orchestration – which are best described as handling tool calls, API requests and memory tasks. AI agents are surfacing this new constraint, which is how to prevent latency and underutilized GPUs following the exponential growth of orchestration needs. 

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

According to TrendForce and commentary from Arm, it’s expected the CPU-to-GPU attach rate increases from 1:8 to a ratio of 1:2 or even 1:1. 

This helps explain why Nvidia spent a decent amount of time last night focusing on its Vera CPU designs: “Vera CPU opens a brand-new $200 billion TAM for NVIDIA, a market we have never addressed before, and every major hyperscale and system maker is partnering with us to get it deployed. We have visibility to nearly $20 billion in total CPU revenue this year, setting us up to become the world's leading CPU supplier.” 

However, this inevitably raises the question as to what this means for GPUs (i.e., will more AI compute spend be diverted from largely being GPUs to now include higher CPU content). One analyst went so far as to state it could cannibalize GPUs, of which Nvidia’s management team pushed back on.  The answer was long-winded so I am keeping only the excerpts that pertain to the concern.  

For more information on the topic, you can read our AMD post-earnings analysis here and Arm post-earnings analysis here.  

Vivek Arya 
BofA Securities, Research Division 

Jensen, there's a lot of excitement around CPU for agentic applications and just a lot of noise around the number of CPUs actually exceeding the number of GPUs. And I was just hoping that you could kind of give your perspective that, first of all, is this an incremental workload? Is this kind of cannibalizing what the GPU would have done otherwise? And then secondly, the $20 billion number that you gave, is that for stand-alone Vera CPUs? Or is that kind of already included in that Vera, as part of Vera Rubin? So just if you could educate us on the role of CPU versus GPU, is it cannibalistic? Is it incremental? And then the $20 billion number, how to kind of put that in context with what you sell, right, which is usually the CPU as part of the GPU? 

Jen-Hsun Huang 
Co-Founder, CEO & Director 

The $20 billion is for stand-alone CPU. And remember, we have Vera, is used in 3 ways. As a stand-alone — 4 ways — let me just start with the one that you already know. The first way is Vera Rubin. And we'll sell millions of Rubins, and every 2 of them is connected to a Vera. And of course, we price those 2 and they're properly priced. And so that's #1 use case.  

The second use case is Vera stand-alone CPU. The third is Vera with CX-9 and the software stack for storage. And then Vera in a — with CX-9 with a software stack for security and compute isolation and confidential computing. Okay, so each one of those use cases is built on Vera. And my sense is that we'll be supply constrained throughout the entire life of Vera Rubin. There are 4 different use cases of it. And — but anyhow, the answer to your question is — of the $20 billion is a stand-alone [,,,] And so — but the large length, every one of those agents are going to spin off subagents. And every time they spin these off, you're going to need to do inference. That's where the thinking happens. All of the thinking happens on GPUs, all of the orchestration essentially runs on CPUs. And the subagents when they're spun off, they — when they're thinking they use GPUs.  

[…] So we're going to need a lot more CPUs, and Vera was designed to be an agentic CPU. The CPUs of the past were designed to have many cores so that it could be easily rentable. People rented cores. Well, agents don't rent cores. They just want the work to be done fast. The economics of the past was dollars per core. That's the economics of cloud computing of the past. The economics of the AI of the future is tokens per dollar or dollars per token. And so what we need to do in the future is to generate tokens, process tokens as fast as possible, and that's what Vera does incredibly well […] 

Supply-Related Commitments Surge to $119B; Good or Bad? 

Nvidia’s total supply-related commitments surged once again in Q1, as Nvidia continues to secure supply and capacity to meet demand, yet there may also be a hidden signal that this is driven by materially higher memory component costs that could weigh on margins. 

Total supply commitments reached $119 billion, up nearly $90 billion YoY and $24 billion QoQ. As stated last quarter, we believe this serves as a key sign that the current accelerated QoQ data center growth will persist as Blackwell and Rubin ramp, as Nvidia is putting the pieces together across the supply chain to meet its $1 trillion in forecasted cumulative revenue through 2027.  

As seen above, this is the largest two-quarter step-up in supply commitments Nvidia has seen at nearly $70 billion, and as it stands, this also is more than 2X its reported cash and equivalents, the first time exceeding this level since Hopper’s breakout quarter. Supply commitments are also substantially higher heading into Rubin’s ramp than prior generations – early FY24 ramped into the teens, before stepping up to the ~$30 billion level for Blackwell.

Nvidia expects $95 billion of these commitments to be paid in the remainder of FY27, and the sheer increase over the past two quarters could imply that there may be some margin headwinds with the Rubin ramp if the bulk of these commitments stems from memory costs.  

Considering that Blackwell Ultra and Rubin contain 60% more HBM content versus Blackwell and with memory prices up ~6X since September, it’s entirely possible that securing HBM and auxiliary memory account for the bulk of this increase. For example, Morgan Stanley estimates that Nvidia’s bill of materials on memory for Rubin has reached $2 million per rack, up 435% from the GB300’s $374,000. Putting this a different way, memory could account for 25% of the total BOM for Rubin, versus <10% for the GB300; when translating this to a $500 billion SKU, this is quite a substantial uplift in memory costs that Nvidia must offset via higher prices to avoid operating margin contraction. 

It’s clear that supply-related commitments are surging above and beyond what is normal for previous GPU generations – which could indicate either a very strong pipeline or incoming margin pressure from higher memory costs/commitments. 

Rubin Remains the Next Major Catalyst, But Timing Risk Remains

There were mixed signals provided on Rubin’s timing. The headline statements seemed to confirm shipments would begin in Q3 (if so … no biggie), but then statements during the Q&A section seemed to point toward the stronger ramp not occurring until Q4-Q1. 

Overall, the commentary left it open on when Rubin will make an impact, with my takeaway being somewhere between Q4 and Q1. Keep in mind that Q4 is end of January for Nvidia, so it could be about 8 months out before there is any material Rubin revenue and about 11 months before a bigger impact. 

“Joshua Buchalter 
TD Cowen, Research Division 

And congrats on the great results. Colette, I believe, in your prepared remarks, you mentioned GB300 is sort of the fastest ramp in the company's history. How should we think about Vera Rubin against this benchmark? It's obviously a new architecture at the silicon level, but in similar rack. Does that mean we should expect a similar slope to the Vera Rubin ramp as the GB300? Or should it be a bit more gradual given the new silicon? 

Colette Kress 
Executive VP & CFO 

Yes. Well, we've indicated for a while that we will be launching Vera Rubin in the second half. We will start in Q3. That will be our initial pieces together. And then once we get to Q4, we're probably going to start to see our ramping continue. It's hard to say at this point what will be a faster ramp. But again, we have demand already planned, we've got POs. We've got almost all of our major customers ready to go, and these are very complex systems that we need to put together. So I think it's just about the timing that it's going to take for us to get that into market. Nothing else other than getting from production of all of the different systems that we have ready for order.  

So a little early to say. But yes, we're going to start in Q3 and continue to ramp into Q4. And Q1 of next year certainly is going to be very big as well.” 

Financials 

Revenue Accelerates 12 Points in Q1, Guided to Persist in Q2 

Nvidia reported $81.62 billion in revenue in Q1, beating its own guidance for $78 billion and marking a fresh record for sequential dollar growth at nearly $13.5 billion (versus $11.1 billion last quarter).  

Revenue growth accelerated 12 points from 73.2% YoY in Q4 to 85.2% YoY in Q1, while QoQ growth was steady at 19.8% QoQ, an impressive growth rate considering the sheer scale of Nvidia’s revenue.

For Q2, Nvidia guided for revenue to be $91 billion, +/- 2%, implying YoY growth accelerating further to 94.7% while QoQ growth would moderate to 11.9%. However, dollar growth would remain rather strong sequentially at $9.4 billion guided. This was notably $4 billion ahead of consensus for $86.95 billion.  

For FY27, current consensus estimates sat at $373 billion (up 72.7% YoY) heading into earnings, $43 billion higher than the $330 billion estimate from late February due to Nvidia’s comments about $1 trillion in cumulative revenue for Blackwell and Rubin through 2027. However, considering Q1’s beat and Q2’s raise over estimates, it’s likely that FY27 revenue estimates will have to move a minimum of $10 billion higher.  

Networking Remains Robust at 35% QoQ to Nearly $60B Annualized 

As expected, Data Center momentum remained robust, with revenue up 92% YoY and 21% QoQ to $75.25 billion. This marked a 17 point acceleration from 75% YoY growth in Q4 while QoQ again remained steady with Q4’s 22% growth off a larger base. Nvidia said that growth was driven by the GB300 ramp as well as demand across its Networking portfolio, including InfiniBand, Spectrum-X Ethernet and NVLink. 

Compute revenue was $60.4 billion, accelerating 19 point to 77% YoY with QoQ growth of 18%, roughly maintaining the 19% QoQ growth from Q4. On a dollar basis, growth was $9.1 billion, increasing from Q4’s ~$8.3 billion. Nvidia added that it recorded no China-based Hopper revenue in the quarter. 

Networking growth remained robust, up 199% YoY and 35% QoQ to a record $14.8 billion, or nearly $60 billion annualized, compared to $20 billion annualized last Q1. While YoY growth did technically decelerate 36 points from 235% YoY in Q4, the more impressive feat was the slight QoQ acceleration from 34% in Q4 to 35% QoQ this quarter.  

New Reporting Structure for Key Segments 

It should be noted that Nvidia shook up its segment reporting this quarter, re-categorizing Data Center to two sub-markets: Hyperscale and AI Cloud, Industrial and Enterprise (ACIE), to emphasize what customer cohorts are driving growth. While Nvidia did provide Compute and Networking revenue this quarter, it’s unlikely that we will get another breakdown here moving forward.  

Nvidia’s other segments – Gaming, Automotive, Pro Viz, and OEM and Other – were reclassified into Edge Computing.  

For a quick snapshot of the new segment structure: 

Hyperscale revenue accounted for roughly 50% of Data Center at $37.87 billion, up 115% YoY and 12% QoQ. Revenue from Hyperscale was $17.6 billion a year ago (45% of DC) and $33.8 billion in Q4 (54% of DC). 

AI Cloud, Industrial and Enterprise (ACIE) revenue was the remaining half of Data Center at $37.38 billion, up 74% YoY and 31% QoQ. ACIE revenue was $21.5 billion a year ago and $28.5 billion in Q4. 

Edge Computing revenue was $6.37 billion, up 29% YoY and 10% QoQ, driven by strong demand for Blackwell workstations, offset by slower consumer PC demand.  

Margins Remaining Steady 

While Nvidia continues to grow its topline at increasingly large rates on a dollar basis, margins are remaining steady. There were also tiny signs of operating leverage at this scale, with gross margins in line with guidance and slight outperformance on operating margins. 

GAAP gross margin was 74.9% and adjusted gross margin was 75%, both in line with guidance. Both were up >14 points YoY due to the H20 impacts last Q1, and marginally lower QoQ. For Q2, Nvidia guided for both to be flat QoQ at 74.9% and 75% respectively, representing roughly 2.5 and 2.3 points of expansion YoY.  

GAAP operating margin was 65.6%, coming in above guidance for 65%; this marked a >16 point YoY expansion again from the H20-related impacts, and a slight increase from 65% in Q4. Adjusted operating margin was 65.9% and saw a similar dynamic, up >13 points YoY and expanding from 65.3% in Q4.  

Looking ahead to Q2, guidance implies operating margins to remain flat QoQ at 65.6% and 65.9% respectively. On a YoY basis, this would represent a 4.8 point expansion for GAAP operating margin and a smaller 1.4 point expansion for adjusted operating margin.  

GAAP net margin was 71.5%, as Nvidia benefitted from nearly $16 billion in gains related to its equity investments, more than offsetting its $11.6 billion in income tax payments this quarter. Adjusted net margin was 55.8%, up more than 10 points YoY but down 1.4 points QoQ. 

EPS  

Nvidia’s GAAP EPS benefitted from the equity investment gains, though growth for adjusted EPS was also robust at 140% YoY.  

GAAP EPS was $2.39, up 214% YoY due to the equity gains, which contributed roughly $0.64 to the bottom line. Adjusted EPS was $1.87, up 140% YoY (versus Q1’s new adjusted figure of $0.78, per Q4’s change in reporting to include SBC).  

For Q2, GAAP EPS is projected to be $1.91, up 76.9% YoY, while adjusted EPS is projected to be $1.96, up 86.6% YoY. 

Cash Flows and Balance Sheet 

Cash flows were another strong point in Q1 as operating cash flow margin returned to above 60%.  

Q1 operating cash flow margin was $50.3 billion for a 61.7% margin, down from a 62.2% margin a year ago but a rebound from 53.1% in Q4. Nvidia says OCF was driven by higher revenue and lower cash taxes, projecting higher taxes in Q2 which is likely to weigh on OCF.  

Q1 free cash flow was $48.6 billion for a 59.5% margin, up slightly from 59.3% a year ago and 51.2% in Q4. 

Cash, equivalents and marketable debt securities were $50.3 billion (excluding marketable equity securities which were previously included in Q4). Debt remained steady at $8.47 billion.  

Inventories were $25.8 billion, up $4.4 billion or 20.6% QoQ, while accounts receivable increased more than $2 billion QoQ to $40.7 billion.  

Conclusion: 

Nvidia delivered a near perfect quarter, as revenue accelerated, networking grew 35% QoQ, with elite-level margins and cash flow that are significantly better than even the trademark value-stock Apple.  

With that said, the catalysts are not as clean as prior years during Hopper and Blackwell. The inference market is becoming more competitive, CPU-to-GPU attach rates could divert compute spend, and Nvidia’s supply-related commitments are surging – which could indicate either a very strong pipeline or incoming margin pressure from higher memory costs/commitments. Lastly, the segment change is likely a defensive move ahead of hyperscaler allocating more AI budget to custom silicon.  

Although I am far from bearish on Nvidia, the I/O Fund is a top tier team in AI research. We can do better than hold the most well-known name in the AI trade. As we close up our earnings season soon following Broadcom, we turn our attention to new ideas for a dedicated seven weeks. Keep an eye on your inbox as we revisit the biggest winners from this quarter and surface new stocks you likely haven’t heard of.

Damien Robbins, Equity Analyst at I/O Fund 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.

Recommended Reading:

• Applied Optoelectronics Q1: Management Guides to 141% YoY Growth; Execution Comes Next
• Arm FQ4: AGI CPU Demand Hits $2B, Revenue Outlook Stays at $1B
• Lumentum FQ3: Firing on All Cylinders Despite Stiff Supply Constraints Across EMLs, Pump Lasers
• Astera Labs: Important QoQ Acceleration, Product Road Map is Loaded

AMD's offered a clear inflection this evening with $10.3B revenue (+38% Y/Y), EPS of $1.37 (+43%), and free cash flow tripling to $2.6B. Data Center saw a resurgence following the CPU boom, with $5.8B in revenue (+57%) and operating margin in the segment expanding to 28%. 

The most important update was the server CPU TAM revision: from about 18% CAGR to more than a 35% CAGR. Management doubled their forecast from $60 billion on the November analyst day to $120 billion by 2030. Management framed this as Agentic AI driving incremental CPU demand rather than GPU substitution. Q2 server CPU revenue is guided to grow over 70% Y/Y. 

Management guided to second quarter revenue of approximately $11.2 billion (±$300 million), implying year-over-year growth of approximately 46% at the midpoint and sequential growth of approximately 9%.  

Sequential growth is expected to be driven by double-digit growth in both the Data Center and Embedded segments, with modest growth in Client and Gaming. As mentioned, Server CPU revenue specifically is guided to grow more than 70% year-over-year in Q2. 

Expanded Server CPU TAM; Venice EPYCs Ship 2027  

The showstopper was that management raised their long-term server CPU TAM outlook materially. The November 2024 Financial Analyst Day target of 18% CAGR for a $60B TAM is now CAGR of 35% for $120B TAM by 2030. 

We’ve covered the CPU boom in an analysis on Arm here stating: “Multi-agent systems are also expected to drive an exponential increase in token generation, which Arm estimated at up to a 15X increase in tokens per user, due to the increase in tool calls and API requests associated with each agent. This is expected to drive CPU core demand much higher, at a time where key x86 suppliers AMD and Intel battle growing supply constraints.” 

Something similar was echoed on the call this evening with management stating: “Inferencing and Agentic AI are increasing the need for server CPU compute as these workloads require additional CPU processing for orchestration, data movement and parallel execution in addition to serving as the head nodes for GPUs and accelerators. As a result, we are seeing both stronger near-term demand and deeper engagement with customers on long-term capacity planning.” 

The 6th Gen EPYC Venice processor built on 2nm technology is expected to ship next year, and is optimized for throughput, performance per watt and performance per dollar. AMD is out to maintain its CPU lead with strong, competitive statements in the opening remarks, such as: “Across the portfolio, Venice widens our competitive advantage, delivering substantially higher performance per socket and per watt versus competitive x86 offerings and more than 2x throughput per socket versus leading ARM-based AI solutions.”  

Perhaps most notable was when the management team reiterated their plan to become “greater than 50% share" of the CPU server market.  

Helios Expected in 2H 2026 

AMD’s Data Center AI revenue was modestly lower sequentially in Q1 due to reduced China revenue, yet management expects the business to return to double-digit sequential growth in Q2.  

The more important inflection for AMD’s Instinct GPUs is the upcoming ramp of MI450 and the Helios rack-scale platform. AMD expects initial MI450/Helios volume in Q3, followed by a more significant ramp in Q4 and continued growth into 2027. Here was the update from the earnings call: 

“A key example is our expanded strategic partnership with Meta to deploy up to 6 gigawatts of AMD Instinct GPUs spanning several product generations. Our agreement includes a custom GPU accelerator based on our MI450 architecture, co-designed to support Meta's next-generation AI workloads. Shipments are on track to begin in the second half of the year, leveraging our Helios rack-scale architecture, which integrates Instinct GPUs with EPYC Venice CPUs to deliver fully optimized high-performance AI infrastructure.” 

Together with the previously announced OpenAI partnership, AMD is gaining visibility into multi-year, multi-gigawatt deployments totaling 12 GWs that move the company into production-scale infrastructure. 

Management also indicated that MI450 customer forecasts are now exceeding initial plans, with additional multi-gigawatt opportunities emerging. According to statements on the call, this gives AMD increasing confidence in its ability to deliver tens of billions of dollars in annual Data Center AI revenue in 2027 and exceed its long-term 80%+ AI revenue CAGR target.  

“As we approach production, demand for MI450 series GPUs continues to strengthen, with lead customer forecasts now exceeding our initial plans and a growing number of new customers engaging on large-scale deployments, including additional multi-gigawatt opportunities. With this expanded visibility, we have strong and increasing confidence in our ability to deliver tens of billions of dollars in annual Data Center AI revenue in 2027 and to exceed our long-term growth target of greater than 80% in the coming years.”

Financials: 

AMD reported an inflection in the company's growth trajectory and a structural shift in the business mix. Revenue of $10.3 billion exceeded the high end of guidance, growing 38% year-over-year, while diluted non-GAAP EPS of $1.37 increased 43%. Free cash flow more than tripled year-over-year to a record $2.6 billion, representing 25% of revenue. The Data Center segment was the primary driver of revenue and earnings, posting 57% year-over-year growth driven by accelerating demand from EPYC server CPUs primarily. 

Management guided to second quarter revenue of approximately $11.2 billion (±$300 million), implying year-over-year growth of approximately 46% at the midpoint and sequential growth of approximately 9%.  

Sequential growth is expected to be driven by double-digit growth in both the Data Center and Embedded segments, with modest growth in Client and Gaming. Server CPU revenue specifically is guided to grow more than 70% year-over-year in Q2. 

Segment Performance 

Data Center: 

The Data Center segment delivered record revenue of $5.8 billion, up 57% year-over-year and 7% sequentially, with operating income of $1.6 billion and operating margin expanding to 28% from 25% a year ago.  

Server CPU revenue grew more than 50% year-over-year, marking the fourth consecutive quarter of record server CPU revenue, with both Cloud and Enterprise customers each contributing more than 50% growth. Turin (5th-gen EPYC) crossed 50% of server revenue mix during the quarter. 

Data Center AI revenue grew by a significant double-digit percentage year-over-year but declined modestly sequentially due to lower China revenue versus Q4.  

Client and Gaming: 

Segment revenue of $3.6 billion was up 23% year-over-year, with operating income of $575 million representing a 16% operating margin, slightly below the 17% margin a year ago.  

The Client business generated $2.9 billion in revenue, up 26% year-over-year on strength in Ryzen processors and continued share gains in consumer and commercial markets, with commercial sell-through of Ryzen Pro PCs increasing more than 50% year-over-year.  

Gaming revenue was $720 million, up 11% year-over-year, with growth in Radeon GPUs partially offset by lower semi-custom revenue at this stage of the console cycle. Sequentially, Client was down 7% and Gaming down 15%, both consistent with normal seasonality. 

Embedded: 

Embedded segment revenue returned to growth at $873 million, up 6% year-over-year, with operating income of $338 million and operating margin of 39% (versus 40% a year ago).  

Margins and EPS: 

Non-GAAP gross margin of 55.0% expanded 170 basis points year-over-year, driven by higher product mix of EPYC 5th gen CPUs. Q2 gross margin is guided to approximately 56%, a further 100 basis-point sequential expansion. 

Non-GAAP operating margin reached 25% in Q1, with operating income of $2.5 billion growing faster than revenue and demonstrating meaningful operating leverage in the model. This came despite a 42% year-over-year increase in operating expenses to $3.1 billion, reflecting aggressive investment in AI roadmap R&D and go-to-market expansion.  

CFO Jean Hu outlined multiple structural tailwinds supporting gross margin into the second half and beyond. 

The principal headwind is the MI450 ramp beginning in Q3 and ramping significantly in Q4, which will run below the corporate gross margin average in its early phases. The long-term target range remains 55%–58% non-GAAP gross margin, as set at the November Financial Analyst Day. 

Record Q1 Free Cash Flow 

AMD generated $3.0 billion in cash from continuing operations in Q1 and a record $2.6 billion in free cash flow, representing roughly 25% of revenue. Free cash flow more than tripled year-over-year, materially outpacing the 38% revenue growth.  

Working Capital and Balance Sheet 

Inventory was roughly flat sequentially at approximately $8.0 billion.  

The company had cash & short-term investments of $12.3 billion, while the debt was $3.2 billion at the end of Q1.

Conclusion: 

The message from the call was clear, which is that AMD believes the market opportunity ahead is materially larger than previously anticipated. Combined with an expanding server CPU TAM tied to agentic AI workloads, AMD is broadening its GPU-challenger story. The dynamic around inference and agentic AI increasing demand for CPUs expands AMD’s opportunity while we await Helios arrival in Q4 and beyond.

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 AMD at the time of writing and may own stocks pictured in the charts.

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

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

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

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

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

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

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

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

Supply Constraints and Product Road Map Combo Can Create Defensibility 

Although the market may be fatigued at hearing there are supply constraints, that dynamic is often what offers the highest level of defensibility for a supplier like Micron.  

Regarding AI memory, Micron stated they began volume shipments of HBM4 36GB (12-high) in 1H26 designed for Vera Rubin and they expect this to reach mature yields faster than HBM3e. Higher yields typically mean more sellable HBM per production run and typically support stronger margins. Additionally, Micron has sampled 48GB (16-high) HBM4 stack with HBM4e in development with a planned 2027 volume ramp, leveraging the 1y DRAM node in the product road map for sustained data center growth.  

On the earnings call, management emphasized that AI is trending toward more reasoning, longer context windows and agentic workflows – all of which require more DRAM capacity and bandwidth. As a result, GPUs and ASICs are expected to need increasing amounts of HBM plus DDR5/LPDDR to support training and inference.  

When it comes to HBM, management stated they expect to see robust growth at least through 2027: “And we continue to feel like we are in an extended space of robust industry demand that obviously, due to HBM being part of these numbers with its trade ratio is just stressing the entire industries and certainly our capabilities to be able to meet those demand numbers. So you're right. I mean, these numbers, at least in the foreseeable future are all supply limited numbers rather than the actual level — true level of demand. So yes, I mean, that's sort of the environment we are in. We do expect that next year, again, we will have a fairly robust level of growth in calendar '27. But yes, we are not providing a long-term number beyond that commentary.” 

On storage, Micron will benefit from rising SSD share from vector databases and KV-cache offload (we’ve covered this in the past here). It’s clear from management commentary that they see no end in sight to the supply shortages on SSD: 

“And we continue to see those shortages for the foreseeable future. That has been another driver. So when we put all of these together, the NAND market is significantly undersupplied to the demand in the data center, and that demand continues to escalate in part driven by KV cache, but also driven by just the insatiable appetite that these AI servers have to have fast storage capability available as these systems get deployed more and more. And so the outlook is really strong. And as we have mentioned earlier, our portfolio is incredibly well positioned to continue to gain share in that space, including our KV cache applications, by the way, yes.” 

The company is in high-volume production of G9 NAND PCIe Gen6 data center SSDs and cited strong adoption of its 122TB SSD that “delivers 16 times the sequential read throughput per watt of a capacity-matched HDD configuration.” 

In the most recent earnings report, Micron saw share gains in SSD for its fourth consecutive year in 2025 with management stating that NAND revenue more than doubled sequentially in fiscal Q2 to a record. 

It was also confirmed that NAND demand significantly exceeds supply, which is fairly evident in the following pricing strength: “Fiscal Q2 NAND revenue was a record $5.0 billion, up 169% year-over-year, and represented 21% of Micron’s total revenue. Sequentially, NAND revenue increased 82%. NAND bit shipments increased in the low-single-digit percentage range. Prices increased in the high-70s percentage range driven by tight NAND industry conditions and included favorable mix.” 

Counterpoints 

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

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

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

Micron Capex Increases 

The CFO stated FY26 capex is raised to over $25B from previous estimates for $20B with some of the new fabs being greenfield sites. Although a glut of inventory is always on top-of-mind for a memory player that aggressively adds more capacity, there is likely more risk to Micron not seizing the opportunity to remain #2 with South Korea being particularly strong competitors. There are some facilities that are expansions yet many of these projects will not translate into meaningful revenue shipments until FY2028. 

In terms of if Micron could be adding more capacity at a peak, management felt confident this is not the case: “So we are very excited about that, and our supply is nowhere close to being able to meet the demand that we see for the foreseeable future.” 

The Shift to Strategic Customer Agreements (SCAs) 

Micron discussed shifting from long-term agreements to strategic customer agreements (SCAs): “We continue to work with customers on strategic customer agreements — or SCAs — that are different from prior LTAs (long-term agreements) and have specific commitments over a multi-year time horizon for improved visibility and stability in our business model. These SCAs also provide customers greater certainty to plan their businesses while reinforcing long‑term engagement across our broad product portfolio. We are excited to have signed our first five-year SCA.” 

If I had to point to one thing that could be causing the softer price action, it would be the read-through that SCAs could lead to a cap in pricing during a surge (like what we are seeing now in surging DRAM and NAND pricing).  

The upside to SCAs is they lock in supply and volume to smooth-out lumpiness in a cyclical industry yet could limit upside in exchange for that visibility. 

There were many questions on SCAs in the call – in fact, this topic dominated the Q&A session, here is one that encapsulates the concern around SCAs limiting upside in pricing yet also helping to remove the effects of a cyclical low, as well: 

“Sreekrishnan Sankarnarayanan 
TD Cowen 

Got it. Thanks for that, Mark. And then a quick question for Sanjay on the SCA. Congrats on your first 5-year SCA. How different is it from an LTA? Is this a multi-year volume and price commitment, or does the price get negotiated every year? And also, how to think about cancellation terms on the SCA in case the cycle slows down during the timeframe? 

Sanjay Mehrotra 
CEO, President & Chairman 

Thank you for recognizing us for the first SCA that we have completed here. And as you noted, SCA is multi-year agreement, and we noted that in our remarks as well. LTAs have tended to be typically 1-year agreement. And of course, in this environment of extremely tight supply outlook in the foreseeable timeframe as well, of course, our customers are very motivated in order for their own planning purposes and for their better predictability to have these structural strategic agreements with us. And of course, these agreements are really meant to bring stability and greater visibility into our business model as well. We have completed 1 SCA, so we are not going to be getting into the specifics here or these agreements. I'm sure you can appreciate that these SCAs are confidential in nature. But of course, these SCAs are meant to achieve the objectives for the customers in terms of their ability to plan and be able to count on supply commitments that are in the agreements, but also for us to be able to count on specific commitments that are there from the customers. And these are meant to go across the periods when the industry is very tight versus other parts of the industry environment as well. So that's why they're long-term agreements, and they have robust terms in them for us as well as for our customers.” 

The correct readthrough, if I had to guess, is that Micron is in the driver’s seat and is able to lengthen the LTA commitments to now 5-year terms for the company’s benefit.  

Financials 

By Royston Roche 

Revenue Growth of 196% 

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

Management also provided a strong FQ3 revenue guidance of $33.5 billion, implying a YoY growth of 260.2% and 40.4% QoQ. The revenue guidance beat consensus estimates by a stellar 44%. Analysts expect strong revenue growth to continue and expect FQ4 revenue to grow by 233.8% YoY to $37.77 billion. 

DRAM Revenue Grew by 207% 

Micron’s FQ2 DRAM revenue grew by 207% YoY and 74% QoQ to a record $18.8 billion. Revenue growth accelerated by 138 percentage points from 69% YoY and 20% QoQ growth in the previous quarter. Bit shipments were up mid-single digits sequentially. Average selling prices increased in the mid-60s percentage range sequentially, driven by tight market conditions and also due to favorable mix.

NAND Revenue Grew by 169% 

FQ2 NAND revenue grew by 169% YoY and 82% QoQ to a record $5.0 billion. Revenue growth accelerated by 147 percentage points from 22% YoY growth in the previous quarter. NAND bit shipments increased in the low-single-digit percentage range sequentially. Average selling prices increased in the high-70s percentage range sequentially, driven by tight NAND market conditions and favorable mix. 

Revenue by Business Units 

CMBU Revenue Grew by 163% 

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

CDBU Revenue Grew by 211% 

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

MCBU Revenue Grew by 245% 

Mobile and Client Business Unit (MCBU) FQ2 revenue grew by 245% YoY and 81% QoQ to a record of $7.71 billion. Revenue growth accelerated sharply from 63% YoY and 13% QoQ growth in the previous quarter. The strong sequential growth was driven by higher pricing, partially offset by lower bit shipments. 

AEBU Revenue Grew by 162% 

Automotive and Embedded Business Unit (AEBU) FQ2 revenue grew by 162% YoY and 57% QoQ to a record $2.71 billion. Revenue growth accelerated sharply from 49% YoY and 20% QoQ growth in the previous quarter. The strong sequential growth was driven by higher pricing, partially offset by lower bit shipments. 

Gravity-Defying Margins

Micron guided for a gross margin of 81% for FQ3. The record gross margin was primarily driven by higher memory prices, cost controls, and favorable revenue mix. The margins are so high that an analyst expressed concerns that perhaps Micron’s customers would be upset by it. Management replied that the demand supply imbalance is leading to higher memory prices. Also, customers are recognizing the higher value as high performance memory helps in driving down costs and improves the overall AI performance.  

Q: Vivek Arya (Analyst) 

“And for my follow-up, Mark, I wanted to revisit this 81% gross margin guidance. I appreciate you're not giving a specific forward view. But what do you — what has happened in kind of prior historical peaks where Micron's margins, I think, peaked in the low 60s, I believe, so what is the difference between the prior situations versus now?  

What have those kind of historical precedents indicated to you about how the trajectory of gross margins can be over the next several quarters? How do customers — do customers start to react differently when they see these level of gross margins and what is a very, very important input into their AI silicon?”  

A: Mark Murphy (CFO) 

“Vivek, I would say that keep in mind that the industry is supply constrained. So — and conditions will remain very tight, and that's beyond '26. So that certainly supports the near-term, medium-term pricing… We're investing in capacity, and we're also increasing R&D to continue to advance the technology and improve the value of memory. And we believe these will help with margins over time, and I think customers are recognizing that and entering into these agreements.” 

• FQ2 gross profits grew by 499.2% YoY to $17.76 billion. Gross profit margin was 74.4%, an improvement of 37.6 percentage points YoY and up 18.4 percentage points sequentially. It beat the management guidance of 67%. The adjusted gross margin improved by 37 percentage points YoY and 18.1 percentage points sequentially to 74.9%. The strong gross margin was driven primarily by higher pricing, favorable mix, and cost controls. Management has guided further improvement of gross margin to 81% in the next quarter. 
• FQ2 operating profits grew by 810% YoY to $16.14 billion. Operating margin came at 67.6%, an improvement of 45.6 percentage points YoY and 22.6 percentage points sequentially. It beat the management guidance of 58.7%. The adjusted operating margin improved by 44.1 percentage points YoY and 22 percentage points sequentially to 69% driven by operating leverage. Management has guided further improvement of operating margin to 76.2% and adjusted operating margin to 76.8% in the next quarter. 
• FQ2 net income was $13.79 billion or 57.8% of revenue compared to $1.58 billion or 19.7% of revenue in the same period last year. Adjusted net income was $14.02 billion or 58.8% of revenue compared to $1.78 billion or 22.1% of revenue in the same period last year. 

Adjusted EPS Grew by 682% 

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

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

Cash Flow and Balance Sheet 

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

• FQ2 operating cash flows grew by 202% YoY to $11.9 billion with an operating cash flow margin of 49.9% compared to 49% in the same period last year. 
• FQ2 adjusted free cash flows grew by 705% YoY to $6.9 billion with an adjusted free cash flow margin of 28.9% compared to 10.6% in the same period last year. Capex grew by 61.3% YoY to $5.0 billion. For FQ3, management has guided a capex of $7.0 billion and expects adjusted free cash flows to roughly double sequentially.  
• Cash and investments were $16.6 billion and debt of $10.14 billion compared to $12.02 billion and $11.76 billion in the previous quarter. Micron repurchased shares worth $350 million and also reduced debt by $1.6 billion in the recent quarter. 
• Inventory increased marginally by 0.6% sequentially to $8.27 billion. 

Conclusion: 

Micron’s record-breaking fundamentals are going far beyond what this company has reported before during previous peaks as the “normal” memory swings are being eclipsed by AI-era capacity scarcity.  

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

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

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

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 MU at the time of writing and may own stocks pictured in the charts.

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• 2025 Full Year Audited Returns

Nvidia put up a stellar report, yet the market seems to be numb to the strong fundamentals coming out of the company. Not only did Nvidia report record QoQ data center growth at $11.1 billion, but the CFO also stated they expect to see QoQ growth every quarter this year with visibility into CY2027. Management also confidently stated they will exceed the $500 billion estimate they had provided for Blackwell and Rubin combined. 

Management also stated that Nvidia is now the world’s largest Ethernet networking company, accomplishing this in just a few short years of Spectrum-X deployments. Networking growth was 263% this quarter, up 100 points from last quarter’s growth rate of 162% YoY growth. 

The Q&A session centered around whether capex can continue to grow, if the CUDA moat is still intact, and the company’s strategy for keeping margins elevated. The analysts poked yet there was no chink to be found in the armor. 

Nearing $700 Billion – can Capex Continue to Grow? 

About four months ago, our firm published on the AI Monetization Supercycle here and here. The point of those articles was to say that debates around an AI bubble are loud at this exact point in time because of Big Tech has spent an exorbitant amount of money for the training phase, which is a foundational stage rather than a revenue-generating stage. As a result, investors see soaring capex, and meanwhile, the revenue streams are still in their infancy, which fuels the bubble debates. 

My contention has been that we are too early in the cycle for these concerns to carry weight. Inference is synonymous with monetization, and we know the inference stage is incoming with architectures like Rubin and Helios (AMD) optimized for high-throughput and low latency at scale. This means they are not only designed to train models, but rather to deploy them into applications where revenue is generated, which is supported by the sheer amount of memory these incoming generations of GPUs offer.  

To add to this, Nvidia recently acquired Groq, a startup with specialized inference hardware called LPUs or language processing units. LPUs allow trained models to generate answers very quickly at several hundreds of tokens per second. Groq offers a cloud platform for Ai inference-on-demand to access language models and AI capabilities in the cloud, and also a rack cluster for on-premises AI inference for data centers that want LPUs. Jensen Huang stated to expect announcements regarding how Nvidia plans to strategically integrate Groq : “What we’ll do with Groq is you’ll come to see GTC, but what we’ll do is we’ll extend our architecture with Groq as an accelerator, in very much the way that we extended NVIDIA’s architecture with Mellanox.” 

Back to whether capex can increase, there was a question on this in the Q&A session, to which Huang’s answer lines up with my understanding of how the return on capital for infrastructure is set to improve: 

Here was the question from Antoine Chkaiban from New Street Research: 

“[…] Jensen, I’m curious, you know, when you look at your top cloud customers, cloud CapEx close to $700 billion this year, many investors are concerned that it would be harder for this level to grow into next year, and for several of them, their cash flow generation capability is also getting compressed. I know you’re very confident about your roadmap, right? And your purchase commitments and whatnot, but how confident are you about your customers’ ability to continue to grow their CapEx?  

Jensen Huang: 

“I am confident in their cash flow growing. The reason for that is very simple. We have now seen the inflection of agentic AI and the usefulness of agents across the world in enterprises everywhere. You’re seeing incredible compute demand because of it. In this new world of AI, compute is revenues. Without compute, there’s no way to generate tokens. Without tokens, there’s no way to grow revenues. In this new world of AI, compute equals revenues. […]  

Now, I am certain at this point that we are at the inflection point. We’ve reached the inflection point, and we’re generating profitable tokens that are productive for customers and profitable for the cloud service providers. The simple logic of it, the simple way to think about it, is computing has changed. What used to be software running on computers, modest amount of computers, you know, call it $300 billion-$400 billion worth of CapEx each year, has now gone into AI. AI, in order to generate tokens, you need compute capacity, and that translates directly to growth, and that translates directly to revenues.” 

The Defensibility of CUDA during the Inference Phase 

One of the more intriguing questions on the call was whether CUDA matters as much as dollars shift from training to inference. Jensen Huang’s answer was essentially that CUDA turns inference from raw compute into a monetizable stack as CUDA offers TensorRT-LLM tools and NVLinkn optimizations, which in turn, lead to a higher performance-per-watt. This also ties back to the notion that inference equals revenue as Huang is stating agentic AI can push tokens into the thousands to hundreds of thousands per session.  

Here was the exchange: 

Atif Malik, Analyst, Citi:  

Thank you for taking my question. Jensen, I’m curious if you can touch on the importance of CUDA, as now more of the investment dollars in AI are coming from inference workloads. 

Jensen Huang:  

Without CUDA, we wouldn’t know what to do with inference. The entire stack from TensorRT-LLM that we introduced a few years ago, which is still the most performant inference stack in the world.  

Optimizing it for NVLink requires us to discover and invent new parallelization algorithms that sits on top of CUDA to distribute the workload and the inferencing to take advantage of the aggregate bandwidth across NVLink Switch. NVLink Switch has enabled us to deliver generationally 50 times more performance per watt. It’s just an incredible leap, and it’s sensible. NVLink Switch is a great invention. It was hard to do. 

The, the creation of the switching technology, disaggregating the switches, building the system racks, all of that, you know, we did it all in plain sight, and everybody knew how hard it was for us to do. The, the results are incredible. You know, performance per watt is 50 times. Performance per dollar, 35 times. The leap in inference is incredible. It’s very important to realize that inference equals revenues now for our customers. Because agents are generating so many tokens, and the results are so effective. When the agents are coding, it’s off generating thousands, tens of thousands, hundreds of thousands, because they’re running for, you know, minutes to hours. These systems, these agentic systems, are spawning off different agents working as a team. 

Durability of Gross Margins 

Nvidia has impressive gross margins that are high compared to previous eras where the gross margins were below 60% and sometimes as low as 40%. The gross margin reported tonight was 75%, thus analysts are wondering if this can be sustained, especially from the rising costs of memory. 

Huang provided his typical approach, which is to not directly answer the question if he doesn’t care for the angle. Instead of discussing what effects memory prices will have on the gross margin, he stated that gross margins are sustained when Nvidia delivers “generational leaps” that create a step-up in performance per watt and performance-per-dollar that outpace what Moore’s Law alone could deliver. 

“The single most important lever of our gross margins is actually delivering generational leaps to our customers. That is the single most important thing. If we could deliver generationally, performance per watt, that exceeds dramatically what Moore’s Law can do. If we can deliver performance per dollar dramatically more than the cost of our systems, than the price of our systems, then we can continue to sustain our gross margins. That’s the simple, most important concept.”

Data Center QoQ Revenue Sets a New Record 

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

One key takeaway is that the company delivered a higher QoQ growth on a dollar basis in Q4 on a larger revenue base, highlighting just how rapidly Blackwell and networking platforms are ramping. Data Center revenue increased $11.1 billion sequentially, surpassing Q3’s $10.1 billion growth. Assuming similar mix in Q1 on the $78 billion guide, Data Center revenue could come in around $71.4 billion at the midpoint, or up another $9.1 billion QoQ.  

Within Data Center, Compute revenue rose 58% YoY and 19% QoQ to $51.33 billion, slowing from 27% QoQ in Q3 though YoY growth accelerated 2 points. Networking revenue accelerated more than 100 points to 263% YoY to $10.98 billion, with QoQ growth accelerating 21 points to 34%.  

For the full year, Data Center revenue was $193.74 billion, up 68% YoY; this was driven by a 59% increase in Compute revenue to $162.36 billion, and a 142% increase in Networking revenue to $31.38 billion. 

Looking ahead through FY27, Blackwell Ultra and related networking will be the main driver of this near-term QoQ growth, but the bigger story will be Rubin and if the upcoming platform is fully priced in, considering it is expected to carry a significant price premium over the GB300s. For example, the Street is suggesting Rubin could carry up to a 40% to 50% premium versus the GB300’s estimated $3.5 million price tag.  

While the timing of the ramp remains a bit more fluid at the moment, Wolfe Research projects Rubin to ramp smoothly in 2H, and quickly meet a similar volume profile to Blackwell in the 1,000 rack/week range. Under a rough projection that Rubin ramps from ~8,000 racks/quarter to 13,000 in 2H, for total volume of ~21,000 racks in FY27, this estimated ASP uplift alone could drive incremental revenue of ~$12.6 billion and $20.5 billion. 

Financials 

Revenue Accelerates to 73% YoY 

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

For Q1, Nvidia guided for revenue growth to accelerate further to 77% YoY, forecasting revenue to be $78 billion, +/- 2%, coming in well ahead of consensus for $72.03 billion. Sequential growth would again moderate to 14.5% QoQ at the midpoint of guidance, though again this is simply due to the law of large numbers as dollar growth is projected to be nearly $10 billion QoQ, versus $11.1 billion in Q4.   

For FY26, Nvidia reported revenue of $215.94 billion, up 65.5% YoY, with this growth driven by Data Center revenue increasing 68.2% YoY to $193.74 billion. Nvidia is not providing full year guidance for FY27, but considering that FQ1 is already $6 billion ahead of estimates, the current estimate for $330.76 billion for 54.6% growth may quickly move tens of billions higher. 

Networking Steals the Spotlight with 263% Growth 

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

On the call, it was stated that Nvidia is likely the largest Ethernet company in the world: “The amount of switching that we do per rack is really quite incredible. We’re also now the largest networking company in the world. If you look at Ethernet, we came into the Ethernet market about a couple of years ago, into Ethernet switching, and I think that we’re probably the largest Ethernet networking company in the world today, and surely will be soon. Spectrum-X Ethernet has been a home run for us. You know, we’re open to however people want to do, networking.” 

This rapid acceleration in 2H drove networking revenue up 142% YoY to $31.38 billion, contributing more than 16% of Data Center revenue, up from more than 11% in FY25. To put in perspective the sheer size of Nvidia’s Networking segment, it alone was >1.5X of Broadcom’s entire AI revenue from FY25, and just $3 billion shy of AMD’s entire annual revenue last year. 

Turning to Nvidia’s other segments:  

Gaming revenue increased 47% YoY but declined (13%) QoQ to $3.73 billion, with YoY growth driven by strong Blackwell demand and the QoQ decline due to channel inventory moderating after the holiday season. However, Nvidia expects supply constraints to be a headwind on Gaming revenue in FQ1 and beyond. 

Pro Viz revenue showed an unusually strong 159% YoY and 74% QoQ increase to $1.32 billion in Q4, accelerating from 56% YoY and 26% QoQ in Q3. Nvidia said this was driven by ‘exceptional’ Blackwell demand, likely for its DGX Spark desktop supercomputer as was the case in Q3. 

Automotive revenue was soft in Q4, up just 6% YoY and 2% QoQ to $604 million, driven by adoption of Nvidia’s self-driving vehicle platforms. 

OEM and other revenue rose 28% YoY but declined (7%) QoQ to $161 million. 

For FY26:  

• Gaming revenue was $16.04 billion, up 41% YoY. 
• Pro Viz revenue rose 70% YoY to $3.19 billion. 
• Automotive revenue rose 39% to $2.35 billion. 
• OEM and other revenue rose 59% to $619 million. 

Margins Expanded in Q4 

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

Q4 GAAP gross margin was 75%, slightly ahead of management’s guidance for 74.8% and expanding by 2 points YoY and 1.6 points QoQ, with the sequential expansion driven by Blackwell and better product mix. Adjusted gross margin was 75.2%, expanding 1.7 points YoY and 1.6 points QoQ. Looking ahead to Q1, Nvidia guided for a minimal QoQ contraction to 74.9% for GAAP gross margin and 75% for adjusted gross margin.  

Q4 GAAP operating margin was 65%, also slightly ahead of guidance for 64.5%, and expanding 3.9 points YoY and 1.8 points QoQ, showing a hint of operating leverage. Adjusted operating margin was 67.7%, expanding 2.8 points YoY and 1.5 points QOQ, coming in slightly above the guidance for 67.3%. For Q1, Nvidia guided for operating margins to be flat at 65% and since the adjusted margin figures will include SBC, it will be lower sequentially at 65.4%. 

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

For FY26, as evidenced by the chart above, gross and operating margins contracted YoY as Nvidia faced inventory charge impacts related to the H20 China ban earlier last year. FY26 GAAP gross margin was 71.1%, down 3.9 points YoY, while adjusted gross margin was 71.2%, down 4.3 points. 

GAAP operating margin was 60.4%, down 2 points YoY, and adjusted operating margin was 63.6%, down 2.9 points. Despite this contraction, GAAP net margin as relatively unaffected at 55.6%, down 0.3 points, through adjusted net margin contracted 2.7 points to 54.2%.   

EPS 

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

Adjusted EPS was $1.62, up 82% YoY and beating estimates by just over 5%. Growth accelerated from 60.5% in Q3 and marked Nvidia’s fastest adjusted EPS growth in the last five quarters. Looking ahead to Q1, current consensus estimates point to this acceleration continuing to nearly 108% YoY, though this is likely to be revised higher considering the scale of the revenue beat.  

For FY26, GAAP EPS rose 67% YoY to $4.90, while adjusted EPS increased 60% YoY to $4.77; for FY27, initial estimates point to strong EPS growth continuing, with adjusted EPS forecast to rise 67.3% to $7.86. 

Cash Flows and Balance Sheet 

Cash flows were robust in Q4, with cash flow margins improving significantly on both a YoY and QoQ basis.  

Operating cash flow was $36.2 billion in Q4 for a 53.1% margin, up 10.9 points YoY and 11.4 points QoQ. For the full year, OCF was $102.7 billion for a 47.6% margin, down 1.5 points YoY due to the softer Q2 print.  

Free cash flow was $34.9 billion for a 51.2% margin, up 11.7 points YoY and 12.4 points QoQ. For FY26, free cash flow was $96.6 billion for a 44.7% margin, down 1.8 points YoY.  

Cash and equivalents totaled $62.6 billion, while debt was $8.47 billion. 

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

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

Conclusion: 

The financials were flawless while the Q&A during the call cleared the pressure points that the bears have leaned on for months, such as sustainability of AI capex, durability of the CUDA moat, and whether memory/input costs can compress margins.  

Management’s answers pointed to the same conclusion, which is that demand is broadening, utilization is tightening, and NVIDIA’s ability to deliver step-function gains in performance per watt and performance per dollar will preserve pricing power.  

The most important takeaway is that inference is no longer a future event; rather it is the revenue engine for customers today while agentic workloads are increasing token demand. The market will continue to play tug-o-war on whether the AI economy is an investable opportunity or a bubble, but the results this evening continue to make one thing clear: the fundamentals are driving forward record growth and profits with Nvidia remaining an obvious choice for participating in the AI monetization cycle.

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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