QUALCOMM Incorporated (QCOM) Earnings Call Transcript & Summary

Okay. Good morning, everybody. Welcome to the Goldman Sachs Communacopia and Technology Conference. My name is Jim Schneider. I'm the semiconductor analyst here at Goldman, and it's my pleasure to welcome you to our first session of the day. We're very happy to have QUALCOMM and CFO and COO, Akash Palkhiwala with us today. Welcome, Akash.

Thank you. Thank you for having me here. .

Akash, I think at the highest level, QUALCOMM is working pretty hard to diversify beyond smartphones over a number of years. I want to get your latest thoughts on the progress starting with data center, but you had a very exciting announcement this morning. So I think a custom silicon agreement with Amazon, multiyear in nature and with some warrants attached those. Maybe you can kind of unpack that for us, help us dimensionalize the opportunity both in terms of size, type of products and so on that you can.

Sure, sure. So first of all, thank you for having me here. Very exciting deal for us. I think as you rightly noted, the company is transforming. We are used to be a smartphone -- primarily a smartphone company. As we look forward, we are very much a highly diversified company with, I'd say, three legs of the stool. We have smartphones, we have auto IoT and data center. And we set pretty compelling targets for our data center business a couple of months ago at our Investor Day. And so very pleased to announce this strategic transaction with Amazon. It's a first of many as we make progress towards what we laid out. So you should think of this as really a landmark deal for us in the data center business. It kicks us off there. It includes two components on the product side. So first is customized silicon business with them, multiple generations of that. We are also going to be working with them on optical connectivity solutions, starting with 1.60N follow-on generations. And the transaction includes a warrant agreement that we've outlined in our 8-K that we filed today. But the way it's structured is we issue warrants against purchases of up to $60 billion from Amazon for data center products over the next 10 years. And there is an upfront vesting of about 15% of those warrants that's associated with the $60 billion, and that is tied to upfront commitments that are being made by Amazon. So the 15% really ties to what they're committing upfront. If you kind of wind back and look at what we had committed at Investor Day, we said approximately $5 billion in revenue in fiscal '27. Fiscal '27 starts shortly for us, and this makes our number of very high confidence. It also positions us for fiscal '28 to deliver strong year-over-year growth from '27 to '28. We are also similarly proceeding with the other data center customer that we talked about at Investor Day. So a lot of strong progress. We'll have start having revenue with Amazon starting the December quarter. And so we're already in production with them. Very excited about how this deal positions us to execute on our targets going forward. We also did set a target of $15 billion in fiscal '29 and you should think of this agreement as one of the core components that allows us to execute on that.

Okay. Great. I want to come back to all of those things -- look you unpack it a little bit more, but maybe Zoomin again for a second. From a technology perspective, the company's long-held expertise and processors. And we're seeing a lot of technologies kind of become more relevant to winning formula in AI overall, specifically networking storage and software. So maybe help investors understand or contextualize for us why these are or not the correct assets they have under the same corporate umbrella? And speak to maybe QUALCOMM's right to win in the marketplace against competitors who maybe have a slightly more diversified technology portfolio in some of those areas?

From a data center prospective?

From a data center prospective, yes.

Yes. So let me maybe kind of step back, as you said and outline the different components of our data center strategy. There are core parts to what we're trying to do. First is custom silicon engagement. And so obviously, in addition to Amazon, we've talked about one other global hyperscaler that we're engaged with. And I think it's very simple. We have a very strong portfolio of technologies, both from a compute and a connectivity perspective. We also do a lot of chips, especially in advanced nodes, tremendous expertise of high-performance, low-power, tremendous expertise of high-yield manufacturing. And so we're bringing all of those things together for our custom silicon engagement. So that's the first part of the business is custom silicon. There's a lot of opportunity in the market. We are obviously a new player, but we have all the technology scale to deliver on what's required there. The second part of the business is AI accelerator. This is an area where the market is going through a transition. We used to have one uniform solution for all kinds of AI accelerator needs. And what we're seeing in the market is a disaggregation of compute, where there is certain kind of solutions, GPUs would be very good for certain things, XPUs would be very good for other things. As you break the workloads down into training and inference as you break inference down into prefill and deCODE, there's a clear desire from hyperscalers to have customized solutions for various components. One of the challenges in the current set of solutions that are available is memory bandwidth constrained solutions. And so QUALCOMM has this innovative technology that we outlined at Investor Day. We call it high bandwidth compute, which is really kind of stacking compute and memory together to deliver extremely high bandwidth that are customer -- that are perfect solution for certain kind of decode workloads within inference. And so we're very excited about the reaction we're getting from customers. And so there's more to come on that. But -- very excited about what that technology brings to the market, something very unique and that the market is looking for. So that's our custom -- sorry, our AI accelerator business. The third is CPU, where we deliver what we think is the leading CPU at the edge in phones and PCs in automotive and industrial devices, and we're bringing that to the data center. And this is delivering high performance at low power, low cost, and that's what we are bringing to the table. And so we have an agreement with Meta as our first customer for silicon solutions in data center and so excited about that. And then finally, connectivity. I think we acquired Alphawave. They had SerDes that is integrated into a lot of these solutions. Even our custom silicon engagement includes Alphawave SerDes, and they have optical connectivity products that are also a part of the -- part of the Amazon agreement. So I think those core areas, of course, we're a new player. But the fact that we come with so much expertise in chip manufacturing at scale, maybe the broadest technology portfolio on the computing side, and that's what we bring to the table.

Fair enough. Very helpful overview. So maybe also another high-level question. Clearly, the size of the AI opportunity, I think is a lot much bigger than a lot of what investors thought about just a few years ago. One point of controversy though in the market has been sort of agentic AI and the scale of token demand that is going to generate. At the same time, I think everyone is also talking about constraints, power supply, other factors, land power shell that sort of can measure or limit the pace in which we can generate those tokens. So what's QUALCOMM view on all of this, in general? And at the end of the day, what's your view on whether II computing stays, can find a data center or moves to the edge? And how you kind of position the company and the products around that?

Yes. Great question. So first of all, we don't think about it as this or this, right? If you think about kind of general compute, not AI compute, normal compute, it's always been distributed in the cloud and in the edge. And we think AI kind of plays the same way. There are certain things that make sense to run on the edge. There are certain things that would make sense to run the cloud. And that is the way we expect things to evolve. Now with our kind of expanded strategy and presence in data center, we have an opportunity to play on both sides, and I'll address both individually. To your specific question on data center, our view is you're going to see demand grow very, very significantly in terms of token. So 1 of my responsibility is also running IT within QUALCOMM. And so as you think about how our engineers use tokens to write software, to design chips, to support customers, we're seeing a massive growth in tokens usage within the company. And of course, that is going to be replicated across every enterprise in the world. And it drives a lot of efficiencies, a lot of time-to-market advantages in terms of being able to launch new products sooner. And so our view is there's going to be very, very significant demand growth for tokens and there will be a need to satisfy that through different kinds of solutions. Clearly, there is a constraint on power. There is a constraint on how many wafers are available and just memory is available. And I think some of those things play to our strength. Our strength has always been delivering performance per watt. And so in any power constrained environment, QUALCOMM has something unique to offer. And so we're excited that we can bring that to data center. The second thing I'll say is in terms of wafer scale, maybe QUALCOMM is one of the top five players in the world. And so us being able to use our wafer scale as a strategic advantage in building our data center business is also very important. And so I think when you think about data center, we bring all those technologies I just outlined. But in addition to that, in a constrained environment, I think QUALCOMM is an advantaged position. On the edge, we're seeing a very similar transition on the edge happening over the next couple of years as we're seeing in data center, which is build an AI accelerator that sits next to the main chip. And their job is to really run pervasive AI at very, very low power. And so we're building very similar to the HBC technology that we talked about in data center. We're building a similar compute plus memory stack as a coprocessor that would go into all edge devices. So whether, again, it's phones or cars or PCs or industrial devices, robotics, those are going to be areas where that technology will become relevant. And so we see data center as an opportunity. We see a as an opportunity for AI.

Very good. So I want to come back to the target you talked about earlier, from your Investor Day, $15 billion in fiscal '29 for data center revenue. Maybe talk about the underlying assumptions here? And are the existing programs, including the one you announced today enough to sort of get to that target? Or do you need to announce other customers to come to the market to hit that?

Yes. So let me kind of summarize the data points and then build to the $15 billion, right? So we talked about $5 billion in fiscal '27, very high confidence at this point. The year starts in about a month for us less than a month. And we are already -- we have POs, we're building the chips. So that's very high confidence. We also talked about strong growth going into '28 based on the engagements that we have. So it allows us to grow significantly beyond the $5 billion. In -- late in '28, going into '29, we'll have the Meta engagement with CPU come on top of that. And then we'll also have -- we've announced as an AI accelerator customer that will be deploying that as well. So when you add those kind of 4, 5 things that I outlined, you're already very significantly on your way towards $15 billion. And so it doesn't take us a lot more to get to the $15 billion. But don't just think about it like that. I'd say that's the numerical part of the answer. But you should really think about the engagement that we will have will be very broad-based because we're delivering technologies, as I outlined earlier, that the market needs that the customer needs. And so tremendous, I think, very well positioned to take advantage of it.

Fair enough. And then in the longer run, maybe you've talked about as kind of 5% of market share of $1 trillion TAM in all-in. Help us bridge between what you just said and how you get there? And how much is kind of tied to your assumptions around Arm's server CPU penetration versus x86 and maybe your share within the ecosystem more broadly?

Yes. So our longer-term forecast is not just tied to CPU engagement. Of course, it's CPI accelerator, custom chip and connectivity, all 4 franchises that we're building. Specifically on CPU, when we signed our agreement with Meta, the size of the CPU market was a lot less than it's perceived to be today. And so we're very excited because we have a very strong engagement with one of the top hyperscalers. We are going to deliver what we think is the best performance per watt, performance per area solution in CPUs. And so we have a tremendous opportunity to grow beyond Meta. The CPU TAM, obviously, has tripled since then. And so we're talking about over $200 billion a year now. And we see a very significant about half of that market transitioning over to our architecture where we will have performance leadership. So very well positioned there. But the largest part of the market, obviously, is the AI accelerator market, and we are tackling it two ways. We have the custom chip engagements that we have with various hyperscalers and then these are global hyperscalers, and we're working on their main AI accelerators. This is not kind of ancillary custom chip engagements. And then the second thing I'll say is we're also -- we have our HBC technology that delivers the significant performance advantage. So overall, very confident that this is a strong portfolio that doesn't rely on one or two customers, don't rely on one or two products. This is multi-gen, multiproduct, multicustomer engagement. And that diversity is what gives us the confidence that the opportunity beyond '29 is much, much bigger.

And then just a couple of more data centers before we close out that section. You just talked a minute ago about inference becoming more disaggregated. Decision requirements for prefill, decode, other stages of the stack and kind of implies a little bit different architecture than we've seen historically. How do you help QUALCOMM viewing this shift strategically? And where do you think the biggest opportunities for you to participate are?

Yes. So I think, obviously, when you look at training and inference, we're better suited to inference. Within inference is prefill and decode, we are starting with a very keen focus on solving the memory bandwidth problem in deCODE. And so our technology stack, HBC is uniquely positioned to that. But that's not the end game. That's where we are starting. I think our ability to kind of extend into everything inference is very strong. We have the technology assets to go do it. And because of the stacking technology and being able to deliver this performance at very, very low power, and to your earlier point, given the power constraints in data center, we have something that's unique and the customers see it. The customers see the need for disaggregated computing. And I think it just positions us very well in a transforming market where the market is transforming in our favor.

Yes. Very good. And then finally, software. Help us understand how the software ecosystem is changing. You bought modular this year and announced a number of open source initiatives in general around that. Where do you think the market is going? Where are some of the challenges you need to overcome to kind of go head-to-head with software incumbents like NVIDIA's CUDA product? And how is Modular helping you get there?

Yes. So software, obviously, is a very, very important problem statement. One of NVIDIA's advantages, obviously, is CUDA. And so what we were missing is a very modern stack that makes it extremely easy to port models onto our silicon, right? And so we met Chris, Latin and modular, and they were on this mission of building a stack that is -- that disaggregates the silicon and works across silicon. And so once you put a model on top of the modular stack, it works across whether it's NVIDIA silicon, ABM silicon or our silicon. And then they also support AWS and Apple. So it truly disaggregates the need for specific silicon tied to the stack. And then build the modern stack that's very easy for developers to work on, but then also allows them to port one and work across different silicon platforms without compromising performance. And so we just came across this incredible company that is just the right size, right culture for us that was building something that we were missing. And so that will become our stack going forward. We're also taking a very friendly approach to open source. We have making the kind of the lower layers of the stack. Think of it as an Android-like approach, where we're making the stack available to everyone in the industry to deploy. And so very optimistic about what it brings both as a horizontal industry platform, but then something that cuts across everything that QUALCOMM makes, whether it's an edge chip or a data center chip. And it takes our silicon very accessible to developers, which was the goal in the first place. So I think it was a missing piece that we have now resolved and it comes at the right time as we start scaling our data center products.

Excellent. Almost 20 minutes in. We have not talked about smartphones yes, so I want to go there, please. You have a huge installed base across billions of devices and smartphones based on your core processing and wireless technologies. As we move to a world where kind of devices at the edge to get more important, especially given the realities of AI we just talked about, what changes should we expect to see in smartphones over the next, say, 3 to 5 years, both in terms of processing, memory and so on?

Yes. So it's interesting. I think this is very much People think of it as a mature market, but it's a market that's very much in transition. And so let me go through kind of a few trends around smartphones. First is kind of building smartphones for agentic experiences. And so we've obviously been in this touch world that goes app by app. And there is a clear vision from a lot of hyperscaler players who are looking for endpoints for their clouds as to building something that is agentic first, that is voice first. And that's a device that were you just give work to an agent and the agent is figuring out across the apps or across clouds of how to take out that -- execute on the task for you. And so very different device it is becoming. I think it's a given that the end point is that. The question is how long does it take and how the journey happens, but it's a device in transition from that perspective. From a silicon perspective, it's a device in transition because of the disaggregation of AI compute and having this AI accelerator that sits next to the main chip and how it is going to increase the silicon content in a device. The third thing I'll say is there's also this third device being added to the personal device ecosystem. That is sometimes connected to the smartphones sometimes a stand-alone device. And we think of it as a wearable device, a device that can see what you can see, a device that can hear what you can hear and a device that you can have an agent AI conversation with. So I'll say every hyperscaler we know of, every cloud company, model company we know of globally is in the process of building a device like that. And so whether it's the big hyperscaler as you know in the U.S., the model companies you know in the U.S., the hyperscalers you know in China, every single OEM globally, they're all using QUALCOMM chips to build a third device that adds to the smartphone. And so very excited about kind of all of those transitions happening at the same time. And we are obviously coming off of a low point in the smartphone cycle given the memory industry dynamics. So I think of smartphones as an area that will offer -- can only offer growth to us given all these vectors.