Thank you, Cherie, and good afternoon, everyone. Joining me on today's call are Hock Tan, President and CEO, Kirsten Spears, Chief Financial Officer, and Charlie Kawwas, President, Semiconductor Solutions Group.

Broadcom distributed a press release and financial tables after the market closed, describing our financial performance for the fourth quarter and fiscal year 2025. If you did not receive a copy, you may obtain the information from the Investors 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 Investors section of Broadcom's website. During the prepared remarks, Hock and Kirsten will be providing details of our fourth quarter and fiscal year 2025 results, guidance for our first quarter of 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 the specific 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 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'll now turn the call over to Hock.

Thank you, Ji. Thank you, everyone, for joining us today.

We just ended our Q4 fiscal '25, and before I get into details of that quarter, let me recap the year. In our fiscal 2025, consolidated revenue grew 24% year-over-year to a record $64 billion, and that's driven by AI semiconductors and VMware.

AI revenue grew 65% year-over-year to $20 billion, driving the semiconductor revenue for this company to a record $37 billion for the year. In our infrastructure software business, strong adoption of VMware Cloud Foundation, or VCF, as we call it, drove revenue growth of 26% year-on-year to $27 billion.

In summary, 2025 was another strong year for Broadcom, and we see the spending momentum by our customers for in AI continuing to accelerate in 2026. Now let's move on to the results of our fourth quarter 2025.

Total revenue was a record $18 billion, up 28% year-on-year, and above our guidance on better than expected growth in AI semiconductors as well as infrastructure software. Q4 consolidated adjusted EBITDA was a record $12.2 billion, up 34% year-on-year.

Let me give you more color on our two segments. In semiconductors, revenue was $11.1 billion, as year-on-year growth accelerated to 35%.

This robust growth was driven by AI semiconductor revenue of $6.5 billion, which was up 74% year-on-year. This represents a growth trajectory exceeding 10 times over the 11 quarters we have reported this line of business.

Our custom accelerator business more than doubled year-over-year as we see our customers increase adoption of XPUs, as we call those custom accelerators, in training their LLMs and monetizing their platforms through inferencing APIs and applications. These XPUs, I might add, are not only being used to train and inference internal workloads by our customers.

The same XPUs, in some situations, are being extended externally to other LLM peers, best exemplified at Google, where the TPUs used in creating Gemini are also being used for AI cloud computing by Apple, Cohere, and SSI as a as a sample. The scale at which we see this happening could be significant.

As you are aware, last quarter, Q3 '25, we received a $10 billion order to sell the latest TPU Ironwood racks to Anthropic. This was the our fourth customer that we mentioned.

In this quarter, Q4, we received an additional $11 billion order from this same customer for delivery in late 2026. That does not mean our other two customers are using TPUs.

In fact, they prefer to control their own destiny by continuing to drive their multiyear journey to create their own custom AI accelerators, or XPU racks, as we call them. I'm pleased today to report that during this quarter, we acquired a fifth XPU customer through a $1 billion order placed for delivery in late 2026.

Now moving on to AI networking, demand here has even been stronger as we see customers build out their data center infrastructure ahead of deploying AI accelerators. Our current order backlog for AI switches exceeds $10 billion as our latest 102 terabyte terabit-per-second Tomahawk 6 switch, the first and only one of its capability capability out there, continues to book at record rates.

This is just a subset of what we have. We have also secured record orders on DSPs, optical components like lasers, and PCI Express switches to be deployed all to be deployed in AI data centers.

All this components combined with our XPUs bring our total order on hand in excess of $73 billion today, which is almost half Broadcom's consolidated backlog of $162 billion. We expect this $73 billion in AI backlog to be delivered over the next 18 months.

In Q1 fiscal '26, we expect our AI revenue to double year-on-year to $8.2 billion. Turning to non-AI semiconductors, Q4 revenue of $4.6 billion was up 2% year-on-year and up 16% sequentially based on favorable wireless seasonality.

Year-on-year, broadband showed solid recovery. Wireless was flat, and all the other end markets were down as enterprise spending continued to show limited signs of recovery.

Accordingly, in Q1, we forecast non-AI semiconductor semiconductor revenue to be approximately $4.1 billion, flat from a year ago, down sequentially due to wireless seasonality. Let me now talk about our infrastructure software segment.

Q4 infrastructure software revenue of $6.9 billion was up 19% year-on-year, both and above our outlook of $6.7 billion. Bookings continue to be strong as total contract value booked in Q4 exceeded $10.4 billion versus $8.2 billion a year ago.

We ended the year with [cough] we ended the year with $73 billion of infrastructure software backlog, up from $49 billion a year ago. We expect renewals to be seasonal in Q1 and forecast infrastructure software revenue to be approximately $6.8 billion.

We still expect, however, that for fiscal '26, infrastructure software revenue to grow low-double-digits percentage. Here's what we see in 2026.

Directionally, we expect AI revenue to continue to accelerate and drive most of our growth and non-AI semiconductor revenue to be stable. Infrastructure software revenue will continue to be driven by VMware growth at low-double digits.

For Q1 '26, we expect consolidated revenue of approximately $19.1 billion, up 28% year-on-year. We expect adjusted EBITDA to be approximately 67% of revenue.

With that, let me turn the call over to Kirsten.

Thank you, Hock. Let me now provide additional detail on our Q4 financial performance.

Consolidated revenue was a record $18 billion for the quarter, up 28% from a year ago. Gross margin was 77.9% of revenue in the quarter, better than we originally guided on higher software revenues and product mix within semiconductors.

Consolidated operating expenses were $2.1 billion, of which $1.5 billion was research and development. Q4 operating income was a record $11.9 billion, up 35% from a year ago.

Now on a sequential basis, even as gross margin was down 50 basis points on semiconductor product mix, operating margin increased 70 basis points sequentially to 66.2% on favorable operating leverage. Adjusted EBITDA of $12.122 billion, or 68% of revenue, was above our guidance of 67%.

This figure excludes $148 million of depreciation. Now a review of the P&L for our two segments, starting with semiconductors.

Revenue for our Semiconductor Solutions segment was a record $11.1 billion, with growth accelerating to 35% year-on-year, driven by AI. Semiconductor revenue represented 61% of total revenue in the quarter.

Gross margin for our Semiconductor Solutions segment was approximately 68%. Operating expenses increased 16% year-on-year to $1.1 billion on increased investment in R&D for leading-edge AI semiconductors.

[cough] Semiconductor operating margin of 59% was up 250 basis points year-on-year. Now moving to infrastructure software, revenue for infrastructure software of $6.9 billion was up 19% year-on-year and represented 39% of total revenue.

Gross margin for infrastructure software was 93% in the quarter, compared to 91% a year ago. Operating expenses were $1.1 billion in the quarter, resulting in infrastructure software operating margin of 78%.

This compares to operating margin of 72% a year ago, reflecting the completion of the integration of VMware. Moving on to cash flow, free cash flow in the quarter was $7.5 billion and represented 41% of revenue.

We spent $237 million on capital expenditures. Days sales outstanding were 36 days in the fourth quarter, compared to 29 days a year ago.

We ended the fourth quarter with inventory of $2.3 billion, up 4% sequentially. Our days of inventory on hand were 58 days in Q4, compared to 66 days in Q3, as we continue to remain disciplined on how we manage inventory across the ecosystem.

We ended the fourth quarter with $16.2 billion of cash, up $5.5 billion sequentially on strong cash flow generation. The weighted average coupon rate and years to maturity of our gross principal fixed-rate debt of $67.1 billion is 4% and 7.2 years, respectively.

Turning to capital allocation, in Q4, we paid stockholders $2.8 billion of cash dividends based on a quarterly common stock cash dividend of 59 cents per share. In Q1, we expect the non-GAAP diluted share count to be approximately 4.97 billion shares, excluding the potential impact of any share repurchases.

Now let me recap our financial performance for fiscal year 2025. [cough] Our revenue hit a record $63.9 billion, with organic growth accelerating to 24% year-on-year.

Semiconductor revenue was $36.9 billion, up 22% year-over-year. Infrastructure software revenue was $27 billion, up 26% year-on-year.

Fiscal 2025 adjusted EBITDA was $43 billion and represented 67% of revenue. Free cash flow grew 39% year-on-year to $26.9 billion.

For fiscal 2025, we returned $17.5 billion of cash to shareholders in the form of $11.1 billion of dividends and $6.4 billion in share repurchases and eliminations. Aligned with our ability to generate increased cash flows in the preceding year, we are announcing an increase in our quarterly common stock cash dividend in Q1 fiscal 2026 to 65 cents per share, an increase of 10% from the prior quarter.

We intend to maintain this target quarterly dividend throughout fiscal '26, subject to quarterly board approval. This implies our fiscal 2026 annual common stock dividend to be a record $2.60 per share, an increase of 10% year-on-year.

I would like to highlight that this represents the 15th consecutive increase in annual dividends since we initiated dividends in fiscal 2011. The board also approved an extension of our share repurchase program, of which $7.5 billion remains, through the end of calendar year 2026.

Now moving to guidance, our guidance for Q1 is for consolidated revenue of $19.1 billion, up 28% year-on-year. We forecast semiconductor revenue of approximately $12.3 billion, up 50% year-on-year.

Within this, we expect Q1 AI semiconductor revenue of $8.2 billion, up approximately 100% year-on-year. We expect infrastructure software revenue of approximately $6.8 billion, up 2% year-on-year.

For your modeling purposes, we expect Q1 consolidated gross margin to be down approximately 100 basis points sequentially, primarily reflecting a higher mix of AI revenue. As a reminder, consolidated gross margins through the year will be impacted by the revenue mix of infrastructure software and semiconductors and also product mix within semiconductors.

We expect Q1 adjusted EBITDA to be approximately 67%. We expect the non-GAAP tax rate for Q1 and fiscal year 2026 to increase from 14% to approximately 16.5% due to the impact of the global minimum tax and shift in geographic mix of income compared to that of fiscal year 2025.

That concludes my prepared remarks. Operator, please open up the call for questions.

Thank you. Just wanted to clarify, Hock, you said $73 billion over 18 months for AI, that's roughly $50-ish billion plus for fiscal '26 for AI.

Just wanted to make sure I got that right. Then the main question, Hock, is that there is sort of this emerging debate about customer-owned tooling, your ASIC customers potentially wanting to do more things on their own.

How do you see your XPU content and share at your largest customer evolve over the next one or two years? Thank you.

To answer your first question, what we said is correct, that as of now, we have $73 billion of backlog in place secured of XPUs, switches, DSPs, lasers for AI data centers that we anticipate shipping over the next 18 months. Obviously, this is as of now.

We fully expect more bookings to come in over that period of time, and so don't take that 73 as that's the revenue we in that we ship over the next 18 months. Just saying we have that now, and that bookings has been accelerating.

Frankly, we see that bookings not just in XPUs, but in switches, DSPs, all the other components that go into AI data center. We have never seen bookings of the nature of that what we have seen over the past three months, particularly with respect to Tomahawk 6 switches.

This is one of the fastest growing products in terms of deployment that we ever seen of any switch product that we put out there. It is pretty pretty interesting, and partly because it's is the only one of its kind out there at this point at 102 terabit per second.

That's the kind that's exact product needed to expand the clusters of the latest GPU and XPUs out there. That's great.

As far as what is the future as XPU, as your broader question, my answer to you is no is don't follow what you hear out there as gospel. It's a trajectory.

It's a multiyear journey. Many of many of the players and not too many players doing LLMs wants to do their own custom AI accelerator for very good reason.

You can put in hardware what if you use a general-purpose GPU, you can only do in software and kernels in software. You can achieve, performance-wise, so much better in the custom, purpose-designed, hardware-driven XPU.

We see that in the TPU, and we see that in all the accelerators we are doing for other customers, much much better in areas of sparse core, training, inference, reasoning, all that stuff. Now, will that mean that over time they all want to go do it themselves?

Not necessarily. In fact, because the technology in silicon keeps updating, keeps evolving.

If you are an LLM player, where do you put your resources in order to compete in this space, especially when you have to compete at the end of the day against merchant GPU, who are not slowing down in their rate of evolution? I I I see that as this concept of customer tooling is an overblown hypothesis, which, frankly, I don't think will will happen.

Thank you.

Hi, thanks for letting me ask the question. Hock, I wanted to go to something you touched on earlier about the TPUs going a little bit more to a merchant go-to-market to other customers.

Do you believe that's a substitution effect for customers who otherwise would have done ASICs with you, or do you think it's actually broadening the market? What are kind of the financial implications of that from your perspective?

That's a very good question, Ross. What we see right now is the most obvious move it does is it goes the people who use a TPU, the alternative is GPUs, merchant basis.

That's the most common thing that happens. Because to do that substitution for another custom, that's different.

To make a investment in custom accelerator is a multiyear journey, is a strategic, directional thing. It's not necessarily a very transactional or short-term move.

Moving from GPU to TPU is a transactional move. Going into AI accelerator of your own is a long-term, strategic move, and nothing would deter you from that to continuing to make that investment towards that end goal of successfully creating and deploying your own custom AI accelerator.

That's the motion we see.

Thank you.

Morgan. Good afternoon.

Thanks for taking my question, and congratulations on the strong results, guidance, and execution, Hock. Again, I just want to sort of verify this, right?

You talked about total AI backlog of $73 billion over the next six quarters, right? This is just a snapshot of your order book right now.

Given your lead times, I think customers can and still will place orders for AI in quarters four, five, and six. As time moves forward, that backlog number for more shipments in second half of '26 will probably still go up, right?

Is that the correct interpretation? Then, even with a strong and growing backlog, right, the question is, does the team have 3-nanometer, 2-nanometer wafer supply, CoWoS, substrate, HBM supply commitments to support all of the demand in your order book?

I know one of the areas where you are trying to mitigate this is in advanced packaging, right? You're bringing up your Singapore facility.

Can you guys just remind us what part of the advanced packaging process the team is focusing on with the Singapore facility? Thanks.

Thanks. To answer your first, simpler question, Harlan, [laughter] you're right.

You can say that 73 billion is the backlog we have today to ship over the next six quarters. You might also say that, and given our lead time, we expect more orders to be able to be absorbed into our backlog for shipments over the next six quarters.

Take it that we expect a minimum revenue, one way to look at it, of $73 billion over the next six quarters, but we do expect much more as more orders come in for shipments within that next six quarters. See, our lead time, depending on the particular product it is, can be anywhere from six months to a year.

With respect to supply chain is what you're asking, critical supply chain on silicon Yes. and packaging,

Yes.

That's an interesting challenge that we have been addressing constantly and continue to. With the strength of the demand and the need for more innovative packaging, advanced packaging, because you're talking about multichips in creating every custom accelerator now, the packaging becomes a very interesting and technical challenge.

Building our Singapore fab is to really talk about partially insourcing those advanced packaging. We believe that we have enough demand, we can literally insource from the viewpoint of not just costs, but in the viewpoint of supply chain security and delivery.

We're building a fairly substantial facility for advanced packaging in Singapore, as you indicated, purely for that purpose, to address the advanced packaging side. Silicon-wise, no, we go back to the same precious source in Taiwan, TSMC.

We keep going for more and more capacity in 2-nanometers, 3-nanometers, and so far, we do not have that constraint. Time will tell as we progress and as our backlog builds up.

Thank you, Hock.

Hey, good afternoon. Thanks for taking my question.

I wanted to ask with the original $10 billion deal, you talked about a rack sale. With the follow-on order, as well as the fifth customer, can you just maybe describe how you're going to deliver those?

Is it an XPU or is it a rack? Then maybe you can kind of just walk us through the math and kind of what the deliverable is.

Obviously, Google uses own networking, I'm kind of curious, too, would it be a copy exact of what Google does, now that you can talk to it to name, or would you have your own networking in there, as well? Thanks.

That's a very complicated question, Blayne. Let me tell you what it is.

It's a system sale. Hock about that?

It's a real system sale. We have so many components beyond XPUs, the custom accelerators, in any AI system used by hyperscalers, that, yeah, we believe it begin to make sense to do it as a system sales and be fully responsible for the entire system or rack, as you call it.

I think people are understanding it as a system sale better. On this customer number four, we are selling it as a system with our key components in it.

That's no different than selling a chip. We certify, and final ability to run as part of the whole selling process.

Thanks, Hock.

Hi, guys. Thanks for taking my question.

I wanted to touch on gross margins and maybe it feeds into a little bit the prior question. I understand why the AI business is somewhat dilutive to gross margins.

We have the HBM pass-through and then presumably with the system sales, that will be more dilutive. You've hinted at this in the past, but I was wondering if you could be a little more explicit.

As this AI revenue starts to ramp, as you start to get system sales, how should we be thinking about that gross margin number? Say, if we're looking out four quarters or six quarters, is it low 70s?

Could it start with a 6 at the corporate level? I guess I'm also wondering, I understand how that comes in, but what about the operating margins?

Do you think you get enough operating leverage on the OpEx side to keep operating margins flat, or do they need to come down, as well?

I'll let Kirsten give you the details, but enough for me to broadly, high-level explain to you, Stacy. Good question.

Phenomenal is you don't see that impacting us right now, and we are already started that process of some system sales. You don't see that in our numbers, but it will.

We have said that openly, the AI revenue has a lower gross margin than obviously, the rest of our business, including software, of course. We expect the rate of growth as we do more and more AI revenue to be so much that we get the operating leverage on our operating spending that operating margin will deliver dollars that are still a high level of growth from what it has been.

We expect operating leverage to benefit us at the operating margin level even as gross margin will start to deteriorate high level.

No, I think Hock said that fairly. The second half of the year, when we do start shipping more systems, the situation is straightforward.

We'll be passing through more components that are not ours, think of it similar to the XPUs, where we have memory on those XPUs and we're passing through those costs. We'll be passing through more costs within the rack, and so those gross margins will be lower.

However, overall, the way Hock said it, gross margin dollars will go up. Margins will go down.

Operating margins, because we have leverage, operating margin dollars will go up, but the margin itself as a percentage of revenues will come down a bit. We'll guide closer to the end of the year for that.

Got it. Thank you, guys.

Good afternoon, and thanks for taking my question. Hock was wondering if you might care to calibrate your expectations for AI revenue in fiscal '26 a little bit more closely.

I believe you talked about acceleration in fiscal '26 off of the 65% growth rate you did in fiscal '25, and then you're guiding to 100% growth for Q1. I'm just wondering if the Q1 is a good jumping-off point for the growth rate you'd expect for the full year, or something maybe a little bit less than that?

Then maybe if you could separately clarify whether your $1 billion of orders for the fifth customer is indeed OpenAI, which you made a separate announcement about? Thank you.

Wow, there's a lot of question here. Let me start off with '26.

Our backlog is very dynamic these days, as I said, and it is continuing to ramp up. You're right, we originally six months ago said, maybe year-on-year AI revenues would grow in '26 60%, 70%.

Q1, we double. Q1 '26, today, we're saying it's double.

We're looking at it because fresh orders keeps coming in, and we give you a milestone of where we are today, which is $73 billion of backlog to be shipped over the next 18 months. We do fully expect, as I answered the earlier question, for that $73 billion over the 18 months to keep growing.

Now, it's a moving target, it's a moving number as we move in time, but it will grow. It's hard for me to pinpoint what '26 is going to look like precisely, I'd rather not give you guys any guidance, and that's why we don't give you guidance, but we do give it for Q1.

Give it time, we'll give it for Q2. You're right, to us, is it an accelerating trend?

My answer is, it's likely to be an accelerating trend as we progress through '26. Hope that answers your question.

Yes, thank you.

Hey, guys. Thanks a lot.

Hey, Hock. I wanted to ask, I'm not sure if the last caller said something on it, but I didn't hear it in the answer, about the OpenAI contract.

It's supposed to start in the second half of the year and go through 2029 for 10 gigawatts. I'm going to assume that that's the fifth customer order there, and I was just wondering if you're still confident in that being a driver.

Are there any obstacles to making that a major driver, and when you expect that to contribute and your confidence in it? Thanks so much, Hock.

You didn't hear that answer from my last caller, Jim's question, because I didn't answer it. [laughter] I did not answer it, and I'm not answering it, either.

It's a fifth customer, and it's a real customer, and it will grow. They are on their multiyear journey to their own XPUs, and let's leave it at that.

As far as the OpenAI view that you have, we appreciate the fact that it is a multiyear journey that will run through '29, as our press release with OpenAI showed, 10 gigawatts between '26 to more like '27, '28, '29. Ben, not '26.

It's more like '27, '28, '29, 10 gigawatts. That was the OpenAI discussion.

I call it an agreement, an alignment of where we're headed with respect to a various respected and valued customer, OpenAI. We don't expect

Oh, that's really interesting.

We do not expect much in '26.

Thanks for clarifying that. That's really interesting.

Appreciate it.

Good afternoon. Thank you for taking the question.

I guess, Hock, I wanted to talk about custom silicon, and maybe speak to how you expect content to grow for Broadcom generation to generation. As part of that, your competitor announced CPX offering, essentially an accelerator for massive context windows.

I'm curious if you see it broadening opportunity for your existing five customers to have multiple XPU offerings. Thanks so much.

Thank you. No, yeah, you hit it right on.

The nice thing about a custom accelerator is you try not to do one size fits all and generationally. Each of these five customers now can create their version of an XPU, custom accelerator, for training and inference, and basically it's almost two parallel tracks going on almost simultaneously for each of them.

I'll have plenty of versions to deal with. I don't need to create any more version.

We've got plenty of different content out there just on the basis of creating this custom accelerators. By the way, when you do custom accelerators, you tend to put more hardware in that are unique, differentiated versus trying to make it work on software and creating kernels into software.

I know, that's very tricky, too. Think about the difference where you can create in hardware those sparse core data routers versus the dense matrix multipliers all in one same chip.

That's just one example of what creating custom accelerators is letting us do. Or for that matter, a variation in how much memory capacity or memory bandwidth for the same customer, from chip to chip, just because even in inference, you want to do more reasoning versus decoding versus something else, like prefill.

You literally start to create different hardware for different aspect of how you want to train or inference and run your workloads. That's a very fascinating area, and we are seeing a lot of variations and multiple chips for each of our customers.

Thank you.

Hock and team, first of all, congratulations on some pretty stunning numbers. I've got an easy one and a more strategic one.

The easy one is your guide in AI, Hock and Kirsten, is calling for almost $1.7 billion of sequential growth. I was curious, maybe talk about the diversity of the growth between the three existing customers.

Is it pretty well spread out, all of them growing, or is one sort of driving much of the growth? Then, Hock, strategically, one of your competitors bought a photonic fabric company recently.

I was curious about your take on that technology, and if you think it's disruptive or you think it's just gimmickry at this point in time? [laughter]

I like the way that you address the question to me. You're almost hesitant.

Thank you. I appreciate that.

[laughter] But on your first part, yeah, we're driving growth, and it begin to feel like this thing never ends. It's a real mixed bag of existing customers and on existing XPUs, and a big part of it is XPUs, what we're seeing.

That's not to slow down the fact that, as I indicated in my remarks and commented on, the demand for switches, not just Tomahawk 6, Tomahawk 5 switches, the demand for our latest 1.6-terabit-per-second DSPs that enables optical interconnects for scale-out, particularly, it's just very, very strong. By extension, demand for the optical components like lasers, PIN diodes, just going nuts.

All that come together. Now, all that is lesser dollars when it comes to XPUs, as you probably guess.

To give you a sense, maybe let me look at it on a backlog side. Of the $73 billion of AI revenue backlog over the next 18 months that I talk about, maybe $20 billion of it is everything else.

The rest is XPUs. Hope that gives you a sense for what the mix is.

That's It does. The rest is still $20 billion, that's not small by any means.

We value that. When you talk about your next question of silicon photonics and as a means to create basically much better, more efficient, lower-power interconnects in not just scale-out, but hopefully scale-up, yeah, I could see a point in time in the future when silicon photonics matters as the only way to do it.

We're not quite there yet, but we have the technology, and we continue to develop the technology even as each time we develop it first for 400-gigabit bandwidth, going on to 800-gigabit bandwidth, not ready for it yet. We have the product, and we're now doing it for 1.6-terabit bandwidth to create silicon photonics switches, silicon photonics interconnects.

Not even sure it will get fully deployed because our engineers and the peers we have out there will somehow try to find a way to still try to do scale-up within a rack in copper as long as possible, and in scale-out in pluggable optics. The final straw is when you can't do it well in pluggable optics, and of course, when you can't do it even in copper, then you're right, you go to silicon photonics.

It will happen, and we're ready for it, just saying not anytime soon.

Thank you, Hock.

Thank you. Hock, could you speak to the supply chain resiliency and visibility you have with your key material suppliers, particularly CoWoS, as you not only support your existing customer programs, but the two new custom compute processors that you announced inter-quarter?

I guess what I'm to get at is you also happen to address a very large subset of networking and compute AI supply chains. You've talked about record backlog.

If you were to pinpoint some of the bottlenecks that you have, areas that you're aiming to address and mitigate from supply chain bottlenecks, what would they be, and how do you see that ameliorating into '26? Thank you.

It's across the board typically. We are very fortunate in some ways that we have the product technology and the operating business lines to create multiple key leading-edge components that enables today's state-of-the-art AI data centers.

Our DSP, as I said earlier, is now at 1.6 terabits per second. [cough] That's the leading edge.

Connectivity chip for bandwidth for the top of the heap, XPU, and even GPU, and we intend to be that way. We have the lasers, EMLs, VCSELs, CW lasers that goes with it.

It's fortunate that we have all this, and the key active components that go with it. We see it very early, and we expand the capacity as we do the design to match it.

This is a long answer to what I'm trying to get at, which is, I think we are, of any of this data center suppliers of the system racks, not counting the power, the power shell, and all that—now that starts to get beyond us on the power shell and the transformers and the gas turbines—if you just look at the racks, the systems on AI, we probably have a good handle on where the bottlenecks are because sometimes we are part of the bottlenecks, which we then work to get to resolve. We feel pretty good about that through 2026.

Thank you.

Hi, thanks for the question. Just first a clarification, and then my question.

Sorry to come back to this issue, but if I understand you correctly, Hock, I think you were saying that OpenAI would be a general agreement, it's not binding, maybe similar to the agreements with both NVIDIA and AMD. Then secondly, you talked about flat non-AI semiconductor revenue.

Maybe what's going on there? Is there still an inventory overhang, and what do we need to get that going again?

Do you see growth eventually in that business? Thank you.

On the non-AI semiconductor, we see broadband literally recovering very well. We don't see the others.

No, we see stability. We don't see a sharp recovery that is sustainable yet.

I guess give it a one a couple more quarters. We don't see any further deterioration in demand, and it's more I think maybe the AI is sucking the oxygen a lot out of enterprise spending elsewhere and hyperscalers spending elsewhere.

We don't see it getting any worse. We don't see it recovering very quickly, with the exception of broadband.

That's a simple summary of non-AI. With respect to OpenAI, no, without diving into deep, I'm just telling you what that 10-gigawatt announcement is all about.

Separately, the journey with them on their custom accelerator progresses at a very advanced stage and will happen very, very quickly and will have a committed element to this whole thing. What I was articulating earlier was the 10-gigawatt announcement.

That 10-gigawatt announcement is an agreement to be aligned on developing 10 gigawatts for OpenAI over '27 to '29 time frame. That's it.

That's different from the XPU program we're developing with them.

I see. Thank you very much.

Great. Thank you very much.

If you have 21 million billion of rack revenue in the second half of '26, I guess do we stay [cough] at that run rate beyond that? Are you going to continue to sell racks, or does that type of business mix shift over time?

I'm really just trying to figure out the percentage of your 18-month backlog that's actually full systems at this point.

It's interesting question. That question basically comes to how much compute capacity is needed by our customers over the next, as I say, over a period beyond 18 months.

Your guess is probably as good as mine based on what we all know out there, which is really what relates to. If they need more, then you see that continuing even larger.

If they don't need it, then probably it won't. As of what we are trying to indicate is that's the demand we are seeing over that period of time right now.

Thank you.

Thank you, operator. This quarter, Broadcom will be presenting at the New Street Research Virtual AI Big Ideas Conference on Monday, December 15, 2025.

Broadcom currently plans to report its earnings for the first quarter of fiscal year 2026 after close of market on Wednesday, March 4th, 2026. A public webcast of Broadcom's earnings conference call will follow at 2:00 p.m.

Pacific. That will conclude our earnings call today.

Thank you all for joining. Operator, you may end the call.