Inc. Second Quarter Fiscal Year 2026 Financial Results Conference Call. At this time, for opening remarks and introductions, I would like to turn the call over to G.U., Head of Investor Relations of Broadcom, Inc.

Thank you, Operator, and good afternoon, everyone. Joining me on today's call are Hawk Tan, President and CEO, Charlie Kawaz, President of Semiconductor Solutions Group, and Ram Valaga President Infrastructure Software Group. Also joining is Kirsten Spears, Chief Financial Officer. As we announced, Kirsten will be retiring June 12th and today we have joining us our incoming Chief Financial Officer, Amy Tiener. Thank you Kirsten for your leadership over the past 12 years. Broadcom Broadcom distributed a press release and financial tables after the market closed, describing our financial performance for the second quarter fiscal year 2026. If you did not receive a copy, you may obtain the information from the Investor Section of Broadcom's website at Broadcom.com. This conference call is being webcast live and an audio replay of the call can be accessed for one year through the Investor Section of Broadcom's website. During the prepared comments, Hawk and Kirsten will be providing details of our second quarter fiscal year 2026 results, guidance for our third quarter fiscal year 2026, as well as commentary regarding the business environment. We'll take questions after the end of our prepared comments. Please refer to our press release today and our recent filings with the SEC for information on risk factors that could cause our actual results to differ materially from the forward-looking statements made on this call. In addition to US GAAP reporting, Broadcom reports certain financial measures on a non-GAAP basis. A reconciliation between GAAP and non-GAAP measures to the extent possible is included in the tables attached to today's press release. Comments made during today's call will primarily refer to our non-GAAP financial results. I will now turn the call over to Hawk.

Thank you, G. In 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%. Thank you, Jay. 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 are massively driven by AI, our operating and EBITDA margins remain strong and stable. Turning to semiconductors, Q2 revenue was a record $15 billion, as I said before, 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 networking simply insatiable. During the quarter, bookings for AI semiconductors were over $30 billion, against the $10.8 billion in the second half of 2020 expect AI semiconductor revenue to double from the first half we shipped last year from the ship this year. Consistent with this trend in Q3 we expect AI semiconductor revenue to accelerate to 16 billion dollars up over 20 to up over 200 percent year-on-year. For the full year 2026 we expect to achieve to achieve AI semiconductor revenue of 56 billion dollars up approximately 180 percent 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 our six core customers. 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 deliver 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. Entropic. As you know, for 2026, we are providing access to Broadcom TPU-based compute of over 1 gigawatts. In April, we entered into an agreement to enable Entropic to access another 5 gigawatts 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 gigawatts in 2027 as part of the larger 10 gigawatts that by 2029 agreement we announced last year. For matter, in April, we announced a partnership to deliver multiple generations of MTIA XPUs. And under this agreement, we expect to deploy 3 gigawatts in 2028. The initial order for 1 gigawatt, 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. 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 with at least one generation of technology and product leadership. For scale-up within racks, we enable direct-attached copper based on an industry-leading 200G and 400Gb 30s, driving co-packaged copper with Ethernet and PCI Express switches. For scale-up between racks, we have been shipping the industry's only 100 terabit Ethernet switch, the Tamag6, 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 terapid DSPs, CW and EML lasers, we are the de facto standard in the industry. Extend AI clusters across data centers. We remain the industry leader with our Jericho 3 and Jericho 4 fabric solutions and enabling the world's largest deployments and 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 capacity at the lowest cost and power for the leading AI frontier labs, including Entropic and OpenAI. To deliver this vision, we are creating the AI with Apollo and Blackstone and other leading investors to deploy more than 20 gigawatts of compute capacity through 2028. The first trench of this flat $5 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 way on the path towards a full cyclical recovery. Broadband, server storage, and enterprise networking together were up, partially offset by 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 customers, enterprise 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.

Thank you, Hawk. Let me now provide additional detail on our Q2 financial performance. Consolidated revenue was a record $22.2 billion for the quarter, up 48% from a year ago. Gross margin was 77.1% of revenue in the quarter, down 230 basis points year on year, as semiconductor became a larger proportion of our product mix. Consolidated operating expenses were $2.2 billion, of which $1.6 billion was R&D. Q2 operating income was a record $14.9 billion, up 52% from a year ago. Note that even with the decline in gross margin, operating margin increased 200 basis points year over year to 67.3% as operating expenses remained relatively flat. Adjusted EBITDA of $15.2 billion, or 69% of revenue, was above our guidance of 68%. Now a review of the P&L for our two segments, starting with semiconductors. Revenue for our semiconductor solution segment was a record $15 billion, with growth accelerating to 79% year-on-year driven by AI. Semiconductor revenue represented 68% of total revenue in the quarter and AI semiconductor revenue represented 49% of total revenue. Gross margin for our semiconductor solution segment was approximately 70%. Operating expenses of 1.2 billion reflected increased investment in R&D for leading-edge AI semiconductors and represented 8% of revenue. Semiconductor operating margin of 62% was up 460 basis points year-on-year, reflecting our strong operating leverage. Now moving on to infrastructure software. Revenue for infrastructure software of $7.2 billion was up 9% year-on-year and represented 32% of revenue. Gross margin for infrastructure software was 93% in the quarter and operating expenses were $1 billion in the quarter. Q2 software operating margin was up 310 basis points year-on-year to approximately 79%. Moving on to cash flow. Free cash flow in the quarter was a record $10.3 billion and represented 46% of revenue. We spent $231 million on capital expenditures. We ended the second quarter with $19.6 billion of cash compared to $14.2 billion in the prior quarter. We ended the second quarter with inventory of $4.3 billion as we continued to secure supply to support strong AI demand. Our days of inventory on hand were 86 days in Q2 compared to 68 days in Q1 in anticipation of accelerating AI semiconductor growth in the second half of the year. Turning to capital allocation, in Q2 we paid stockholders 3.1 billion of cash dividends based on a quarterly common stock cash dividend of 65 cents per share. Now moving to guidance. Our guidance for Q3 is for consolidated revenue of 29.4 billion up 84% year-on-year. We forecast semiconductor revenue of approximately 20.5 billion up 124% year-on-year. Within this, we expect Q3 AI semiconductor revenue of $16 billion, up over 200% year-on-year. We expect Q3 infrastructure software revenue of approximately $8.9 billion, up 31% year-on-year. Moving on to margins. As the proportion of AI revenue significantly grows in Q3, we expect Q3 consolidated gross margin to be down to approximately 74%. This decline in gross margin does not represent a structural change in semiconductor margin. Rather, it reflects product mix between semiconductors and infrastructure software. Regardless of the impact to gross margin, we expect Q3 operating margin to be 67 percent, which is flat quarter on quarter, demonstrating our strong operating leverage. We highly recommend that investors model semiconductor and infrastructure software margins separately to properly reflect the impact of changes in total revenue mix going forward. We expect the non-GAAP tax rate for Q3 in fiscal year 2026 to be approximately 16% due to the impact of the global minimum tax and the geographic mix of income compared to that of fiscal year 25. In Q3, we expect the non-GAAP diluted share count to be approximately 4.94 billion shares, excluding the impact of potential share repurchases. That concludes my prepared remarks operator please open up the call for questions thank you to ask a question you will

need to press star one one on your telephone to withdraw your question press star one one again due to time restraints we ask that you please limit yourself to one question please stand by while we compile the q a roster and our first question will come from the line of harlan sir

with jp morgan your line is open yeah good afternoon thank you for taking my question um thanks for all your support kirsten and amy uh welcome to the team uh first just a housekeeping quick housekeeping item hawk on on this fiscal year ai sort of 2x growth second half over first half that would put ai revenues over 60 billion with sequential growth in fiscal q4 but you gave us this 56 billion dollar number which is only like one and a half x you know half over half growth with 4Q AI actually being down sequentially. So if you could just help us kind of square the numbers there. And then for my real question, you know, back in December of last year, you talked about in the AI backlog, next 18 months, $73 billion. Market sort of took that number, spread that linearly over six quarters. But we know that the backlog is always more front loaded over the first four quarters, right? And sure enough, you're going to deliver around 80% or more of that backlog in this fiscal year or first four quarters. Just given the strength of all your programs, the broadening of the customer base, accelerating year-over-year trends in your AI shipments, all the multi-gigawatt partnerships that you just articulated today, which is most of it, which is set to start to fire next year. Is it fair to assume that your 18 months AI backlog, second half of this year through all of fiscal 27 sits at $200 billion or better?

Complicated set of number questions. To begin with, we ship in total AI revenue, something in the range of 19. So if you do 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, Harlan. So that's the numbers, it's still very, very, now you'll pick a question on the second hour which you're going into a very detailed analysis of is, yeah, we 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 if you drive on that basis of what we're seeing here, almost 2x, in the range of 2x what 2026 will be, I think you will easily see that 2027 will exceed very easily $100 billion in 2027, which is pretty much what we indicated last quarter, and we are continuing to say that it will be over $100 billion in 2027. So in that sense, if anything else, it might be based on what we're doing very much on if not strong stronger but we're not trying to guide you every quarter what 27 would be like so we basically say it continues to be in excess of hundred billion in 27 but it is on a same trajectory as we are seeing in the back

half of 20s got it okay thank you Hawk one moment for our next question and

And that will come from the line of Blaine Curtis with Jefferies. Your line is open.

Hey, good afternoon. Thanks for taking my question. Hawk, I wanted to ask you, inter-quarter you had that 8K with the long-term agreement with Google. I think obviously you're probably not going to tell me what the total value is there, but I think there's a lot of concern about share within that customer. I was just kind of curious, now that you have this agreement, maybe you could speak to a little bit more in terms of your confidence. and if there's upside of that customer, you know, is it a fixed amount or is there share? Is there any way you can kind of add some color to that agreement that came out?

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-general products, and the intellectual property 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 will be some diversity of sources for them, but our commitment from them is a very substantial dollar amount.

One moment for our next question. And that will come from the line of Ross Seymour with Deutsche Bank. Your line is open.

Thanks for the asked question, and congrats to both Kirsten and Amy. Question on the gross margin side of things. I know, Kirsten, you talked about it going down due to the mixed dynamics within the semis versus the software side. But given the strength on the software side and the quarter, it seems like the gross margin is falling a little bit harder. So behind the scenes, can you just talk a little bit about what the drivers within semis are? Is that the XPU versus the networking side of things? And is that trend likely to continue next year? Are there rack scale versus chip scale? All those sorts of dynamics, any color you could give on that would be helpful.

Yes, certainly as our semiconductor business grows, just to reiterate, on a consolidated basis relative to our software business, you're going to have a decline in margins, right, a bit. You'll have compression. But remember that it's accretive because we have strong operating leverage, right? So our operating margin, within semiconductors, we've always said our ASICs, the TPUs, some of the wireless business has lower margins. So as the TPUs continue to accelerate, there'll be pressure overall on margins. But the connectivity side, the AI networking side of the business has very rich margins. So it'll offset it somewhat.

I mean, Ross, as Kirsten said in her remarks, Structurally, the semiconductor margins remain very stable and very solid. It's particularly a mix between software and non-AI to the very, very rapidly growing AI semiconductor that is just diluting gross margin.

And the rack versus chip side of things, is that all clarified now?

perfect thank you one moment for our next question and that will come from the line of Ben Reitsis with Mellius your line is open yeah hey guys thanks appreciate it

wanted to ask about 2027 Hawk with regard to you know previously we talked about the cam being ended well it's kind of a longer term question actually you've talked about the TAM being 10 to 20 and whatnot. It seems that one of your competitors talked recently about the, you know, the TAM per gigawatt going up a lot, you know, as we go throughout the decade. And it seems, you know, it wasn't just due to infrastructure, it was due to the compute and networking components and other things. Perhaps you're familiar with that comment that Jensen made where the overall infrastructure is going from something around 50-something towards 100 and the compute content going way up are you are you seeing the same thing as you go throughout the long term is that potentially being an accelerator you know what you've already outlined in terms of your cam per gigawatt and how

are you thinking about that thanks a lot sure well I think the accelerating part But if you talk about, realize one thing is the dollars per gigawatt, the content dollars is not as much as each individual, 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, relatively stable. But the number of gigawatts will keep going, as I think some of our remarks indicate. And that's what we are seeing, the amount of gigawatts required to measure, you know, compute capacity as measured by number of gigawatts. We are seeing that particularly to the point where for even two of our customers, we're talking about, which is Entropic 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 don't talk about the consumption beyond the PlatXPV platform we have announced here. Our other customers, which is Google-owned internal workloads, MetaS workloads, and any other customer, and the other two customers 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.

Thank you, Hock.

One moment for our next question, and that will come from the line of Timothy Arcuri with UBS. Your line is open.

Thanks a lot, Hock. I wanted to ask you about supply and kind of your ability to get incremental volume of wafers and HBM as I look at some of your competitors I mean they're kind of able to drop you know 20 billion dollars out of thin air and get incremental you know wafer supply so I'm wondering do you feel pretty good about like if a customer comes to you are you able to get upside in terms of wafers and HBM and and and are you beginning to consider maybe using other boundaries to add more optionality to your to your to your supply thanks a lot getting a

supply it's not just about dropping money team though that does well no we're about four needs 26 27 working on 28 and 29 right now right but if a customer

comes to you and wants incremental supply are you able to go to your suppliers and get it the way that it seems like some of your competitors are

old customer come customers have been coming to us continue okay thank you one

moment for our next question and that will come from the line of Stacy C. Rascon with Bernstein Research. Your line is open.

Hi, guys. Thanks for taking my question. Hawk, you gave some gigawatt shipment targets for next year for your various customers. I just want to know, are those any different? Do they contemplate any change from what you said last quarter, right? I think you said that was like close to 10 gigawatts you'd be shipping in 27. And can you just sort of help us shape the year? it sounded to me like he expected that to be more back half loaded in 27 I given given the shape of the of the ramps but most importantly is there any change that is it more gigawatts or less gigawatts or the same gigawatts versus

what you were suggesting last quarter well good question yeah for 27 we indicated about 10 gigawatts shipment in 27. They're still very much intact. They will be shipping 10 gigawatts, we're planning to ship 10 gigawatts in 27 and nothing has changed. Back half loader, 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.

Got it. That's helpful. Thank you.

One moment for our next question. And that will come from the line of Jim Schneider with Goldman Sachs. Your line is open.

Good afternoon. Thanks for taking my question. I was wondering if you could comment a little bit on the profile of your networking business talk. As we head through fiscal 26 and 27, about 40% of AI revenue this quarter. Will you expect that to sort of fall back down as some of these custom ramps ramp into the end of the year, into early next year? Or would you sort of expect to stay at the upper end of that range and maybe talk about when you see some of the optical and CPO revenue becoming meaningful? Thank you.

There's a hell of a... Quite a few moving partners uses a lot of our networking components And that drives increase in consumption. But it also means that we have been able to sell networking to non-XPU. So that part of it would dilute the growth rate. And this 40%, I consider as a very, well, almost a situation where stars are aligned, where we are shipping a lot of networking over 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 AR 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 closer to around 30%.

One moment for our next question. That will come from the line of Tom O'Malley with Barclays. Your line is open.

Hey, Hawk. Thanks for taking the question. So I noticed with the most recent deal with Anthropic that you guys are using Broadcom chips as a backstop for the deal. do you expect more deals to come like this in the future? And then as you start to see the AI environment, is there any way you're thinking about financing in the future? Are you going to continue to do it with chips or anything that you can offer on that?

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

Sorry, Hawk. Essentially, the most recent deal with Anthropic is being backstopped by Broadcom chips. Do you think that in the future, you will see more deals done this way. And then any comments on the future financing of deals with the large AI models?

I have to correct you on that. Our deal with Entropic, and that we basically talked about a release, disclosing our 8K recently. The deal we did with Entropic is we use compute capacity to... The one that wasn't backstop in that sense. We were the ones providing the chips. We were the ones providing the compute capacity in tropics.

Thank you. One moment for our next question. That will come from the line of CJ Muse with Cancer Fitzgerald. Your line is open.

Yeah, good afternoon. Thanks for taking the question. I guess, Hawk, in recent years you've talked about really focusing your efforts on very large XPU platforms. And I'm just curious. We're seeing many kind of XPU attached derivatives, you know, across interconnect storage other and I'm wondering if there's any sort of Programs there you know are more niche that are that are whetting your appetite

Oh, no, 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 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 in form, and that continues to be the model we do, which is we provide technology in the form of chips, whether they be AI compute 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, we 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 the compute capacity, large gigawatt of computer 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 they're getting access to technology, which provides them with the lowest power and the lowest cost.

One moment for our next question. That will come from the line of Ateef Malik with Citi. Your line is open.

Hi, thank you for taking my question.

I have a question on infrastructure software business.

Are you guys seeing any impact of AI, agentic AI on your software growth and renewals? And if you can just talk about some sort of long-term growth

for that business.

Well, we're not seeing it. If anything else, CPUs are in business and as you can see in Q3, we're seeing an accelerated growth and we expect it to continue, I guess, for the next multiple quarters as this demand picks up. But long term, given what we do in the hardware, which is where our products are, we do not expect to see any impact on software products.

And one moment for our next question. That will come from the line of Edward Snyder with Charter Equity Research. Your line is open.

Thanks a lot. Now, this is very interesting because the gigawatts that you've laid out for the different customers makes it very clear that the two that are offering kind of CSPs, I don't want to say CSP, but consumer versions of AI, Anthropics and OpenAI, have very large gigawatt commitments in the out years. I know part of that's catch-up because they've just started late, where your oldest customers have been doing these for quite some time. But even part of Google's is offering cloud services to other folks too. So are we seeing a shift here? I know that initially a lot of the XPUs and the AI services were through the hyperscalers with their own customer workloads. We've talked about that ad nauseum. And now you're seeing AI finally hit the enterprises and you're seeing cloud take off with the programming, which is sweeping everybody. Can we expect then that there's going to be this big second wave of demand that's driven as AI starts hitting enterprises is in consumer getting access to it or finding usable tools because the numbers you're saying here are significantly different for the two classes of

customers very interesting talk here and and you're you and you may be very well right that enterprise consuming 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 enterprise is consuming on tokens. They are buying a lot of these tokens from the platforms, the product API platform, API they pull from the platforms of this same name of customers we talked about, which is Entropic, OpenAI, Gemini. These are the large guys they're pulling it from, and that's where I think a high, but high substantially most of this tokens consumption are tied to those LLMs and these LLM guys as they productize their frontier models whether it be Opus 4.7 check GPT 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, AI tokens for their own workloads, for their own productivity users as consumers do, they're buying from the same source, these same fugas. 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're seeing now through 2028 as well. So this is It's getting to be quite a sustainable and steepening trajectory of demand.

So if I could, doesn't this change the dynamic of what we talked about before? You talked about seven or so customers for your XPUs, but this is actually happening. You've already seen it, Google Operating Cloud Services for GPUs. It opens up XPU access to all those smaller companies that don't meet the criteria for doing their own ASAP. that you couldn't partner with to Broadcom's technology through these platforms is it why would that not be the case well I guess the answer to that

is it's possible but the reality of the whole issue is this the compute capacity most of AI generated provided in the form of SAS SAS models API's are pulled from the clouds, whether they're from Bedrock, Vertex, Azure, or the first party, it is still provided in the cloud. So, 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 to consumer and enterprises globally source of demand comes from those frontier model labs who are developing the products which consumer 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, create a software stack to then write applications and run it themselves. I'm sure there are a 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, creating things things, as I said, like code assistants, like engineering verticals, which are really coming from the same source of guys who are doing all 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.

One moment for our next question, and that will come from the line of Joe Moore with Morgan Stanley. Your line is open.

Great. Thank you. You talked about $30 billion of AI bookings in the quarter, which is a lot, I guess, relative to this quarter and next quarter shipments. Can you talk about the dynamic? Why is there so much backlog now? Or is there, you sort of said you can react to upside with supply, just why so many bookings this quarter relative to revenue?

Well, there's a huge demand of compute. See, a lot of large, this few, six customers now, they realize 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 that 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 are placing your orders early and they're placing your 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. Three months ago I can tell you our visibility run pretty much 27. Today it runs to 28 and that's a And that's a big part of the reason why we are creating this XPV platform as really the platform to plan to build up this, 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 are telling you and in the experiences you have, which is driving huge consumption of tokens from those compute capacity we are 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 particularly relates to connection into an infrastructure globally or through America, at least, that enables inference to be distributed through to consumers and enterprises throughout the country. So we're just getting a lot of lead time.

Very helpful. Thank you.

Thank you. We do have time for one final question, and that will come from the line of Joshua Buchalter with TD Cowan. Your line is open.

Hey, guys. Thank you for taking my question. In the past, you've talked about sort of $15, $20 billion per gigawatt of compute. And, you know, given the 10 that you implied is what you'll be doing next year, it implies a much larger number than $100 billion. You know, you've also mentioned that the value per gigawatt does vary per project. So I guess how should we think about the evolution of your revenue per gigawatt over time? As I would expect, on one hand, den-to-den pricing to increase on programs you're already shipping, But also there are other projects that are entering the model. Thank you.

Our revenue, our content per gigawatt will in content from the fact that our compute chip will automatically, particularly when you not only put SRAMs into it as far as cost, you start putting a lot you start putting embedding CPU costs into the same XP you basically multi die with lots of HVM so that the trajectory of content increases increases for closing remarks thank you operator Broadcom currently

plans to report its earnings for the third quarter of fiscal year 2026 after close of market on Wednesday, September 2nd, 2026. A public webcast of Broadcom's earnings conference call will follow at 2 p.m. Pacific time. That will conclude our earnings call today. Thank you all for joining. Cherie, you may end the call. This concludes today's program. Thank

you all for participating. You may now disconnect.