Qualcomm Inc (QCOM) September 2026 Conference Transcript

Okay, good morning, everybody. Welcome to the Goldman Sachs Cucopia 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 Pakabala with us today. Welcome, Akash. Thank you.

Thank you for having me here.

You know, Akash, I think at the highest level, Qualcomm has been 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, multi-year, and nature, and with some warrants attached to us. 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 to the extent 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 used to be a smartphone, primarily a smartphone company. As we look forward, we are very much a highly diversified company with, I'll 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 months ago at our investor day. And so very pleased to announce the 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 businesses, 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 1.6 T and follow-on generations. And the transaction includes a warrant agreement that we've outlined in our 8K 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 westing 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 a 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 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 those things and let you unpack it a little bit more, but maybe zooming out again for a second, from a technology perspective, of companies' long-held expertise in processors. And we're seeing, though, 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 are not the correct assets to 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 perspective. Yeah.

So let me maybe kind of step back, as you said, and outline the different components of our data center strategy. There are four 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 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 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 pre-fill 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 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 and 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 a SIRDIS that is integrated into a lot of these solutions. Even our custom silicon engagement includes AlphaWave SIRDIS. and they have optical connectivity products that are also a part of the Amazon agreement. So I think those four areas, of course, we are 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 review. So maybe also another high-level question. Clearly, the size of the AI opportunity, I think, is 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's 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's view on all this in general? And at the end of the day, what's your view on whether IAI computing stays confined to the data center or moves to the edge? And how are you kind of positioning the company and the products around that?

Yeah, 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 on 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 one of my responsibilities 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 token 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'll 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 memories 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 advantage 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 Edge 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 you to that target, or do you need to announce other customers to come to the market to get that?

Yeah, so let me kind of summarize the data points and then build to the 15, 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. 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 Humane as an AI Accelerator customer. They'll be deploying that as well. So when you add those kind of four or five things that I outlined, you're already very significantly on your way towards 15. And so it doesn't take us a lot more to get to the 15. 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, you know, in the longer run, maybe you've talked about this kind of 5% of market share of a trillion-dollar 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 ARMS server CPU penetration versus x86 and maybe your share within the ecosystem more broadly?

Yeah, so our longer-term forecast is not just tied to CPU engagement. Of course, it's CPU, AI, Accelerator, Custom Chip, and Connectivity, all four 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're 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 temp obviously has tripled since then, and so we're talking about over $200 billion a year now. And we see a very significant, and about half of that market transitioning over to ARM 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 have our HBC technology that delivers this significant performance advantage. So overall, very confident that this is a strong portfolio that doesn't rely on one or two customers, doesn't rely on one or two products. This is multi-gen, multi-product, multi-customer engagement, and that diversity is what gives us the confidence that the opportunity beyond 29 is much, much bigger.

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

Yeah, so I think, obviously, when you look at training and inference, we're better suited to inference. Within inference as pre-fill 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 endgame. 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 this 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. Yeah, very good.

And then finally, software. Help us understand how the software ecosystem is changing. You bought Modular this year, announced a number of open-source initiatives in general around that. Where do you think the market's going? What 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?

Yeah, 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 Latner and Modular, and they were on this mission of building a stack that disaggregates the silicon and works across silicon. And so once you port a model on top of the modular stack, it works across whether it's NVIDIA Silicon, AMD Silicon, or R Silicon, and then they also support AWS and Apple. So it truly disaggregates the need for specific silicon tied to the stack and then builds a modern stack that's very easy for developers to work on, but then also allows them to port once 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 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 makes 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.

Almost 20 minutes in. We have not talked about smartphones yet, so I want to go there. You know, you have a huge installed base across billions of devices and smartphones based on your core processing and wireless technologies. You know, as we move to a world where kind of devices at the edge 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, three to five years, both in terms of processing, memory, and so on?

Yeah, 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 where you just give work to an agent and the agent is figuring out across the apps or across cloud MCPs of how to execute on the task for you. And so very different device it is becoming. I think it's a given that the endpoint 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 smartphone, sometimes a standalone 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 agentic 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 hyperscalers 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.

Tactical question to follow up on that. I want to sort of ask you sort of how do you think your customers are adopting to sort of the new normal in terms of memory prices and the unit dynamics that impact on the market? Clearly, you've already talked about you think Android has bottomed as a market today. How are you thinking about sort of the forward in terms of smart from year growth for the broader market, some of the catalysts that might accelerate growth from year?

Yeah, so the catalysts are the ones that I just outlined. But maybe to start with the first part of your question, We've seen maybe volume go down by low double digits on smartphones, low teens, over the last year. And the impact is largely on the lowest tier and the second lowest tier, so everything below $300. That's where the largest impact has been. Because in a lot of cases, memory has now become more than half of the bomb of the phone. And obviously, it makes some of those device prices unsustainable. And so we're seeing an impact there. If you look at the very top of the smartphone market, which is where Qualcomm has the most significant presence, we have actually not seen much of an impact. The prices clearly have gone up. But really kind of when you step back and look at the importance of the phone and the consumer's lives, it's the central device. It's the most important device, right? And so you're continuing to see people spend the money they need to spend to get the right phone. And that, I think, shows up when you look at the market data as well. So we don't expect that to change. We think the low end of the market will continue to be under pressure. But again, I think as we stand today, we are at the low part of the cycle, and we have all these new vectors in place that improves the opportunity for us going forward.

Okay, so we went through a lot of things about sort of how AI is changing, moved to the edge, also the impact of Agentec. How does this apply to automobiles and your automotive business? How is AI changing the automotive architecture over time and sort of how you participate in that transition?

Yeah, incredible set of changes obviously happening in automotive and we've been at the center of it. I'd say definitely our most successful diversification initiative. Next year we expect to be the largest chip supplier to the automotive industry. very, very kind of well-positioned in terms of driving the transition, not just participating in it. I'll say AI is very deeply integrated into automotive. It started with ADAS. Obviously, AI is the foundation for what happens in autonomous driving, and we are one of the two chip leaders on the autonomous driving side. But what is also happening now is AI is becoming central to the cockpit experience as well. So within the car we're seeing this, your hands are already busy on the wheel. It's difficult for you to go and work the buttons as you're operating the car and so being able to talk to the car, I think if there are people in the audience who drive a Tesla you can get very used to talking to grub while you're driving, right? And so it is just a great way to use voice, to use AI, to use voice AI, really, to kind of interact with the car and get information to ask it to do things. And so that is becoming very foundationally getting deployed in automotive. And we're seeing every OEM around the world as kind of the core feature that they're looking to deploy in kind of next generation cars is around AI. If you allow me, I'll also say that the way we think about robotics is really, for us an extension of the automotive opportunity. Because from a silicon perspective, those things look very similar. And in some ways, a robot is a car standing up. So we are extending that portfolio, everything we're doing in automotive, those products to robotics as well. And AI is obviously foundational to that. So very excited about kind of this broader category of physical AI that starts with automotive, goes into industrial and robotics and us being able to take our automotive platform into those areas.

So you see that robotic opportunity as more or less coincident from the product standpoint for you?

A very large leverage of everything we've built from automotive, at least from a silicon perspective, the stack is different, obviously.

Okay. And then just in terms of content growth in that automotive market, You know, what areas of that business do you see kind of driving the fastest content growth?

Yeah, so tremendous content growth for us. What has happened is we were at our generation three of products. We went to gen four. Now we're deploying, beginning to deploy gen five. The compute content growth from gen three to gen five is 8x. So a lot more processing, a lot more AI. and we've also transitioned the business from selling chips to selling modules and SIPs. And so we're integrating memory, we're integrating passives and we're delivering a complete solution to our customers. And so there's a cost advantage to the customers, there's a performance advantage to the customers, there's obviously content growth for us that comes from that. And this sits on top of the fact that there's a demand for a lot more compute, there's a demand for a lot more AI. And all of those things are coming together, and that's why when you look at our financials for automotive, we had set a target for $10 billion in revenue in 31, then we pulled it to 29. Now we've pulled it back further because we're getting to those numbers much faster than we thought a couple years ago because of this trend for content growth, and then we're gaining share across the board as well, right? Whether it's the Chinese OEMs or whether it's Europeans or Japanese or Korean or American, we're gaining share across the board in the growing part of the automotive silicon tab.

I want to talk a little bit about sort of smart glasses and wearables market, which you just brought up a minute ago. What is really needed for this category to move to sort of enthusiast-level adoption, to broad consumer adoption, and do you see the potential for these kind of smart glasses and other wearables to be used more broadly in things like the enterprise, or is it more of a kind of a consumer-centric thing in your view?

Yeah, so I think it's definitely consumer and enterprise. But the way the device is being designed, and maybe I'll broaden the category beyond smart glasses, it's a personal AI device that, as I said earlier, you can talk to it, it can see what you can see, it can hear what you can hear. And so you have certain OEMs focusing on glasses. You have others building watches, pendants, pins, dongles, all kinds of devices being built. But each device has the same premise. It's a battery-powered, high-performance device that is an AI-first device that becomes the interaction point for a user. The reason glasses is a very reasonable form factor is it's close to your eyes and close to your ears. And so it can see what you can see and hear what you can hear. And so that's a form factor that works very well. Outside of the consumer use cases, there's tremendous use case in enterprise. Clearly, this is a platform that allows you to have a lot of efficiencies if you're working on a machine, if you're working in a distribution center, in retail. Just being able to look at something and get information about it, there's tremendous value. So I think we're going to see broad deployment of it. Like automotive, our strategy is also transitioning here. We're transitioning from chips to delivering modules and SIPs because form factor is so important that we are integrating everything into the smallest possible module that would be very difficult for someone else to do. And so when you combine processing wireless connectivity AI along with memory passives, and you put it in the smallest possible module that is performing at very low power, only Qualcomm can do that. So I think this is a device that is for us to own, and as the market takes off, you'll see it come through in our financials.

I think I'm going to be chastised if I don't have the CFO and don't ask any financial questions. And we don't. So maybe as data center kind of becomes a larger part of your product mix and portfolio, how should investors be thinking about the longer-term margin profile for your business?

Yeah, so I think at Investor Day, we outline kind of how we see the margins play out. I think gross margins are going to be somewhere in the range of where we are at today. We think there will be a combination of custom products being lower in margin than our current rate, but merchant products being significantly higher, and there will be some weighted average. and we'll have to see how kind of the two businesses play out relative to each other. So that's our view on gross margins. The operating margin argument for Qualcomm has always been around scale and being able to leverage R&D across everything we're doing. And so as we grow in these new areas, it just automatically helps our operating margin, and that's the way we are thinking about it.

Yeah, in terms of then investment balance versus that growth trajectory, maybe talk about that intensity.

Yeah, so you should think of our investment increase in OPEX trailing the growth significantly. And so as we look kind of three years out, we've set a target of 30% operating margins. But really, kind of as we go from there, there is no reason to invest more. It's really just kind of incremental revenue scale sitting on top of the existing investment base. and so excited about what that combination brings from a financial perspective as well.

Now, we've covered a lot of ground today. As you think about kind of Qualcomm's position in AI, compute, data center, et cetera, what do you think investors are still sort of underestimating about your opportunity ahead, and what would you sort of like everybody take away from this if they only had to take away one thing?

Well, I think obviously investors are very focused on data center. We outlined a compelling strategy and a compelling set of products, but there was a little bit of, okay, but I want to see how you execute on it. And today is a key milestone for that. Obviously, very large deal with Amazon, but it's not the last one. It's just the first one. And we have a very strong engagement with another hyperscaler that we've not disclosed, but similar to the transaction, the engagement we have with technology engagement we have with Amazon. So I think it's just the beginning. We're executing on everything we said we'd execute on, and hopefully today's announcement gives people a lot of confidence that that'll be the case. And then when you look beyond kind of data center and when you look automotive IoT, clearly our position is very strong, and we're very well positioned to really execute faster than any target we've set out there as well. And then finally on smartphones, the third leg of the stool, I'll say we're at the low point in the cycle. Things can only go up from here, both from a way the market is evolving, but then also from the impact that we're seeing from memory in the short term kind of resolving through. So it is an opportunity to buy into a well-priced, highly diversified, and growing stock.

I think, unfortunately, we're out of time, but Akash, thanks so much for being here. Thank you so much. I appreciate it. Thank you.