Advanced Micro Devices Inc ($AMD) Q1 2026 Earnings Call

Thank you, Matt, and good afternoon to all those listening in today. We delivered an outstanding start to the year, driven by accelerating demand for AI infrastructure across our portfolio. Growth was broad-based with every segment increasing year-over-year, led by 57% data center revenue growth. First quarter revenue increased 38% year-over-year to 10.3 billion. Earnings grew more than 40% and free cash flow more than tripled to a record 2.6 billion, driven by significantly higher sales of EPYC CPUs, Instinct GPUs, and Ryzen processors. These results mark a clear inflection in our growth trajectory and a structural shift in our business. Data center is now the primary driver of our revenue and earnings growth. And as AI adoption scales, demand is increasing not only for accelerators, but also for the high-performance CPUs that power and orchestrate those workloads.

Turning to our segments, data center revenue increased 57% year-over-year to a record 5.8 billion, led by strong demand for our EPYC CPUs and Instinct GPUs. In server, we delivered our fourth consecutive quarter of record server CPU revenue. Revenue increased more than 50% year-over-year with sales to both cloud and enterprise customers each growing more than 50%. Share gains accelerated year-over-year, reflecting the ramp of fifth gen EPYC Turin CPUs and continued strength of fourth gen EPYC processors across a wide range of workloads. In cloud, AI was the primary driver of growth in the quarter as every major cloud provider expanded their EPYC footprint to support a broad range of AI workloads, from general purpose compute and data processing to head nodes for accelerators and emerging adjacent applications. EPYC-powered cloud instances increased nearly 50% year-over-year to more than 1,600 with instances optimized for virtually every enterprise workload and expanded availability across the largest global cloud providers. In enterprise, demand accelerated with record revenue and record sell-through in the quarter. We expanded our customer base with new wins across financial services, healthcare, industrial, and digital infrastructure companies, while also building momentum with mid-market and SMB customers. We are well positioned to continue gaining share as more enterprises standardize on EPYC across on-prem and hybrid environments based on our leadership performance and TCO.

Looking ahead, our 6th gen EPYC Venice processor, built on our Zen 6 architecture and 2 nanometer process technology, is designed to extend our leadership across cloud, enterprise, and AI workloads. The Venice family spans a broad set of CPUs optimized for throughput, performance per watt, and performance per dollar, including Genoa, our first EPYC CPU purpose-built for AI infrastructure. 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. Customer demand is very strong with more customers validating and ramping platforms at this stage than with any prior EPYC generation, and we remain on track to launch Venice later this year.

Looking more broadly, we are seeing a meaningful acceleration in customer demand driven by the rapid scaling of AI workloads across both cloud and enterprise. Inference 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. At our financial analyst day in November, we outlined a server CPU market growing at approximately 18% annually over the next 3 to 5 years. Based on the demand signals we are seeing today and the structural increase in CPU compute requirements driven by agentic AI, we now expect the server CPU TAM to grow at greater than 35% annually reaching over $120 billion by 2030. In response to this demand, we are working closely with our supply chain partners to meaningfully increase our wafer and back-end capacities to support this growth. As a result, we now expect server CPU revenue to grow by more than 70% year-over-year in the second quarter with robust growth continuing through the second half of 2026 and into 2027 as we ramp our next generation EPYC processors.

Now turning to our data center AI business, revenue grew by a significant double-digit percentage year-over-year as adoption of Instinct accelerates across cloud, enterprise, sovereign, and supercomputing customers. We're seeing strong momentum as customers move from pilots to large-scale production deployments, particularly in inference where our leadership memory capacity and bandwidth are key advantages. This momentum is driving deeper long-term customer engagements including large-scale multi-generation deployments. A key example is our expanded strategic partnership with Meta to deploy up to 6 GW of AMD Instinct GPUs spanning several product generations. Our agreement includes a custom GPU accelerator based on our MI250 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 scale architecture, which integrates Instinct GPUs with EPYC Venice CPUs to deliver fully optimized high-performance AI infrastructure. Together with our previously announced OpenAI partnership, these engagements position AMD as a core partner to the world's largest AI infrastructure builders with deep co-engineering relationships and multi-year visibility into large-scale deployments.

More broadly, Instinct adoption continues to expand across AI native and enterprise customers for both training and inference workloads. Existing partners are expanding Instinct across broader set of workloads, while a growing number of new partners are deploying production AI workloads on Instinct, highlighting the maturity of our hardware and software stack. On the software front, we continue to make strong progress with ROCm, improving performance, scalability, and enabling customers to reach production faster. In our latest MLPerf results, MI355X delivered strong competitive performance across the full suite with leadership results in multiple categories. We also expanded day-zero support for the leading open models, including the latest Google Gemma 4 family, Qwen, Kimi, and others, enabling customers to deploy new models quickly with optimized performance. To build on this momentum, we have significantly accelerated our ROCm development cadence through increased software investments and agent-based coding workflows, enabling faster performance improvements and more rapid deployment of new capabilities.

Looking ahead, customer pull for Instinct is very strong, driven by our leadership performance, memory bandwidth and scale-out capacity. Instinct development is progressing well with strong execution across silicon, software and systems as we advance through key milestones. We have begun sampling MI250X series GPUs to lead customers and remain on track to ramp Instinct production shipments in the second half of the year. As we approach production, demand for MI250X 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. I look forward to sharing more on our next generation Instinct GPUs, EPYC processors, Instinct rack-scale platform and our growing customer engagements at our Advancing AI event in July.

Turning to client and gaming, segment revenue increased 23% year-over-year to 3.6 billion. In client, revenue grew 26% year-over-year to 2.9 billion, led by strong sales of our latest Ryzen processors and continued share gains across consumer and commercial markets. In desktop, we strengthened our Ryzen lineup, including our latest X3D processors that deliver leadership performance across gaming, content creation, and professional workloads. We also introduced the Ryzen AI 400 series and Ryzen AI Pro 400 series desktop CPUs, extending our AI PC offerings across both consumer and commercial systems. In mobile, we delivered strong growth driven by a richer product mix as Ryzen 400 mobile PC shipments ramped and commercial adoption increased. Commercial was a key highlight in the quarter with sell-through of Ryzen Pro PCs increasing more than 50% year-over-year as Dell, HP, and Lenovo broadened their AMD offerings. We also closed new enterprise wins across large technology, financial services, healthcare, and aerospace customers. Looking ahead, we expect demand for our Ryzen CPUs to remain solid in the second quarter. However, we are planning for second-half PC shipments to be lower due to higher memory and component costs. Against this backdrop, we still expect our client revenue to grow year-over-year and outperform the market driven by the strength of our Ryzen portfolio and expanding commercial adoption.

In gaming, revenue increased 11% year-over-year to 720 million. Semi-custom revenue declined year-over-year as expected at this stage of the console cycle, while engagements with customers on next-generation platforms remain strong. In graphics, revenue increased year-over-year led by demand for our latest generation Radeon 9000 series GPUs. We also strengthened our Radeon portfolio with updates to our FSR software that improved performance and visual quality across a broad set of gaming workloads. Similar to the PC market, we believe that second half demand in gaming will be impacted by higher memory and component costs, and we are planning the business accordingly.

Turning to our embedded segment, revenue increased 6% year-over-year to 873 million, driven by strength in test, measurement and emulation, aerospace and defense, and communications, as well as increased adoption of our embedded x86 products. Design win momentum grew by a double-digit percentage year-over-year with billions of dollars in new wins across markets, reflecting the continued expansion of our embedded business from a primarily FPGA-focused portfolio to a broader set of adaptive, embedded x86, and semi-custom solutions, significantly expanding our TAM. Our semi-custom engagements also expanded in the quarter as data center, communications, and other embedded customers leverage our broad IP portfolio and high-performance expertise to build differentiated solutions.

In summary, our first quarter results mark a clear step up in our growth trajectory with accelerating momentum across the business. Our client business continues to outperform the market driven by rising adoption and share gains, while in embedded, design win momentum and demand are strengthening across our expanded adaptive and x86 portfolio. At the same time, our data center business is inflecting with strong demand for both EPYC and Instinct products driving significant growth. While we are still in the early stages of the AI infrastructure cycle, the pace and scale of deployments we are seeing today reinforce both the magnitude and durability of the opportunity ahead. As inferencing and agentic AI deployment scale, they are fundamentally increasing compute requirements, driving both larger-scale accelerated deployments and significantly more CPU compute. AMD is uniquely positioned to lead in this next phase of AI with leadership products across high-performance server CPUs and AI accelerators and the ability to optimize them together as fully integrated rack-scale solutions. We have a world-class supply chain and are making significant investments to expand capacity and execute at scale. With the momentum we are seeing across the business and the expanding market opportunity, we see a clear path to exceed our long-term financial targets, including delivering more than $20 in EPS over the strategic time frame. Now, I will turn the call over to Jean to provide additional color on our first quarter results. Jean?

Yeah, sure, Josh. Thanks for the question. So, first of all, back to when we think about CPU TAM, we've always said that CPUs are a very critical part of data center infrastructure and that's been where we've invested and we saw the first signs of let's call it AI demand really pulling CPU demand last year and that was the reason we updated the TAM to let's call it the 18% CAGR approximately 60 billion. And what we've seen is all of the things that we believed in terms of agentic AI and inferencing and all the CPU compute that is required is just happening and it's happening at a much faster pace. So over the last few months as we've talked to our customers and we've seen how AI adoption is really unfolding, we're seeing significantly more CPU demand from really every major cloud provider as well as enterprise customers. And the way that comes across is as AI adoption scales you need more inferencing, as inferencing scales and you do more, you have more agents and agentic AI, they all require CPUs for all of the orchestration and the data processing and these other tasks. So with that, we've looked at it both bottoms up in terms of talking to customers and having them give us longer term forecasts as well as just doing some clear workload analysis. And yeah, I mean it's a very exciting TAM. I think it's exciting to see CPUs growing greater than 35% to over 120 billion dollars. And then when you think about AMD in the context of that, CPUs are critical for so many tasks that you are seeing a lot more discussion about CPUs in the market. But we actually view it in three categories, right? There's general purpose compute, there's the head nodes that really support the AI accelerators and then there's CPUs just for all of the agentic AI work and to do all of this, our belief is you need a broad portfolio of CPUs, and that's really what we have been focused on building, not just one type, but really a broader in terms of throughput optimized, power optimized, cost optimized, AI infrastructure optimized, as we've done in the Venice family. So, when you put all that together, we're very excited about the larger TAM, and we're also very happy with the traction that we're getting. We're clearly feeling like we're seeing significant share gain as we're going into our Turin portfolio that has ramped very nicely. Venice is extremely well positioned, and we're working with customers right now on beyond Venice and what we're doing in those architectures. So, we feel really good about the market as well as our opportunity to grow to a greater than 50% share of that market.

Sure, Josh. So, we are very excited about MI450 and Helios. We're seeing significant customer interest in those products as well. So, we have certainly talked about our large partnerships with OpenAI and Meta, and those are going really well. We appreciate the deep co-engineering that has gone on there. When we look at the totality of let's call it, based on our current visibility, how those forecasts are coming in with all of our customers, we're actually seeing it above our initial plans that we had planned for 2027. And I think the encouraging thing is we're seeing a breadth of customers who are now very interested in deploying at significant scale MI250 series in those. And those are for both training and inference workloads, although the largest deployments are for inference. And based on all of that and the scale of new customer interest, we see a path to really exceed our original targets of greater than 80% CAGR. And these are really a 2027 timeframe. Obviously, when we talk to customers, we're talking to them about MI255. There's a lot of good traction we're seeing there. MI450 and Helios, I think for significant large-scale deployments. And then many customers are also very engaged with us on the MI500 series. And all of the opportunities there. So, we feel like very, very good progress and the key is that we're continuing to broaden and widen the scope of both customers as well as workloads.

Yeah, okay. A lot of pieces of that question Tom, so let me try to get through it. So first of all on the data center segment in Q1, the server business was greater than 50% year-over-year as we said in the prepared remarks. The data center AI was actually down modestly because of the China transition. We had more China revenue sequentially in Q4 and it was less in Q1. But as we go forward, I think we see strong growth in both segments. So we guided data center Q2 up sequentially double digits and that's double digits in both server as well as data center AI. And the progression as we go forward, so first on the server CPU side, we talked about growing to over 70% year-over-year in Q2 and that continuing into the second half of the year. And on the data center AI side, we will be ramping Helios in the second half of the year, so let's call it starting with initial volume in Q3 with a significant ramp in Q4 and then continuing to ramp in Q1. So that's kind of a little bit of a progression. And then to your questions about customers and supply, I think I answered Josh the customer question. I think we have very good visibility now into the deployments that are on track for 2027. And when I say good visibility, it's visibility down to which data centers are the GPUs going to be installed in. And so that's...

Necessary just given all of the constraints out there. We feel that there is tightness in the supply chain. There is certainly tightness in data center build-outs, but we are confident in our ability to supply to the levels of growth that we're talking about and to exceed the levels of growth that we're talking about. And we're also working very closely with our customers and our partners to ensure that we have good visibility to data center power. And there is much more power that's coming online in 2027. And so with all those things in mind, I think again, lots of things to manage. They say it's a complex ramp, but we're very pleased with the progress on the ramp.

Hi, Ross. So, look, we're very engaged with every major hyperscaler in terms of understanding their needs on the CPU side. I think we have very much wanted to optimize our CPU roadmap for the various workloads. I think we were early to call this AI component of CPUs and so we've been actually optimizing very closely with those customers. The way to think about this, Ross, is that you're going to need a broad portfolio of CPUs. Like, not all CPUs are the same. Frankly, you're going to need different CPUs for whether you're talking about general-purpose operations or you're talking about head nodes or you're talking about agentic AI tasks. They're going to be optimized differently. And we thought through that, and we are absolutely optimizing across the various workloads. So, from a competitive standpoint, we feel very good about where things are. And from a deep relationship with the customer set, I think we feel very good about that. So, from our current standpoint, I think the depth of our road map just expands as we go forward. And you shouldn't think about it as people are going to do one or the other. I think you're going to see people actually use x86 and ARM for many of the large hyperscalers. And even for those who are developing their own, they're still buying lots of CPUs in the merchant market for the reason that I just stated, which is you need different CPUs for the different types of workloads. And there's very high demand at the moment.

Yeah, Tim, the way I would say it is maybe let me bring you back to Q1 for a moment. So, if you look at our significant growth in the server business, it was actually although we were up on a year-over-year basis for both ASPs and units, it was actually much more unit driven. So, we are shipping more CPUs, across not just the high-end Turin family, but we're actually shipping a lot of Genoas, the Zen 4 family as well. As we go forward for Q2 and into the second half, we are guiding for a significant amount of growth. I think there's a little bit of ASP in there, but the way we're thinking about pricing to be fair is we are in a range where the supply chain is tight. And so, there are some inflationary pressures, costs have gone up a bit. And we are sharing some of that with our customers, but we are also being very thoughtful in like this is we're playing out for the long term and that means that our goal is to ship more units and a lot more units. And so from that standpoint, you should imagine that the majority of the growth is unit driven and the ASPs are just really to help cover some of the inflationary pressures.

Yeah, sure. So look, I think what we're seeing is what we expected in the sense that as the AI adoption continues and the volumes continue to go up and the overall market goes up, you are going to see different computer architectures being used because you want to get more cost optimization from that. So we expect that even in that situation, obviously the vast majority of the total TAM is still going to be data center GPUs as the primary accelerator, but you may choose to do optimization around inference, around low latency, around certain parts of the stack, whether it's decode versus prefill. I think that's very natural. The way we look at it is we're developing a full compute portfolio. So that's CPUs, that's GPUs, that's the ability to connect to all accelerators as well as the ability to do customization for certain customers and we've also talked about our semi-custom capabilities. And with all of those compute capabilities in our tool chest, I think we will be able to address very effectively a large portion of this market including the low latency portion of the market. So from our standpoint this is kind of a natural evolution. Now how fast it goes depends a bit on the technology in terms of what share of the TAM these things become but we should expect that there will be different variants and we're well prepared to address those different variants.

Sure Vivek. So the way we're thinking about it is it's largely additive to the TAM. So you should think about we need all of the accelerators to run these foundational models and then as these agents do work they spawn more CPU tasks. So I would say largely incremental. The key is to make sure what we're seeing is in these deployments the key is to make sure the ratio of CPUs to GPUs are the right ratio. So if you're installing a gigawatt of compute, the ratio or the percentage of CPU as part of that gigawatt will increase. Some of the conversation in the industry has been about CPU to GPU ratios. And it's very hard to call exactly, but we certainly see the movement towards where in the past the CPU to GPU ratio was primarily just as a host node in like a 1:4 or 1:8 configuration. Now changing and getting closer to a 1:1 configuration or even you can even imagine if you get lots and lots of agents that you could have more CPUs and GPUs. So, but all in all to answer your question, I think it's largely additive to the TAM and the key is that everyone is now planning and thinking about CPUs at the same time that they're thinking about their accelerator deployments, which is a good thing.

Sure. So, let me answer the second one first. I think from a supply standpoint, we are very happy with our partnerships with the memory vendors and we have secured enough supply to certainly meet and exceed our targets. So, it is a tight memory environment, let me be clear. But I think we have very deep partnerships with the memory providers. And then back to your comments on the inflationary pressures, look, this is something that everyone in the industry is working with in the time of tight supply we are seeing some cost increases on the memory side. I think we are all working through that. The way we're seeing it unfold in the market is actually on the data center side, because of the demand for AI compute. People are largely focused on supply and ensuring that the supply assurance is there. The corollary of that, the larger impact that we're watching is the impact on the consumer market and as we said in the prepared remarks, we are expecting that there could be some demand impact as a result of the memory price increases on things like the PC business in the second half of the year as well as the gaming business. So, we're taking that into account in our overall model and we continue to work closely with the memory providers as well as our customers to ensure that every time we ship a CPU or GPU that it's paired with the memory on the other side so that we don't have compute that is not being deployed.

Sure. And so let me start with the broader question. The broader question, regarding the way we think about the CPU TAM is again, think about it as three categories. So, there is a traditional CPUs, let's call it general purpose CPU TAM that is increasing but let's call it increasing at a low rate, maybe low double digits. Then you have your AI head node which is connecting to accelerators which is also growing but it's smaller and then the largest piece of the growth is this agentic AI piece which we think is really stemming from all of the agentic processes. I don't have a number that I can tell you in terms of relative ASPs because it really depends on the workload that is being run. And what we see going forward is as core counts increase, obviously we will see ASP increase and that's the direction that we're going in as we go forward. But the main point is the largest portion of this is the agentic AI CPUs that are serving these agentic AI workloads in terms of the TAM increase.

Yeah, Aaron, the best way to think about the server CPU landscape is, again, number one, everyone is talking about CPUs. So, that tells you how critical they are for the AI infrastructure and I think that's a good thing. We feel like we're very well positioned. No question, ARM is a good architecture. It has a place in the data center market. We view it as more point products relative to a portfolio where from an AMD standpoint, we built this broad portfolio of CPUs going forward, which you're going to need for all of these different workloads. And we have in the Venice timeframe added an AI optimized CPU with a Verona in addition to our throughput optimized and cost optimized point. So, from that standpoint, I think we're very competitive. We're continuing to innovate on architecture. We're continuing to innovate on both advanced packaging as well as all of the architectural pieces. So, we feel very well positioned going forward. And the key is the TAM is much, much larger than anybody thought. And so, there's a lot of opportunity for different products to be successful in this area.

Sure. So, CJ, I think the client business has performed really well for us. I think if we look at Q1, it actually was a little bit stronger than what we expected. We are seeing some mix shift in the client business. The mix that we're seeing is the MNC or the notebook business is actually growing, especially the premium portion. We're making very good progress in the commercial PC arena with our AI PCs. We did see desktops a little bit softer just given desktop is a more consumer-focused market. And so, in that market, it's more impacted by some of the memory pricing and the component pricing increases. When we look at the full year, our commentary is we are planning for some demand impact in the second half due to the memory pricing. But even in that environment, what we're focused on is ensuring that we continue to make good progress on the commercial business and continuing to focus on the premium segments of the market. So, we believe that we will continue to grow on a year-over-year basis for the client business compared to last year. And as it relates to ASPs, again, it's a little bit of puts and takes between notebook and desktop, but overall, I think we're feeling good about our opportunity to outperform the market in client going forward.

Actually Blaine, I don't think we see the older products hanging around longer in our case. I think it might be company-specific stuff. In our case, we actually see first of all, Turin is very strong. We actually crossed over 50% of our revenue being Turin this quarter. Genoa is very strong. We're still shipping some Milan, but I would say that's come down over time. So, in general, people want to use the newer products because they're just more efficient in every aspect from performance, from cost structure, from power standpoint. So, that's what we're seeing. By the way, I should also mention, in addition to what we're seeing in the cloud segment of server, we're seeing really nice strong pick up in enterprise. And there as well, we're seeing our newer products do very well. So, from our standpoint, it is all about ensuring that we ship what the customer needs. And in this case, it typically is our newer products. And we expect that to continue. As we transition into Venice later this year, we will expect Turin and Genoa to continue shipping, but there's a lot of goodness in going to the new products. And on the supply chain side, I know there's been a lot of discussion about how tight the supply chain is. The supply chain is tight. I would definitely say that. But I also think this is an area where we excel. We have very deep relationships across the supply chain. On the wafer side, on the back end capacity side. And we are seeing meaningful improvements in that. And as our customers come to us with more demand, we are getting more supply. And the good thing about this is we're now talking about 27 CPU demand, we're talking about 28 CPU demand. And so, that allows us to just plan much better as we go forward.

Yeah, and if I just add to that, Blaine, the places that we invest Jean's absolutely right. We're investing in R&D ahead of sales and marketing. But the places that we're investing in sales and marketing are paying off. So, the investments are going into enterprise servers, they're going into commercial PCs, they're going into mid-market, small and medium business. These are places where AMD traditionally didn't invest, but now that we have a much broader portfolio both on the server CPU and on the commercial PC side, it makes sense for us to invest because that's sort of the very best part of those markets.