$AVGO Broadcom Q2 2026 Earnings Conference Call

Thank you, Jean. Thank you, everyone, for joining today. In our fiscal Q2 2026, total revenue reached a record $22.2 billion, up 48% year on year, above our guidance on strength in AI semiconductors. Q2 operating margin was a record 67% and adjusted EBITDA was a record 69% of revenue, which was above our guidance. Even as our revenue scales up massively, driven by AI, our operating and EBITDA margins remain strong and stable. Turning to semiconductors, Q2 revenue was a record 15 billion, as we grew 79% year on year. Driving this growth was AI semiconductor revenue at a record 10.8 billion, up 143% year on year, and above our outlook. Networking represented almost 40% of our Q2 AI revenue. Demand for XPUs and networking is simply insatiable. During the quarter, bookings for AI semiconductors were over $30 billion against the $10.8 billion we shipped. In the second half of 2026, we expect AI semiconductor revenue to double from the first half we shipped this year. Consistent with this trend in Q3, we expect AI semiconductor revenue to accelerate to $16 billion, up over 200% year on year. For the full year 2026, we expect to achieve AI semiconductor revenue of $56 billion, up approximately 180% from fiscal 2025. Now, we expect this momentum to continue into fiscal year 2027 and reiterate our AI semiconductor revenue guidance to be in excess of $100 billion. We expect AI semiconductor revenue growth to continue in fiscal 2028 based on the following initiatives we have with core customers. As you are aware, with Google, we announced in April that we entered into a long-term agreement to develop and supply multiple generations of TPUs and AI networking. Our relationship continues to be strategic and very substantial as we continue to provide vastly superior technology and execution compared to other alternatives. This ability to provide differentiated value to Google ensures that our business will sustain and grow for the foreseeable future. For Anthropic, as you know for 2026, we are providing access to Broadcom TPU-based compute of over 1 GW. In April, we entered into an agreement to enable Anthropic to access another 5 GW of next-generation TPU-based compute beginning in 2027. For OpenAI, we have delivered silicon and we are on track for production late 2026. We have a contractual commitment to deploy 1.3 GW in 2027 as part of the larger 10 GW that by 2029 agreement we announced last year. For Meta, in April, we announced a partnership to deliver multiple generations of MTIA XPUs. And under this agreement, we expect to deploy 3 GW through the end of 2028. The initial order for 1 GW, which includes XPUs and our networking, has been received and will start delivery in the second half of 2027. For our other two customers, we expect shipments to begin late 2026 and accelerate into 2027. To date, we have received purchase orders totaling $6 billion. While we have significant IP and execution leadership in XPUs, networking is key to building scalable XPU and GPU clusters. And here in networking, we have at least one generation of technology and product leadership. For scale up within racks, we enable direct attach copper based on our industry-leading 200G and 400 gig serdes, driving core package copper with Ethernet and PCIe Express switches. For scale out between racks, we have been shipping the industry's only 100 terabit Ethernet switch, the Tomahawk 6, for over a year. We will now be taping out our next-generation 200 terabit switch this quarter. And in CPOs, which is co-packaged optics, 1.6 terabit DSPs, CW and EML lasers, we are the de facto standard in the industry. To expand AI subclusters across data centers, we remain the industry leader with our Jericho 3 and Jericho 4 fabric solutions, enabling the world's largest deployments at multiple hyperscalers. Our strategic vision is to bring together Broadcom's leading technology and investor partners with the strongest balance sheets to deliver at scale sufficient compute capacity at the lowest cost and power for the leading AI frontier labs including Anthropic and OpenAI. To deliver this vision, we are creating the AI XPU platform with Apollo and Blackstone and other leading investors to deploy more than 20 gigawatts of compute capacity through 2028. The first tranche of this platform valued at $35 billion is in fact currently being launched by Apollo. Now, turning to non-AI semiconductors, Q2 revenue of $4.2 billion was up 6% year-on-year. Bookings during the same period exceeded $6 billion which is a clear indication we're on the path towards a full cyclical recovery. Broadband service provider and enterprise networking together were up, partially offset by a seasonal decline in wireless. Consistent with this trend in Q3 we forecast non-AI semiconductor revenue to be approximately $4.5 billion, up 12% from a year ago. In summary, we expect Q3 semiconductor revenue to be 20.5 billion, up 124% year-on-year. Let me turn to infrastructure software segment. Q2 software revenue of 7.2 billion was up 9% year-on-year, in line with our guidance. Bookings continue to be strong as we sustain ARR growth of 17% year over year. For Q3, we forecast software revenue to be approximately 8.9 billion, up 31% year-on-year. We just released VMware Cloud Foundation 9.1, focused on improving infrastructure efficiency, security, and support for enterprise AI inferencing workloads. With strong server demand globally, the deployment of VCF 9.1 for on-prem cloud computing is extremely strong, driving robust revenue growth. This release adds heterogeneous compute support across GPUs and CPU architectures, including AMD, Intel, and Nvidia platforms, enabling enterprise cloud customers to run AI, Kubernetes, and traditional virtualized workloads on a common private cloud environment. So, to sum it up for Q3 2026, we expect our consolidated revenue to grow to 29.4 billion, up 84% year-on-year. We expect operating margin to be stable at approximately 67% of revenue and adjusted EBITDA to be at approximately 68% of revenue. And with that, let me turn the call over to Kirsten.

That's a very complicated set of number question. To begin with, let's start with 26. What doing a math basically 2x to 2x, the first half we should we ship about in total AI revenue something in the range of 19 billion if you want to be precise. So you And if you do what I indicate and 2x that in the second half, you get to pretty much in the range of what we're talking about, which is around 56 billion. Uh hold on. So that set of numbers is still very very does I don't very well. Now, the only bigger question on the second half, which we're going into very detailed analysis of is yeah, we really keep the momentum going as we expect to see in 2027. What we will see in 2027 is continued growth of the level we're talking about. And And you'd If you drive on that basis of what we're seeing here, almost 2x what 2026 will be, I think you will easily see that 2027 will exceed very easily a hundred billion dollars in 2027, which is pretty much what we indicated last quarter, and we are continuing to say that it will be over a hundred billion in 2027. So in that sense, if anything else, it might be based on what we're doing very much on track, if not stronger. But we're not trying to guide you every quarter what 27 would be like. So we basically say it continue to be in excess of a hundred billion in 27, but it is on the same trajectory as we are seeing in the back half of 26.

Okay. Well, you know, it's a very very strong agreement. And it basically reflects the strength of the partnership we have simply because of the products we do, the multi-generational products, and the intellectual property we deploy into this whole program. To answer your question specifically, it's a commitment that is very substantial in dollars. Very very substantial amount of dollars. Now, we also accept the fact that while we like to win every design in that program, we also accept the fact that given the growth of consumption and development and consumption of AI compute even by our partner Google, that we fully expect that there'll be some diversity of sources for them. But our commitment from them is a very substantial dollar amount.

No, I mean, Ross, as Kirsten said in her remarks, structurally the semiconductor margins remains very stable and very solid. It's the mix, particularly the mix between software and non-AI to the very, very rapidly growing AI semiconductor that is just diluting gross margin.

No, no no racks, is all chip. We only chips.

Sure. Well, I think the accelerating part of if you talk about power, realize one thing, it's the dollars per gigawatt, the content dollars or racks per gigawatt, it's not accelerating that much because you are creating chips that drive that each individual chips are driving higher and higher power. So, you're driving less chips though the price ASP of each chip is going up in price. So, dollars per gigawatt billions of dollars per gigawatt is relatively stable. But, the number of gigawatts will keep go as will accelerate as I think some other remarks indicate. And that's what we are seeing that the amount of gigawatts required measured compute capacity as measured by number of gigawatts is growing very fast. And we're seeing that. And we are seeing that particularly to the point where for even two of our customers we're talking about which is Anthropic and OpenAI for which we're creating this platform to enable them to run sufficient compute power. We're talking about capacity as measured by gigawatt power that are way ahead of what we fully what we have expected say six months ago. And that's just these guys. We're not talking about the consumption beyond the XPU platform we have announced here from our other customers which is Google own internal workloads, Meta's workloads, and any other customer and the other two customers that we have. So, fold that in and you're talking about gigawatts in totality if you ask about 27 or 28 that will continue to grow. We expect in fact 28 to be a substantial growth from what we are forecasting in 27.

Getting supply is not just about dropping money, Tim, though that does work. No, we are very comfortable that we have been able to secure supply of the types you mentioned about for needs 26, 27. Working on 28 and 29 right now.

All customers have been coming to us incrementally over the last few months. We expect that to continue and by and large, yes.

Well, you fought good question. Yeah, for '27, we indicated about 10 gigawatts shipment in '27. That's still very much intact. They will be shipping 10 gigawatts planning to ship 10 gigawatts in '27 and that nothing has changed. Back half loaded to that extent, yes. And which really provides an interesting trajectory into '28 with this back half trajectory. So, '28, we expect a lot more gigawatts.

That's a hell of a great question, Jim. It's just very difficult to answer because of how do we predict that? Because there are quite a few moving parts there. One of which is to start with is as more as as a volume as more and more of our customers turn to XPUs. Obviously, XPUs uses very much our networking components across the board. So, that's great for us and that drives increase in consumption. But it also means that we have been able to sell networking to non-XPU footprints. So that part of it would dilute the growth rate. And this 40% I consider as a very well I'm almost a situation where stars align where we're shipping a lot of networking to non-XPU while the growth of XPU are obviously allowing us to grow this networking business to our XPUs and we get to 40%. But I see that as probably as high as that percentage of total AI revenue would go. Not the first time I indicated that. The more expected percentage as a share of total AI revenue for networking would be lower.

Can you repeat that question, especially the front end? I didn't quite get what you're saying here. I don't want to answer the wrong way.

Oh, I have to correct you on that. Our deal with Anthropic that we cut basically talked about and basically released disclosing our 8K recently. As the deal we did with Anthropic is we use our TPU chips that we developed to provide the compute capacity to Anthropic. We won that it wasn't backstopped in that sense. We were the ones providing the chips to Anthropic. We were the ones providing that compute capacity to Anthropic.

Well, not I don't think so. I think our business model is actually very, very straightforward, which is we are developing XPUs, custom AI accelerators for use by our customers who are pretty much all LLM developers, whether it's for training or inference. We are also creating a portfolio of critical components to enable these XPUs and even GPUs to be clustered and form better performance. And that continues to be the model we do, which is we provide chips, technology in the form of chips, whether they be AI computer accelerators, we call XPUs, or networking chips that cluster them together, be it switches, PCI Express connectors, DSPs, lasers, NICs, and routers. And that's very much still the model we employ in semiconductors. And we still, as you can see, our financial model and the program we go to drive towards a chip versus model through the technologies we provide. What we're doing to enable some of these LLM players to be able to get access to the volume of compute capacity, the large gigawatt of compute capacity they need to scale up their models, is we are, as I announced here today, creating in partnership with guys with the best balance sheets around, a vehicle to basically have these chips funded for these LLM players who otherwise might have difficulty getting access to our technology, which provides them with the lowest power and the lowest cost.

Well, we're not seeing it. If anything else, as I reported, the high volume of core count of CPUs selling together with GPUs is driving some accelerated growth of our VMware business. And as you can see in Q3, we're seeing an accelerated growth. And we expect that to continue I guess for the next multiple quarters as this demand picks up. Long term, given the kind of products we do in infrastructure software, very, very close to literally the hardware, the hypervisor, which is where our products are, we do not expect to see any impact on software products.

Well, that's a very interesting thought here and you may be very well right that enterprise consuming AI is still relatively at an early stage of the game. But having said that, what we're also seeing is a lot of what the enterprises consuming on tokens, they're buying a lot of these tokens from the platforms, the API platform they pull from the platforms of this same name of customers we talked about, which is Anthropic, OpenAI, Gemini. Look, these are the large guys that are pulling it from and that's where I think substantially most of these tokens consumption are tied to those LLMs. And these LLM guys, as they productize their true frontier models, whether it's Opus 4.7, ChatGPT 5.5, or Gemini 3.5, comes back to the same end demand on compute capacity we provide to all these guys. And so, even a growth of enterprise demand that we're now starting to see as enterprise starts to consume AI tokens for their own workloads, for their own productivity uses as consumers do, they're buying from the same source. These same few guys. And that's what's driving this very large I call it insatiable growth in compute capacity that we are experiencing and we see that continuing to happen now through 2027 and what we see now through 2028 as well. So this is getting to be quite a sustainable and steepening trajectory of demand.

Well, I guess the answer to that is it's possible, but the reality of the whole issue is the compute capacity, most of the AI generated provided in the form of SaaS models. APIs are pulled from the clouds, whether they're from Bedrock, Vertex, Azure, or the first party from the it is still provided in the cloud. So a lot most of all that demand at the end of the day in terms of compute capacity, which is what we're doing, comes from those few large frontier model developers and the products they generate to supply to consumer and enterprises globally. Source of demand comes from those frontier model labs who are developing the products which consumer and enterprise like you and us and our companies are consuming. And what we're doing is providing that capacity to that demand source. As opposed to going to a company or bank and trying to provide them XPUs and then they having to try to build it, run a create a software stack to then write application and running themselves. I'm sure there are few enterprises doing now, but they're not many. It's early stage in that whole game. Right now, the most of the demand are coming from the frontier model players who are creating products. The things as I say, like code assistants, like engineering verticals which are really coming from the same source of guys who are doing all this those few guys doing the frontier models. It's not really coming from 100,000 companies directly trying to buy XPUs or for that matter GPUs. It's not.

Well, there's a huge demand of compute. See, a lot of our large six customers now, they realized that lead time to get compute, you need lead time. You need to be thoughtful. And it's not just asking for wafers to get the chips or memory to ensure their HBMs are available or DRAMs available. They're also talking about 'Hey, I got to have the power, the power shell.' So, all this is planning ahead. And what we are seeing the bookings that coming is not for immediate delivery. Some are hope to have, but the reality they all accept is they need to align quite a few other things in place before they can deliver. But, they're placing their orders early and they're placing their orders now and they're placing their orders in fairly huge demand, which basically gives us a lot more visibility than we normally otherwise would have in semiconductors. Our visibility runs all the way to 2028 right now. Just 3 months ago, I can tell you our visibility run pretty much 27. Today, it runs to 28. And that's part of that's a big part of reason why we are creating this XPU platform as really the platform to plan to build up this capacity put in place such capacity for those frontier model customers of ours who are seeing, as you guys are seeing in some of the financials, they're telling you and any experiences you want you have, we're just driving huge amount of consumption of tokens from those compute capacity we're giving them. We have the benefit now of a lot of lead time. And we're planning that. And it's not because of shortage of our components, it's also the other elements that need to be put in place, which basically relates to power. And connection into an infrastructure globally or through America at least that enables inference to be distributed to consumers and enterprises throughout the country. So, it's we're just getting a lot of lead time.

Our revenue our content per gigawatt will increase. Put it simply, our content from the fact that our computer chip will XPUs will go up in price very dramatically. Particularly when you not only put SRAMs into it as far as cost, you start putting embedding CPU costs into the same XPUs and making those chips basically multi-die with lots of HBM. So, that the trajectory of content increases increase will go on. It just doesn't go up every month, every 6 months, or every quarter, but it will follow one generation to the next that the content will grow per gigawatt.