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Founded in 1961, Broadcom operates in two segments: One is focused on developing and supplying semiconductors, including chips for artificial intelligence. The other provides infrastructure, including Ethernet switching and routing and fiber-optic transmitter and receiver components. The company also offers components for Wi-Fi, Bluetooth, and global positioning systems. Its products are used in various applications in enterprise and data center networking, including artificial intelligence networking and connectivity. Google, Meta, ByteDance, and OpenAI are among Broadcom’s customers for its custom AI chips.

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Broadcom (AVGO): Company Profile, Stock Price, News, Rankings

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Broadcom

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Welcome to Broadcom's Inc. Second Quarter Fiscal Year twenty twenty five Financial Results Conference Call. At this time, for opening remarks and introductions, I would like to turn the call over to Ji Yu, Head of Investor Relations of Broadcom Inc.

Thank you, operator, and good afternoon, everyone. Joining me on today's call are Hock Tan, President and CEO Kirsten Spears, Chief Financial Officer and Charlie Kuaz, President, Semiconductor Solutions Group. Broadcom distributed a press release and financial tables after the market closed describing our financial performance for the second quarter of fiscal year twenty twenty five. If you did not receive a copy, you may obtain the information from the Investors section of the 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 comments, Hock and Kirsten will be providing details of our second quarter fiscal year twenty twenty five results, guidance for our third quarter of fiscal year twenty twenty five, 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 U. 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 will now turn the call over to Hock.

Thank you, Ji, and thank you, everyone, for joining us today. In our fiscal Q2 '20 '20 '5, total revenue was a record $15,000,000,000 up 20% year on year. This 20% year on year growth was all organic as q two last year was the first full quarter with VMware. Now revenue was driven by continued strength in AI semiconductors and the momentum we have achieved in VMware. Now reflecting excellent operating leverage, q two consolidated adjusted EBITDA was $10,000,000,000, up 35% year on year.

Now let me provide more color. Q2 Semiconductor revenue was $8,400,000,000 with growth accelerating to 17% year on year, up from 11% in Q1. And of course, driving this growth was AI semiconductor revenue of over 4,400,000,000.0 which was up 46% year on year and continues the trajectory of nine consecutive quarters of strong growth. Within this, Custom AI accelerators grew double digits year on year, while AI Networking grew over 170% year on year. AI networking, which is based on Ethernet, was robust and represented 40% of our AI revenue.

As a standards based open protocol, Ethernet enables one single fabric for both scale out and scale up, and remains the preferred choice by our hyperscale customers. Our networking portfolio of Tomahawk switches, Jericho routers and NICs is what's driving our success within AI clusters in hyperscalers. And the momentum continues with our breakthrough Tomahawk six switch just announced this week. This represents the next generation 102.4 terabits per second switch capacity. CommAut six enables clusters of more than hundred thousand AI accelerators to be deployed in just two tiers instead of three.

This flattening of the AI cluster is huge because it enables much better performance in training next generation frontier models through a lower latency, higher bandwidth, and lower power. Turning to XPUs or customer accelerators. We continue to make excellent progress on the multiyear journey of enabling our three customers and four prospects to deploy Customer AI accelerators. As we had articulated over six months ago, we eventually expect at least three customers to each deploy 1,000,000 AI accelerated clusters in 2027, largely for training their frontier models. And we forecast and continue to do so a significant percentage of these deployments to be custom XPUs.

These partners are still unwavering in their plan to invest despite this certain economic environment. In fact, what we've seen recently is that they are doubling down on inference in order to monetize their platforms. And reflecting this, we may actually see an acceleration of XPO demand into the back half of twenty twenty six to meet urgent demand for inference on top of the demand we have indicated from training. And accordingly, we do anticipate now our fiscal twenty twenty five growth rate of AI semiconductor revenue to sustain into fiscal twenty twenty six. Turning to our Q3 outlook.

As we continue our current trajectory of growth, we forecast AI Semiconductor revenue to be $5,100,000,000 up 60% year on year, which would be the tenth consecutive quarter of growth. Now turning to Non AI Semiconductors in Q2. Revenue of $4,000,000,000 was down 5% year on year. Non AI Semiconductor revenue is close to the bottom, has been relatively slow to recover, but there are bright spots. In Q2, Broadband, Enterprise Networking and Service Storage revenues were up sequentially.

However, industrial was down and as expected, wireless was also down due to seasonality. In Q3, we expect enterprise networking and broadband to continue to grow sequentially, but server storage, wireless and industrial are expected to be largely flat. And overall, we forecast non AI semiconductor revenue to stay around $4,000,000,000 Now let me talk about our Infrastructure Software segment. Q2 Infrastructure Software revenue of $6,600,000,000 was up 25% year on year, above our outlook of $6,500,000,000 As we have said before, this growth reflects our success in converting our enterprise customers from perpetual vSphere to the full VCF software stack subscription. Customers are increasingly turning to VCF to create a modernized private cloud on prem, which will enable them to repatriate workloads from public clouds while being able to run modern container based applications and AI applications.

Of our 10,000 largest customers, over 87% have now adopted VCF. The momentum from strong VCF sales over the past eighteen months since the acquisition of VMware has created annual recurring revenue or otherwise known as ARR growth of double digits in our core infrastructure software. In Q3, we expect infrastructure software revenue to be approximately $6,700,000,000 up 16% year on year. So in total, we are guiding Q3 consolidated revenue to be approximately $15,800,000,000 up 21% year on year. We expect Q3 adjusted EBITDA to be at least 66%.

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 $15,000,000,000 for the quarter, up 20% from a year ago. Gross margin was 79.4% of revenue in the quarter, better than we originally guided on product mix. Consolidated operating expenses were $2,100,000,000 of which $1,500,000,000 was related to R and D.

Q2 operating income of $9,800,000,000 was up 37% from a year ago, with operating margin at 65% of revenue. Adjusted EBITDA was $10,000,000,000 or 67% of revenue, above our guidance of 66%. This figure excludes $142,000,000 of depreciation. Now, a review of the P and L for our two segments. Starting with semiconductors.

Revenue for our semiconductor solutions segment was 8,400,000,000.0 with growth accelerating to 17% year on year, driven by AI. Semiconductor revenue represented 56% of total revenue in the quarter. Gross margin for our Semiconductor Solutions segment was approximately 69%, up 140 basis points year on year, driven by product mix. Operating expenses increased 12% year on year to 971,000,000 on increased investment in r and d for leading edge AI semiconductors. Semiconductor operating margin of 57% was up 200 basis points year on year.

Now moving on to infrastructure software. Revenue for infrastructure software of 6,600,000,000.0 was up 25% year on year and represented 44% of total revenue. Gross margin for infrastructure software was 93% in the quarter compared to 88% a year ago. Operating expenses were 1,100,000,000.0 in the quarter, resulting in infrastructure software operating margin of approximately 76%. This compares to operating margin of 60% a year ago.

This year on year improvement reflects our disciplined integration of VMware. Moving on to cash flow. Free cash flow in the quarter was 6,400,000,000.0 and represented 43% of revenue. Free cash flow as a percentage of revenue continues to be impacted by increased interest expense from debt related to the VMware acquisition and increased cash taxes. We spent 144,000,000 on capital expenditures.

Day sales outstanding were thirty four days in the second quarter compared to forty days a year ago. We ended the second quarter with inventory of $2,000,000,000 up 6% sequentially in anticipation of revenue growth in future quarters. Our days of inventory on hand were sixty nine days in Q2 as we continue to remain disciplined on how we manage inventory across the ecosystem. We ended the second quarter with $9,500,000,000 of cash and $69,400,000,000 of gross principal debt. Subsequent to quarter end, we repaid $1,600,000,000 of debt, resulting in gross principal debt of $67,800,000,000 The weighted average coupon rate and years to maturity of our $59,800,000,000 in fixed rate debt is three point eight percent and seven years, respectively.

The weighted average interest rate and years to maturity of our $8,000,000,000 in floating rate debt is five point three percent and two point six years, respectively. Turning to capital allocation. In q two, we paid stockholders two point eight billion of cash dividends based on a quarterly common stock cash dividend of $0.59 per share. In Q2, we repurchased $4,200,000,000 or approximately 25,000,000 shares of common stock. In Q3, we expect the non GAAP diluted share count to be approximately 4,970,000,000 shares, excluding the potential impact of any share repurchases.

Now, moving on to guidance. Our guidance for Q3 is for consolidated revenue of $15,800,000,000 up 21% year on year. We forecast semiconductor revenue of approximately $9,100,000,000 up 25% year on year. Within this, we expect Q3 AI semiconductor revenue of $5,100,000,000 up 60% year on year. We expect infrastructure software revenue of approximately $6,700,000,000 up 16% year on year.

For modeling purposes, we expect Q3 consolidated gross margins to be down approximately 130 basis points sequentially, primarily reflecting a higher mix of XPUs within AI revenue. As a reminder, consolidated gross margins through the year will be impacted by the revenue mix of infrastructure software and semiconductors. We expect Q3 adjusted EBITDA to be at least 66%. We expect the non GAAP tax rate for Q3 and fiscal year twenty twenty five to remain at 14%. And with this, that concludes my prepared remarks. Operator, please open up the call for questions.

Thank you. Our first question will come from the line of Ross Seymore with Deutsche Bank. Your line is open.

Hi, guys. Thanks for letting me ask a question. Hock, I wanted to jump onto the AI side and specifically some of the commentary you had about next year. Can you just give a little bit more color on the inference commentary you gave? And is it more the XPU side, the connectivity side, or both that's given you the confidence to talk about the growth rate that you have this year being matched next fiscal year?

Thank you, Ross. Good question. I think we're indicating that what we are seeing and what we have quite a bit of visibility increasingly is increased deployment of XPUs next year, much more than we originally thought. And hand in hand, we did, of course, more, more and more networking. So it's a combination of both.

Yeah. We're seeing much more inference now.

Thank you. One moment for our next question. And that will come from the line of Harlan Sur with JPMorgan. Your line is open.

Good afternoon. Thanks for taking my question and great job on the quarterly execution. Hock, good to see the positive growth inflection quarter over quarter, year over year growth rates in your AI business. As a team has mentioned, right, the quarters can be a bit lumpy. So if I smooth out kind of first three quarters of this fiscal year, your AI business is up 60% year over year. It's kind of right in line with your three year kind of SAM growth CAGR. Right? Given your prepared remarks and, knowing that your lead times remain at thirty five weeks or better, do you see the Broadcom team sustaining the 60% year over year growth rate exiting this year? And I assume that that potentially implies that you see your AI business sustaining the 60% year over year growth rate into fiscal twenty six, again, based on your prepared commentary, which again is in line with your SAM growth maker.

Is that kind of a fair way to think about the trajectory this year and next year?

Yeah. Harlan, that's a very insightful set of, analysis here, and that's exactly what we're trying to do here. Because six over six months ago, we gave you guys a point a year, 02/1927. As we come into the second now into the February, and we've improved visibility and updates we're seeing in the way our hyperscale partners are deploying data centers, AI classes. We are providing you more of some level of guidance, visibility, what we are seeing, how the trajectory of '26 might look like.

I'm not giving you any update on '27. We're just still establishing the update we have in '27, '6 months ago. But what we're doing now is giving you more visibility into where we're seeing '26 headed.

But is the framework that you laid out for us, like second half of last year, implies 60% kind of growth CAGR in your SAM opportunity. Is that kind of the right way to think about it as it relates to the profile of growth in your business this year and next year?

Thank you. One moment for our next question. And that will come from the line of Ben Reitzis with Melius Research. Your line is open.

Hey, how are doing? Thanks, guys. Hey, Hock. Networking AI networking was really strong in the quarter, and it seemed like it must have beat expectations. I was wondering if you could just talk about the networking in particular, what caused that?

And how much of that is your acceleration into next year? And when do you think you see Tomahawk kicking in as part of that acceleration? Thanks.

Well, I I think the network AI networking, as you probably would know, goes pretty hand in hand with deployment of AI accelerated clusters. It isn't. It doesn't deploy on the timetable that's very different from the way that accelerators get deployed, whether they are XPUs or GPUs. It does happen. And they're deployed a lot in scale out where Ethernet, of course, is the choice of protocol, but it's also increasingly moving into the space of what we all call scale up within those data centers, where you have much higher, more than we originally thought consumption or density of switches than you have in the scale out scenario.

It's in fact, the increased density in scale up is five to 10 times more than in scale out. And that's the part that kind of pleasantly surprised us, and which is why this past quarter q two, the AI networking portion continues at about 40% from when we reported a quarter ago for q one. And, at that time, I said I expect it to drop. It hasn't.

And and your thoughts on Tomahawk driving acceleration for next year and and when it kicks in?

Oh, Tomahawk six. Oh, yeah. That's extremely strong interest. Now we're not shipping, big orders or any orders other than basic proof of concepts out to customers, but there is tremendous demand for this new 102 terabit per second Tomahawk switches.

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

Hey, thanks and great results. I just wanted to ask maybe following up on the scale out opportunity. So today, I guess your main customer is not really using kind of an NVLink switch style scale up. I'm just kind of curious your visibility or the timing in terms of when you might be shipping a switch Ethernet scale up network to your customers.

Yeah. Well, scale up is very rapidly converting to Ethernet now. Very much so. It's I for our fairly narrow band of hyperscale customers, scale up is very much Ethernet.

Thank you. One moment for our next question. And that will come from the line of Stacy Rasgon with Bernstein. Your line is open.

Hi, guys. Thanks for taking my questions. Hock, I still wanted to follow-up on on that AI twenty twenty six question. I wanna just put some numbers on it just just to make sure I've got it right. So, if you you did 60% in the first three quarters of this year.

If you grow 60% year over year in q four, puts you at, like, I don't know, 5,800,000,000.0, something like 19 or 20,000,000,000 for the year. And then are you at are you saying you're gonna grow 60% in 2026, which would put you 30,000,000,000 plus in AI revenues for 2026? I just wanna make is that the math that you're you're trying to communicate to us directly?

I think you're doing the math. I'm giving you the trend. But I did answer that question, I think Harlan asked earlier. The the rate we are seeing, the now so far in fiscal twenty five and will presumably continue. We don't see any reason why it doesn't give an lead time visibility in '25.

What we're seeing today based on what we have visibility, on '26 is to be able to ramp up this AI revenue in the same trajectory. Yes.

So is is the SAM going up so is the SAM going up as well? Because now you have inference on top of training. So is the SAM SAM still 60 to 90, or is the SAM higher now high as as how as you see it?

I don't I'm not playing a SAM game here. I'm just giving a trajectory towards where we drew the line on 27 before. So I have no no response to is the same going up or not. Stop talking about same now. Thanks.

One moment for our next question. And that will come from the line of Vivek Arya with Bank of America. Your line is open.

Thanks for taking my question. I had a near and then a longer term question on the XCU business. So, Hawk, for near term, if your networking upsided in in q two and overall AI was in line, it means xCU was perhaps not as strong. So I I realize it's it's lumpy, but anything more to read into that, any product transition or or anything else? So just just a clarification there.

And then longer term, you know, you have outlined a number of additional customers that you're working with. What milestones should we look forward to? And what milestones are you watching to give you the confidence that you can now start adding that addressable opportunity into your 27 or 28 or other numbers? Like how do we get the confidence that these projects are going to turn into revenue in some, you know, reasonable timeframe from now? Thank you.

Okay. On the first part that you are asking, it's, you know, it's like you're trying to be you're trying to count how many angels on the head of a pin here. I mean, it's XP or or networking. Networking is hard, but that doesn't mean XP is any soft software. It's very much along the trajectory we expect it to be.

And that's that's no lumpiness. There's no softening. It's pretty much what we expect the trajectory to go so far and into next quarter as well and probably beyond. So we have a fairly it's a fairly, I guess, in our view, a fairly clear visibility on the short term trajectory. In terms of going on to '27, no, we are not updating any numbers here.

We, six months ago, we drew a sense for the size of the SAM based on, you know, million XP million GPU XPU clusters for three customers. And that's still very valid at that point that you'll be there. But and we have not provided any further updates here, nor are we intending to at this point. When we get a better visibility, clearer sense of where we are, and that probably won't happen until '26, we'll be happy to give an update to the audience. But right now though, in today's prepared remarks and answering a couple of questions, we have we are, as we are doing, as we have done here, we are intending to give you guys more visibility what we are seeing the growth trajectory in 'twenty six.

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

Yeah, good afternoon. Thank you for taking the question. I was hoping to follow-up on Ross's question regarding inference opportunity. Can you discuss workloads that are optimal that you're seeing for for custom silicon? And that over time, percentage of your XPU business could be inference versus training? Thank you.

I think there's no differentiation between training and inference in using, merchant accelerators versus customer accelerators. I think that all under the the whole premise behind going towards custom accelerators continues, which is it's not a matter of cost alone. It is that as custom accelerators get used and get developed on a on a road map with any particular hyperscaler, That's a learning curve, a learning curve on how they could optimize the way the algorithms on their large language models gets written and tied to silicon. And that ability to do so is a huge value added in creating, algorithms that can drive their LLMs to higher and higher performance, much more than, basically a segregation approach between hardware and the software. Is that you literally combine end to end hardware and software as they take that as they take that journey.

And it's a journey. They don't learn that in one year. Do it a few cycles, get better and better at it, and then lies the fairly the fundamental value in creating your own hardware versus using a third party merchant silicon that you are able to optimize your software to the hardware and eventually achieve way high performance than you otherwise could. And we see that happening.

Thank you. One moment for our next question. And that will come from the line of Karl Ackerman with BNP Paribas. Your line is open.

Yes. Thank you. Hock, you spoke about the the much higher content opportunity in scale up networking. I was hoping you could discuss how important is demand adoption for co package optics in achieving this five to 10x higher content for scale up networks? Or should we anticipate much of the scale up opportunity will be driven by Tomahawk and Thornex? Thank you.

I'm trying to decipher this question of yours. So let me try to answer it perhaps in a way I think you want me to clarify. First and foremost, I think most of what's scaling up, there are a lot of the scaling up that's going in, or as I call it, which means a lot of XPU or GPU to GPU interconnects. It's done on copper copper interconnects. And because, you know, the the size of the size of this in of this scale up cluster, still not that huge yet that you can get away with copper to using copper interconnects.

And they're still doing it. Mostly, they're doing it today. At some point soon, I believe, when you start trying to go beyond maybe 72 GPU to GPU interconnects, you may have to push towards a different protocol, by protocol mode at that different medium from copper to optical. And when we do that, yeah, perhaps then things like exotic stuff like co packaging might be for of of, silicon with optical might become relevant. But truly, what we really are talking about is that at some stage, as the clusters get larger, which means scale up becomes much bigger and you need to interconnect GPU or XPU to each other and scale up many more than just 72 or 100, maybe even 28.

You start going more and more. You want to use optical interconnects simply because of distance, and that's when optical will start replacing copper. And when that happens, the question is what's the best way to deliver on optical. And one way is co package optics, but it's not the only way. You can just simply use continue use perhaps pluggable at low cost optics, in which case then you can interconnect the bandwidth, the radix of a switch.

And our switch is now 512 connections. So you can now connect all these XPUs, GPUs, 512 for scale up phenomenon. And that was huge, but that that's when you go to optical. That's going to happen within my view a year or two, and we'll be right in the forefront of it. And it may be co package optics, which we are very much in development, but it's a lock in co package, or it could just be as a first step pluggable optics.

Whatever it is, I think the bigger question is when does it go from optical and from copper connecting GPU to GPU to optical connecting it. And the the stamp in that move will be huge. And it's not necessary co package optics, though that's definitely one path we are pursuing.

And one moment for our next question. And that will come from the line of Joshua Buchalter with TD Cowen. Your line is open.

Hey, guys. Thank you for taking my question. I realized it's a bit nitpicky, but I wanted to ask about gross margins in the guide. So your revenue implies sort of $800,000,000 increase, but gross profit up, I think, 400,000,000 to $450,000,000, which is kind of pretty well below corporate average fall through. Appreciate that semis is dilutive and and custom is probably dilutive within semis, but anything else going on with margins that we should be aware of?

And and how should we think about the margin profile of custom longer term as that business continues to scale and diversify? Thank you.

Yeah, we've historically said that the XPU margins are slightly lower, than the rest of the business other than wireless. And so there's really nothing else going on other than that. It's just exactly what I said, that the majority of it quarter over quarter, the 130 basis point decline is being driven by more XPUs.

You know, there are more moving parts here than your simple analysis pros here. And I think your simple analysis is totally wrong in that regard.

And 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, Og. I also wanted to ask about Scale Up, Hawk. So there's a lot of competing ecosystems. There's UA Link, which, of course, you left. And now there's the big, you know, GPU company, you know, opening up NVLink, and they're both trying to build ecosystems.

And there's an argument that you're an ecosystem of one. What would you say to that debate? Does does does opening up NVLink change the landscape? And sort of how do you view of your AI networking growth next year? Do you think it's gonna be primarily driven by scale up, or would still be pretty scale out heavy? Thanks.

It's you know, people do like to create platforms and new protocols and system. The fact of the matter is scale up. It can just be done easily, and it's currently available. It's open standards, open source Ethernet. Just as well just as well, you don't need to create new systems for the sake of doing something that you could easily be doing in, networking in Ethernet.

And so, yeah, I hear a lot of this interesting new protocols, standards that are trying to be created. And most of them, by the way, are proprietary, much as they like to call it otherwise. What is really open source and open standards is Ethernet. And we believe Ethernet will prevail as it does before for the last twenty years in traditional networking. There's no reason to create a new standard for something that could be easily done in transferring bits and bytes of data.

And one moment for our next question. And that will come from the line of Christopher Rolland with Susquehanna. Your line is open.

Thanks for the question. Yeah, my question is for you, Hock. It's kind of a bigger picture one here. And this kind of acceleration that we're seeing in AI demand, do you think that this acceleration is because of a marked improvement in ASICs or XPUs closing the gap on the software side at your customers? Do you think it's these require tokenomics around inference, test time compute driving that, for example?

What do you think is actually driving the upside here? And do you think it leads to a market share shift, faster than we were expecting towards XPU from GPU? Thanks.

Yeah. Interesting question. But no. None of the foregoing that you outlined. So it's simple.

The way inference has come out, very, very hot lately is, remember, we're only selling to a few customers, hyperscalers with platforms and LLMs. That's it. There are not that many. And and you we told you how many we have, and we haven't increased any. But what is happening is this all these hyperscalers and those with LLMs need to justify all the spending they're doing.

Doing training makes your frontier models smarter. That's no question. It's almost like science, research and science. Make your frontier models by creating very clever algorithm that that deep, consumes a lot of compute for training smarter. Training makes it smarter.

You want to monetize inference, and that's what's driving it. Monetize, I indicated in my prepared remarks, the drive to justify a return on investment, and a lot of the investment is training, and that return on investment is by creating use cases, a lot AI use cases, AI consumption out there through availability of a lot of inference. And that's what we are now starting to see among a small group of customers.

And one moment for our next question. And that will come from the line of Vijay Rakesh with Mizuho. Your line is open.

Yeah. Thanks. Hey, Hock. Just going back on the AI revenue side. I know you said fiscal twenty five kind of tracking to that up 60% ish growth.

If you look at fiscal twenty six, you have many new customers ramping a meta and probably, you have the four of the six hyperscalers that you have talked in the past. Would you expect that growth to accelerate into fiscal twenty six, above that, you know, kind of the 60% you have talked about?

You know, my my my prepared remarks, which I clarify, that the rate of growth we are seeing in 2025 will sustain into 2026 based on improved visibility and the fact that we're seeing inference coming in on top of the demand for training as the clusters get built up bigger and bigger still stands. I don't think we are getting very far by trying to pass through my words or data here. It's just a tricky thing. And we see that going from '25 into '26 as the best forecast we have at this point.

Got it. And and on the NVLink the NVLink fusion versus the scale up, do you expect that market to go the route of top of the rack where you've seen some move to the Ethernet side in in kind of scale out? Do you expect scale up to kind of go the same route? Thanks.

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