Okay, we're gonna get started. I'm Tim Arcuri. I'm the Semi and Semi-Equipment Analyst at UBS, and very pleased to have Teradyne here later in the afternoon and very pleased to have Greg Smith, who is the President and the CEO. So thanks, Greg.
Hey.
Great. Well, let's just start from a macro perspective, and I wanted to ask you about the big picture opportunity in SemiTest. And we hear all these massive deals. We hear OpenAI signing all these deals. We hear how fast data centers are growing. We see these great, you know, numbers from NVIDIA. And yet the semiconductor test team, the SoC team, is still gonna be $6-$6.5 billion this year. It seems very low relative to how, to, you know, how much semiconductor revenue's growing. So, I guess my question is sort of, how do you think about the opportunity and, like, how much the team can grow relative to how, you know, we're hearing all these semiconductor revenue growth opportunities?
I think we should probably talk about things we know and things we don't know. Things that we know is that there is a certain amount of committed data center capacity that's going in over the next few years, and that is gonna drive significant silicon growth year on year. The other thing that we know is that the silicon complexity is growing at a much faster rate in the data center than it is, than it has in other parts of the market. Then the last thing that we know is that the timeframe between, you know, like, a deal being announced and it actually having an impact in the market is a significant period of time, you know. People are very excited about new deals being inked, around, you know, new hyperscaler, ASIC programs, next-generation ASIC programs.
Those are all things that are gonna have an impact in 2027 and 2028. That's when it would really impact the test market. So I think, you know, you're, you're talking about, you know, like, "Oh, the TAM is only $6.5 billion." I'm kinda psyched that it's $6.5 billion now, and there is room to go up from here, that I think all of the equations are leading us towards this kind of sustained growth. And the last thing that's really exciting about the data center opportunity is, the pursuit of high-performance compute, sort of, tokens per watt or whatever metric you wanna use to measure sort of how much revenue you can get out of a data center. That is such a potent draw that people are pulling advanced technologies into the process very, very quickly.
And it is also a situation where you can end up with technologies coming into production that are at much lower yields than they have been in other device technologies. So you're in this situation where people are spending a lot of money to build out this capacity, but they're also really trying to see what they can do to maximize the output that they have of good parts. That's kind of the perfect recipe for higher spend on test because we can help people sort out the good ones from the bad ones when processes are immature.
Got it. And so I hear, quite often, I mean, obviously we know it's a duopoly, and the theory is that the duopoly has favored your competitor because they're more exposed to memory and compute, and you're more exposed to mobile. I think that's really changing, but I hear that a lot. So can you just talk about, like, what does that theory miss?
I think that the theory doesn't miss much from a historical perspective. If you look in the rearview mirror, incumbency was everything, you know, that if you had possession of a customer, the amount of energy that it would take to enter or disrupt that customer was sort of beyond what any customer would invest in. Now the difference is that for the main providers of compute for data centers, it's such a major part of their overall corporate strategy, and that's such a major part of the overall semiconductor economy that supply assurance now becomes a much more important factor than when you're talking about gaming chips. You know, if you're building gaming chips and that's a small single-digit percentage of total TSMC capacity, that's sort of one set of circumstances around your overall test strategy.
If, like, economic growth in the entire planet is dependent on your success in AI, that's a whole different story in terms of what you need in terms of supply assurance. So I think we've entered this era that for the large players in the data center, that supply chain resilience is increasingly important, and Teradyne is positioned to benefit from that. You know, I think that Advantest has done a great job aligning to the compute market for a long time, and they've reaped the benefit of that in the short term. But I think this importance of the compute market overall is such that these customers are going to be seeking alternatives, alternative solutions.
So you mentioned the risk, you know, the risk mitigation and dual sourcing and, you know, obviously the big GPU, you know, customers trying to do that across everything it buys. Do you think from a custom ASIC perspective, it's historically, like, you know, TPU, for example, those decisions have been made via the custom ASIC.
Mm-hmm.
Producer. You, however, are going more to the direct customer and saying, "Listen, you need to get more involved in this, and we have a better tester." So is the procurement decision on the ASIC side also changing as well?
I think over time it is migrating more towards the hyperscaler, this vertically integrated platform that's driving the design, and the power of the aggregator is reducing. That's certainly, like, I don't know if it's a trend, but that's the evidence that we've seen in the, you know, in the large-scale deployments that we've seen that, and by the way, it's not just around tester selection. What you'll see is that the hyperscaler, even if they have worked with a particular aggregator for multiple generations of parts, now they are looking to other aggregators as a way for them to provide assurance. So we believe that the ultimate decision-making power will be migrating to these hyperscalers, and so we think that's the most important place to prove our advantages.
You know, that doesn't mean that we aren't focused on spending time with those aggregators and to try and show them that we have a great way to ensure that they have the capacity that they need. But I think it's a more powerful argument to the hyperscalers 'cause they're the ones that are making these billion-dollar commitments on data centers that they need to get up.
So you think there are these pools of moats that they've had in the past where, you know, where your competitor has had a 100% share for the big GPU supplier, they've had a 100% share for TPU. These, the bulk of what's growing, they've had a 100% share. But would you say, I mean, obviously on the, you know, GPU side, they are trying to diversify, but also for TPU, I mean, do you think all these customers are gonna want dual source? And so, you know, you're the share gainer.
So I think you know the difference between the merchant GPU opportunity that we have and these other things that you're talking about is kind of how far down the road they are. At the end of the day, the same challenge that led a merchant GPU manufacturer to invite us to compete, which is you know wanting to be able to be sure that they could get the test capacity when they need the test capacity. I think that becomes even more important if you are not the most important customer for our competitor, you know, so if you are going to be the third or fourth priority, then you always have to be worried about who's gonna get in line in front of you. So I think there's one reason why a leading manufacturer of GPUs would do it.
There's another reason why a VIP might do it. But in general, it's all around making sure that you have multiple shots on goal to get the capacity that you need.
Great. So let's talk about that GPU opportunity you have.
Mm-hmm.
It seems like you're in the correlation phase now. From what I know about that, that's a win to even get to that point. And I would think that this would be a first, you know, first for your program and, you know, maybe a little less volume at first, but then you sort of get your foot in the door and the bigger, you know, data center stuff comes in the not-too-distant future. Is that fair?
Yeah. So I think to like lay it out, we've been working on this sort of qualification project for a little bit less than the last six months, and that project has three phases. First phase is, you know, conversion and offline development. The second phase is debug. The third phase is correlation and qualification. We are late in that third phase now. To your point, nothing terrible has happened so far, you know. Like, it's been. We've made good progress. We've been on schedule. We've had a great level of engagement with the customer. So we expect to succeed. We are unable to predict exactly the timing of when that will occur because the qualification process is iterative. You're trying to prove equivalence between two solutions.
And if there is an equivalence, it could be a problem with our solution, could be a problem with the incumbent solution, and frankly, it could be something that doesn't matter. And so each one of those has to be investigated as an engineering challenge and resolved. And once they're resolved, then the platform is qualified. What happens beyond that point is an interesting, like, there's a sort of a long-range set of events that will occur. The first is, as soon as we're qualified on a part, we would be able to capture incremental capacity against that specific device. We could also potentially, if there is a need for capacity on the incumbent platform on another part, we could backfill against that platform so that they could move capacity over. But it's gonna be a small incremental start because we just have this one part.
The other thing that happens when you're qualified is they give you more to do. So we'll begin other projects to do more conversions of parts that are much earlier in their life cycle. And those would be the things that could ramp to more significant volume. And that's probably back half of 2026. Longer term than that, the vision that we have is to help them get to what we're calling a tester-agnostic development flow. And that would mean that they're able to flip a switch and decide whether they put it on one platform or the other or even both, and then plan capacity against that, very late in the process. And we really like that outcome because then we're competing on a level playing field.
You know, it's a matter of differentiating on tester performance and reliability, customer service, time to market, yield, things where in other head-to-head competitions, we felt like we've done quite well.
They're $2 billion of the $6-$6.5 billion SoC TAM this year. So, I mean, even if you got 25% share, that's a big number for you. So if I told you that in 2027, let's say, just to pick a year, if I told you that you're gonna be 25% share of whatever their share of the TAM is in that year, would that be a disappointing number to you? Would you be okay with that? Or would you say, "Oh, I can do better than that"?
So, the two adjectives that you should probably take away is inevitable and incremental, right? That, I think we are going to gain share, but I think gaining share is going to take time because there is a broad range of parts. There is a broad ecosystem to bring those parts to market on the incumbent platform, and we are building that up. So if you were to tell me in 2025 I had 25% share of that, I'd be delighted. You know, I think that, you know, ultimately long term, what we've seen in other customers that do dual sourcing is that your share ends up in a 30%-70% range based on differentiation and customer satisfaction. It's probably gonna take us three or four years to get into that range to be competing on an even keel.
2027 is still on the earlier side of that.
Got it. Okay. Let's talk about another growth driver, which is Apple business for you. And how much visibility do you have there? Typically not much. They don't give you very much visibility. But the drivers are units, transistor density, and test times. And it seems like, and not just for that customer, but generally it seems like test times are going up because, you know, some of these wafer level packages. Finally, I think there's more aggressive shrink going on in mobile. So it seems like mobile could be a little bit better outlook for you next year than it's been the past couple of years. And would you agree with that? And how much does, like, a wafer level package, for example, how much does that increase test time?
Yeah. So, you know, I'll comment more sort of generally about the mobile ecosystem than around any specific customer. But I agree with your assessment that we're positioned for a more significant complexity increase next year. And that's both through adoption of two-nanometer process, enabling more, you know, more functions in the die, especially more AI processing TOPS in the die, and then also change in the memory packaging, the sort of the packaging technology around memory, for at least the premium tier. And the interesting thing about the change in memory technology is the reason that that is being done is to make the bus width bigger between the processor and the memory to open up memory bandwidth. Every single connection between the mobile processing die and the memory actually requires a tester resource to be connected to it.
We have this large installed base to test mobile processors. The fact that each one of those processors is gonna consume more tester resources means that you'd be able to test fewer of them at the same time. It's not like a huge difference, but even an incremental decrease, you know, like from six to five at the same time is a much larger jump in complexity than even the increase in transistors going from, you know, from 3 nm to 2 nm. So that's sort of two tailwinds. The things that we don't know is we don't know how pervasive this technology will be across a mobile phone product line. You know, so if it's just at the super premium tier and very low volume, then that's not gonna be enough to move the needle.
If it's across a broader range of products, then it could be a very big impact, and then the other thing that has been, like, forecasting has been sort of historically pretty bad is around unit volume, and the hard part of the unit volume for any of the non-Chinese smartphone makers is predicting what their share in China is gonna end up being, so I think that that's a potential anchor against it, but when you add it all together, I agree we're more optimistic about mobile in 2026 than we have been for the past couple of years, but it's kinda like we're a little afraid to dream the dream because there are these factors that we can't really measure.
Great. And then let me ask you about the third, at least, I mean, there's more than just three, but the third thing that I'm focused on is your opportunity in Cobots. And you are building a big manufacturing facility in the US to support a single customer. There's been some blogs. You're being qualified there. I mean, they have a lot of warehouses there. They could be quite big, you know, depending on how quickly it gets adopted. So can you talk about that and sort of just the general outlook for your robotics business?
Mm-hmm. So, first of all, the manufacturing facility that we are going to be building out in 2026 for Cobots in the U.S., that isn't like, that's certainly going to help us serve this new major customer. But there are many large customers in North America that want to procure from U.S. manufacturing. So there's a more general trend towards reshoring and procuring equipment that has been manufactured in the U.S. And so we wanted to do this not only for the major customer, for other big customers, and also because there's significant tariffs against products that are being imported into the U.S. So there's a bunch of reasons why it made sense for us to do our next capacity expansion for Cobots in the U.S. versus in Europe where we do our other manufacturing.
Now, against the large opportunity, the large customer that we have, it's in the e-commerce space. I agree with you that there is a large opportunity set that there are tons of distribution centers and warehouses that are slated to be automated through this technology. The thing that is uncertain in my mind is the rate at which that automation will be installed. In the past, most of the automation projects that this customer have done have been associated with like greenfield buildout, you know, so build a new distribution center and introduce a new kind of automation with it. This is a bit of a new thing for them where they're taking an existing process in a distribution center and changing it from a manual process to an automated process. They've planned an incremental path to get that done.
And it, you know, sort of the first wave happens in 2026, and then subsequent waves in North America and Europe and beyond are happening in 2027 and 2028. So we think that this has legs to grow in 2026 and 2027 and beyond.
If I took those three opportunities, the mobile opportunity, the robotics opportunity, and the GPU opportunity, and I said over the summation of 2026 and 2027, let's not take one year or the other. Over that period, which one of those three would you say would be the largest?
And what are my choices again? We got GPU.
GPU.
Yep.
Robotics.
Robotics.
And the mobile opportunity.
Mobile. So, GPU.
GPU.
Yeah. Because, in terms of percentage above baseline, the biggest opportunity is probably in robotics. But that is coming from a smaller base. And also in terms of an impact on earnings, our semiconductor business is much more efficient at turning revenue into EPS than our robotics business. So, you know, there's a lot of room to run in terms of robotics before it's gonna have a significant impact on results. The other thing is that GPU, the sort of the compute TAM is so huge that, you know, like a, you know, like you were saying, just one customer is kinda $2 billion this year. If that one customer grows by 20%, that's like bigger than our entire robotics business. So, a relatively small change or an incremental share gain in compute will have a really disproportionate positive effect on our results.
Makes sense. Great. Thank you. Let's. We haven't talked about memory yet. So, historically, you've not had much exposure for wafer test and DRAM, but now we have these new test insertions like stack tests for HBM, and the memory market seems to be really changing. So can you talk about how the market's changing? And maybe you can extend the answer to include HBM4E. You've taken a little bit of a different approach where you can reuse your tester and your competitor. You have to buy a new tester, so that's allowed you to take some share. So can you just talk about all that?
Sure. So, if you look into history, we have tended to focus our investments towards the final test markets. And the reason that we did that is, performance, the way that the world had worked historically was at the wafer level, it was kind of a commoditized test, you know, that you were just validating that the core of the memory worked. There wasn't a lot of ability to differentiate on the architecture of the tester or the performance of the tester. You were kinda just providing a commodity. In the final test, yield was dependent on signal integrity. Throughput was dependent on the efficiency of the architecture. So we were able to differentiate. So our investment priority was against the final packaged parts. HBM changed that because now there is actually a performance-oriented insertion at the wafer level.
That was the, you know, the reason that we developed the Magnum 7H to participate in that performance test. And that's been the part of the market that has been driving most of the growth in memory. And over the past, from the middle of 2024 to the end of 2025, we've gone from like 0% share of HBM performance test at the wafer level to like 50/50. And so that's been a great story of, you know, that we know how to do performance testing. We applied that at the wafer level, and we were able to achieve a lot of share gain.
Looking into the future, as HBM units expand, I would expect that is gonna be a growing market and something that we would expect to be able to compete quite well against Advantest, not only because of the asset life being able to be used for multiple generations, but also we also have it's more scalable, and we believe it's more performant in terms of delivering yield.
Just from a memory TAM point of view, how do you assess sort of the puts and takes on the memory TAM next year? I mean, it's been great the past few years, but could we see some digestion next year?
So I think 2025 was a digestion year that a lot of HBM capacity was put in place in 2024 that was occupied in 2025. So I think when you look at the TAM for memory going forward, there are more puts than takes that I think the HBM market is going to be increasing year on year. And right now you have a memory market that's like 70%-80% DRAM and 20%-30% flash. And there's certainly tightening in the flash market around SSD that could result in additional flash capacity coming online, and that would need test as well. So I think, you know, from a baseline perspective, the core of growth in next year is really around HBM and DRAM, DDR, LPDDR. But there is an upside opportunity against flash, depending on how desperate people get for SSDs and data centers.
Great. I wanted to ask you about the financial model. You're gonna give a new model next quarter. Your typical pattern would be to keep the same 2028 base year and to just refine the, you know, $4.5-$5.5 and a half revenue and $7-$9.50 EPS range to just, you know, tweak that range. Is that what we should expect, or do you wanna take a step back and take a different approach?
So I think, you know, we'll give you the full story in January. The things that we're wrestling with as we're trying to do this is, our practices around providing a business model, were really formed when the semiconductor market was far better behaved than it is right now. That if you look at that period from like 2010 out through 2019, it was just like there were little bumps along the way, but it was pretty smooth growth. And that, and the other thing is that predictability from quarter to quarter was actually pretty strong because the market was mobile dominated, and that was following a calendar period. What we're facing right now and what we're wrestling with is that the revenue is much lumpier. There are a few incredibly important customers.
They are putting in capacity in huge tranches, and their capacity needs do not follow a regular calendar. They follow sort of the device maturity and release schedule. So while we have a pretty good idea of how efficient a business model we would have at different revenues, it's much more difficult for us to predict how quickly we would achieve a particular revenue point. So I think we'll probably be talking in terms of expected aggregate growth rates. We will talk a lot about inherent uncertainty in the market, and try to make sure that people understand just how resilient our business model is across a range of revenue outcomes.
Got it, and maybe I'll ask about Technoprobe. I know you've been through the, that you took the, you know, position there. How much of a differentiator has that been so far in winning business with these VIPs?
So, you know, one of the parts of this, the deal that we had with TPI is, we had an internal group that developed device interfaces, and we actually sold that group to TPI, because the trend in the market was to integrate the device interface and the probe technology, and that has been great. You know, they have been a fantastic partner for business acquisition and to provide these device interfaces going forward. There’s another part of that partnership, which was really around the direction that the market was going. The direction that the market was going was around HBM performance test and around hybrid bonding and very dense connections and things that we thought would be opening up opportunities for us because we had a more scalable test platform.
The work on those projects is ongoing, but it is yet to have an impact on share acquisition. So what we've gotten so far, we've kinda gotten the old-fashioned way, from demonstrating the superiority of our tester, from a reliability and availability and performance perspective, this idea of, you know, like, one plus one equals three in terms of a partnership. Those are projects that are ongoing, and we would expect to start showing some benefits in 2026.
Okay. And then maybe just last question. So, the guidance for Q4 was, you know, obviously much better. Sounds like you think that what's strong in Q4 will persist into Q1. And I'm not asking you to guide next year, but it seems like next year maybe the sort of normal pattern of, you know, June being the strong quarter, it might be a bit different next year than it's been in the past.
It, yeah, like I feel confident saying it's gonna be different than the past. I'm not as confident saying what it will be. So I am, like at this point, I'm confident that 2026 is gonna be a good year. I believe that we are seeing demand solidifying throughout the year, but there is so much lumpiness in the demand. You know, we were, you know, in our last earnings call, we talked about uncertainty between Q4 and Q1 and even between, you know, Q1 and Q2. That kind of capacity on the edge is something that's gonna make sort of percentage quarter on quarter comparisons really tough to do.
Got it. Thank you for the time, Greg.
Hey, thank you.
Appreciate it.
Bye.