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Welcome to Broadcom Inc.'s 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 Ji Yoo, Head of Investor Relations of Broadcom Inc.

Thank you, operator. Good afternoon, everyone. Joining me on today's call are Hock Tan, President and CEO, Charlie Kawwas, President, Semiconductor Solutions Group, and Ram Velaga, 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, Amie Thuener. Thank you, Kirsten, for your leadership over the past 12 years. 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, Hock 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 Hock.

Thank you, Ji. 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 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 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. 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 with our six 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 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. For Anthropic, as you know, for 2026, we are providing access to Broadcom TPU-based compute of over one gigawatts. In April, we entered into an agreement to enable Anthropic to access another five 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 Meta, in April, we announced a partnership to deliver multiple generations of MTIA XPUs. Under this agreement, we expect to deploy 3 gigawatts through the end of 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 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. Here in networking, we have at least one generation of technology and product leadership.

For scale up within racks, we enable direct attached copper based on our industry-leading 200G and 400G SerDes, driving co-packaged copper with Ethernet and PCI 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. 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 extend AI clusters 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. 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 a path towards a full cyclical recovery. Broadband, service storage 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-over-year. Let me turn to Infrastructure Software segment. Q2 software revenue of $7.2 billion was up 9% year-over-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-over-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. 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. With that, let me turn the call over to Kirsten.

Thank you, Hock. 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%. A review of the P&L for our two segments. Starting with semiconductors.

Revenue for our Semiconductor Solutions 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 Solutions 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 $4.33 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 $0.65 per share. Now moving to guidance. Our guidance for Q3 is for consolidated revenue of $29.4 billion, up 84% year-over-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%, which is flat quarter-over-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 2025.

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. Our first question will come from the line of Harlan Sur with J.P. Morgan. Your line is open.

That's a very complicated set of number questions. To begin with, let's start with 2026. Doing a math, basically 2x to 2x. The first half, we ship in total AI revenue, something in the range of $19 billion, if you want to be precise. 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, Harlan.

That set of numbers does tie up very well. Your bigger question on the second half, which you're going to need a very detailed analysis of is, yeah, we will 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. 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. We are continuing to say that it will be over $100 billion in 2027.

In that sense, if anything else, it might be based on what we're doing very much on track, if not stronger. We're not trying to guide you every quarter what 2027 would be like. We basically say it continues to be in excess of $100 billion in 2027. It is on a same trajectory as we are seeing in the back half of 2026.

One moment for our next question. That will come from the line of Blayne Curtis with Jefferies. Your line is open.

Well, it's a very strong agreement. 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 we've deployed into this whole program. To answer your question specifically, it's a commitment that is very substantial in $. Very substantial amount of $. 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. Our commitment from them is a very substantial $ amount.

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

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. Remember that it's accretive because we have strong operating leverage, right? Our operating margins will stand up a bit over time to that. Within semiconductors, we've always said our ASICs, TPU, some of the wireless business has lower margins. As the TPU continue to accelerate, there'll be pressure overall on margins. The connectivity side, the AI networking side of the business, has very rich margins. It'll offset it somewhat as we go.

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 highly, rapidly growing AI semiconductor that is just diluting gross margin.

No rack. It's all chips.

We're in the chip business only.

We only chips.

Only chips.

One moment for our next question. That will come from the line of Ben Reitzes with Melius. Your line is open.

Sure. Well, I think the accelerating part, if you talk about power, realize one thing, is the $ per gigawatt, the content $ or racks per gigawatt, is not accelerating that much because you are creating chips that each individual chips are driving higher and higher power. You're driving less chips, though the ASP of each chip is going up in price. $ per gigawatt, $ billions per gigawatt is relatively stable. The number of gigawatts will accelerate as I think some of our remarks indicate. That's what we are seeing, that the amount of gigawatts required, compute capacity as measured by number of gigawatts, is growing very fast. We're seeing that.

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 have expected, say, six months ago. That's just these guys. We've not talked about the consumption beyond the XPU platform we have announced here from our other customers, which is Google-owned internal workloads, Meta's workloads, and the other two customers we have. Fold that in, and you're talking about gigawatts in totality. If you ask about 2027 or 2028, that will continue to grow. We expect, in fact, 2028 to be a substantial growth from what we are forecasting in 2027.

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

Getting supply is not just about dropping money, Tim, though that does work. We are very comfortable that we have been able to secure supply of the types you mentioned about for our needs 2026, 2027. Working on 2028 and 2029 right now.

Customers have been coming to us incrementally over the last few months. Expect that to continue. By and large, yes.

One moment for our next question. That will come from the line of Stacy Rasgon with Bernstein Research. Your line is open.

Well, good question. Yeah. For 2027, we indicated about 10 gigawatts shipment in 2027. That's still very much intact. We're planning to ship 10 gigawatts in 2027, and nothing has changed. Back-half loaded to that extent, yes, and which really provides an interesting trajectory into 2028 with this back-half trajectory. 2028, we expect a lot more gigawatts.

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

That's a hell of a great question, Jim. It's just very difficult to answer because of how do we predict that. There are quite a few moving parts there. One of which is to start with is as a volume, as more and more of our customers turn to XPUs. Obviously, XPUs uses very much a lot of our networking components across the board. That's great for us, and that drives increase in consumption. It also means that we have been able to sell networking to non-XPU footprints. That part of it would dilute the growth rate. This 40%, I consider as almost a situation where stars align, where we are 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%.

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 closer to around 30%.

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

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 the wrong way.

Oh, I have to correct you on that. Our deal with Anthropic and that we basically released, disclosed in our 8-K recently. As the deal we did with Anthropic is we use our TPU chips that we developed to provide the compute capacity to Anthropic. It wasn't backstop in that sense. We were the ones providing the chips to Anthropic. We were the ones providing the compute capacity to Anthropic.

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

Well, I don't think so. I think our business model is actually 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. That continues to be the model we do, which is we provide chips, 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, DSP, lasers, NICs, and routers. We still, as you can see, our financial model and the program we go, we drive towards a chip business model through the technologies we provide.

What we are 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.

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

Well, we're not seeing it. If anything else, as I reported, the high volume of core count of CPUs selling together with GPUs, it's driving some accelerated growth of our VMware business. 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 close to literally the hardware, basically the hypervisor, which is where our products are. We do not expect to see any impact on software products.

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

Well, that's a very interesting thought here. You may be very well right that enterprise consuming AI is still relatively at an early stage of the game. 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 they pull from the platforms of this same name of customers we talked about, which is Anthropic, OpenAI, Gemini. These are the large guys they're pulling it from, and that's where I think high, substantially most of these tokens consumption are tied to those LLMs. These LLM guys, as they productize their frontier models, whether it be 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.

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 users, as consumers do, they are buying from the same source, these same few guys. That's what's driving this very large, I call it insatiable growth in compute capacity that we are experiencing. We see that continuing to happen now through 2027 and what we're seeing now through 2028 as well. 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 AI generated are provided in the form of SaaS models. APIs are pulled from the clouds, whether they're from Bedrock, Vertex, Azure, or the first party. It is still provided in the cloud. 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.

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 application and run it themselves. I'm sure there are few enterprises doing now, but there are not many. It's early stage in that whole game. Right now, most of the demand are coming from the frontier model players who are creating products. Things, as I said, like code assistance, like engineering verticals, which are really coming from the same source of guys who are doing all those. 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. That will come from the line of Joseph Moore with Morgan Stanley. Your line is open.

Well, there's a huge demand of compute. See, a lot of our large, these few six customers now, they realize that lead time to get compute, you need lead time. You need to be thoughtful. That'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." All this is planning ahead. What we are seeing, the bookings that are coming, is not for immediate delivery. Some are hope to have, the reality they all accept is they need to align quite a few other things in place before they can deliver.

They are placing their orders early, and they're placing their orders now, and they are 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. Three months ago, I can tell you our visibility run pretty much 2027. Today, it runs to 2028. That's a big part of the reason why we are creating this XPU platform as really the platform to plan to build up this 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 amount of consumption of tokens from those compute capacity we are giving them.

We have the benefit now of a lot of lead time, we're planning that. 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 power and connection into an infrastructure globally or through America, at least, that enables inference to be distributed through to consumers and enterprises throughout the country. We're just getting a lot of lead time.

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

Our revenue, our content per gigawatt will increase. Put it simply. Our content from the fact that our compute chip XPU will go up in price very dramatically, particularly when you not only put SRAM into it, sparse cores, you start putting embedding CPU cores into the same XPUs and making those chips basically multi-die with lots of HBM. The trajectory of content increase will go up. It just doesn't go up every month, every six months, or every quarter. It will follow one generation to the next, that the content will grow per gigawatt.

Thank you. I would now like to turn the call over to Ji Yoo, Head of Investor Relations, 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 2:00 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.