Cadence Design Systems, Inc. (NASDAQ:CDNS) Q3 2025 Earnings Call Transcript

Cadence Design Systems, Inc. (NASDAQ:CDNS) Q3 2025 Earnings Call Transcript October 27, 2025

Cadence Design Systems, Inc. beats earnings expectations. Reported EPS is $1.93, expectations were $1.79.

Operator: Ladies and gentlemen, good afternoon. My name is Abby, and I’ll be your conference operator today. At this time, I would like to welcome everyone to the Cadence Third Quarter 2025 Earnings Conference Call. [Operator Instructions] Thank you. And I will now turn the call over to Richard Gu, Vice President of Investor Relations for Cadence. Please go ahead.

Richard Gu: Thank you, operator. I would like to welcome everyone to our third quarter of 2025 earnings conference call. I’m joined today by Anirudh Devgan, President and Chief Executive Officer; and John Wall, Senior Vice President and Chief Financial Officer. The webcast of this call and a copy of today’s prepared remarks will be available on our website, cadence.com. Today’s discussion will contain forward-looking statements, including our outlook on future business and operating results. Due to risks and uncertainties, actual results may differ materially from those projected or implied in today’s discussion. For information on factors that could cause actual results to differ, please refer to our SEC filings, including our most recent Forms 10-K and 10-Q, CFO commentary and today’s earnings release.

All forward-looking statements during this call are based on estimates and information available to us as of today, and we disclaim any obligation to update them. In addition, all financial measures discussed on this call are non-GAAP unless otherwise specified. The non-GAAP measures should not be considered in isolation from or as a substitute for GAAP results. Reconciliations of GAAP to non-GAAP measures are included in today’s earnings release. [Operator Instructions] Now I’ll turn the call over to Anirudh.

Anirudh Devgan: Thank you, Richard. Good afternoon, everyone, and thank you for joining us today. Cadence delivered excellent results for the third quarter of 2025, with strong operational and financial performance across all product categories and geographies as we continued the disciplined execution of our strategy. Bookings exceeded our expectations with backlog growing to over $7 billion, underscoring our continued technology leadership and reaffirming Cadence as the trusted partner enabling customer success. Given the ongoing strength of our business, we are raising our full year outlook to approximately 14% revenue growth and 18% EPS growth. John will provide more details on our financials shortly. The accelerating AI megatrend is fueling an unprecedented wave of design activity across industries ranging from hyperscaler infrastructure to fast-growing physical AI realm of autonomous driving, drones and robotics to the emerging domain of sciences AI.

As AI drives exponential design complexity and new system architectures, Cadence is uniquely positioned to capture this generational opportunity with a differentiated and comprehensive portfolio spanning EDA, IP, 3D-IC, PCB and system analysis. The Cadence.Ai portfolio embodies our strategy of design for AI and AI for design, empowering customers to build out the global AI infrastructure, while we infuse AI into our own products to deliver breakthrough automation and productivity. With deep partnerships across AI innovators, foundries and system leaders and a comprehensive chip-to-systems portfolio, Cadence is driving transformative PPA and productivity gains, positioning us well for sustained growth in the AI era. In Q3, we meaningfully expanded our partnership with Samsung through a wide-ranging proliferation of our core EDA software as well our system software across PCB, advanced packaging and system analysis.

We also deepened our long-standing partnership with a leading semiconductor company in Q3 through a broad proliferation of our core EDA, IP and systems portfolio and are closely collaborating on next-generation agentic AI EDA solutions. We expanded our long-standing partnership with TSMC to power next-gen AI flows supporting TSMC’s N2 and A16 technologies. Our Integrity 3D-IC solution provides comprehensive support for the latest TSMC 3DFabric die-stacking configurations. And our design-in-ready IP, including HBM4 and LPDDR6 on N3P-enabled next-generation AI infrastructure. At TSMC’s OIP conference, Broadcom highlighted Integrity 3D-IC full flow deployment success for hyperscaler high-capacity ASICs. Our IP business maintained strong momentum in Q3, driven by global accelerating IP demand and increasing customer proliferation of our expanding IP portfolio.

Our profitable, scalable IP strategy focused on AI, HPC and automotive verticals positions us well for continued growth. Increasing complexity of interconnect protocols driven by AI and chiplet architectures, along with new foundry opportunities are providing strong tailwinds to our IP business. Bookings were strong and tracked ahead of our expectations. Our design IP portfolio secured several competitive wins at top AI and memory customers. For instance, we won a highly competitive engagement at a marquee memory company that embraced our HBM4 and DDR5 IP for its new AI design. The recently completed acquisition of the Arm Artisan Foundation IP further augments our design IP portfolio with standard cell libraries, memory compilers and IOs optimized for advanced node at the leading foundries.

Our Tensilica audio and vision DSPs and Neo AI accelerator NPUs scored multiple design wins with leading customers in U.S. and Asia for mobile, automotive and data center verticals. Our core EDA business delivered strong results, driven by growing adoption of our AI-driven design and verification solutions. In digital, Cadence Cerebrus AI Studio, the industry’s first agentic AI, multi-block, multiuser design platform continues to deliver unparalleled PPA and productivity benefits. Samsung U.S. taped out a SF2 design using Cadence Cerebrus AI Studio to achieve a 4x productivity improvement. In another instance, Samsung used Cadence Certus, Tempus and Innovus to rapidly close and sign off a multibillion instance AI design on SF4, with 22% power reduction and first-pass silicon success.

Our Virtuoso Studio and Spectre platforms saw strong momentum, with their AI-driven features and workflows gaining rapid traction as the customers leverage the automated design migration and optimization capabilities. Our hardware verification platforms have become the de facto choice for AI designs, offering industry-leading performance, capacity and scalability. Hardware had a record Q3 with several significant expansions, especially at AI and HPC customers. We deepened our overall collaboration with OpenAI, as they expanded their commitment to our Palladium emulation platform in Q3. Verisium SimAI saw growing adoption as it delivered dramatic debug productivity, test bench efficiency and accelerated coverage closure. NVIDIA, Samsung and Qualcomm, all presented SimAI success stories at CadenceLIVE India, highlighting 5x to 10x improvement in verification throughput.

Our system design and analysis business achieved another solid quarter, driven by expanding set of innovative solutions and growing adoption across a broadening customer base. In Q3, we significantly expanded our Cadence Reality Digital Twin Platform library, with NVIDIA DGX SuperPOD model and DGXGB200 systems to accelerate AI data center deployment and operations. Three major memory providers significantly increased their clarity and security usage as they transition to a full Cadence flow for advanced IC packaging, displacing competitive solutions. BETA CAE continued its momentum with multiple competitive displacements, underscoring its accuracy and performance advantages, including a significant competitive win at a large Tier 1 automotive company in China.

In Q3, Infineon Technologies standardized its PCB design workflow on the Cadence AI-driven Allegro X platform for their future designs. Last month, we signed a definitive agreement to acquire Hexagon’s D&E business, including its MSC software business to bring industry-leading structural analysis and multi-body dynamics technologies to Cadence. Complementing our multiphysics portfolio, this will accelerate our expansion in SDA and put us at the forefront in unlocking new opportunities across automotive, aerospace, industrial and the rapidly emerging world of physical AI. In summary, I’m pleased with our Q3 results and the strong momentum across our businesses. The AI era offers massive market opportunities and through the co-optimization of our entire portfolio with AI and accelerated computing, Cadence is uniquely positioned to be the trusted partner to deliver AI-centric transformational solutions across multiple industries.

Now I will turn it over to John to provide more details on the Q3 results and our updated 2025 outlook.

John Wall: Thanks, Anirudh, and good afternoon, everyone. I’m pleased to report that Cadence delivered strong results for the third quarter of 2025 with broad-based momentum across all our businesses. We exceeded our guidance for Q3 revenue, operating margin and EPS and are raising the full year outlook across these key metrics. With the updated outlook and at the midpoint, we now expect our 2025 revenue to grow approximately 14% year-over-year on track to achieve double-digit growth across all our product categories for the year. Third quarter bookings were strong, resulting in a backlog of $7 billion. Here are some of the financial highlights from the third quarter, starting with the P&L. Total revenue was $1.339 billion. GAAP operating margin was 31.8% and non-GAAP operating margin was 47.6%.

And GAAP EPS was $1.05, with non-GAAP EPS $1.93. Next, turning to the balance sheet and cash flow. Cash balance at quarter end was $2.753 billion, while the principal value of debt outstanding was $2.5 billion. Operating cash flow was $311 million. DSOs were 55 days, and we used $200 million to repurchase Cadence shares. Before I provide our updated outlook, I’d like to highlight that it contains the usual assumption that export control regulations that exist today remain substantially similar for the remainder of the year. With that in mind, for Q4, we now expect revenue in the range of $1.405 billion to $1.435 billion, GAAP operating margin in the range of 32.5% to 33.5%, non-GAAP operating margin in the range of 44.5% to 45.5%, GAAP EPS in the range of $1.17 to $1.23 and non-GAAP EPS in the range of $1.88 to $1.94.

As a result, our updated outlook for 2025 is revenue in the range of $5.262 billion and $5.292 billion, GAAP operating margin in the range of 27.9% to 28.9%, non-GAAP operating margin in the range of 43.9% to 44.9%, GAAP EPS in the range of $3.80 to $3.86, non-GAAP EPS in the range of $7.02 to $7.08, operating cash flow in the range of $1.65 billion to $1.75 billion, and we expect to use at least 50% of our annual free cash flow to repurchase Cadence shares. As usual, we published a CFO commentary document on our Investor Relations website, which includes our outlook for additional items as well as further analysis and GAAP to non-GAAP reconciliations. In conclusion, I’m pleased with our Q3 results, strong 2025 as we continue to deepen strategic partnerships across the ecosystem.

As always, I’d like to close by thanking our customers, partners and our employees for their continued support. And with that, operator, we will now take questions.

Q&A Session

Operator: [Operator Instructions] And our first question comes from the line of Vivek Arya with Bank of America Securities.

Vivek Arya: Your IP business is now, I think, tracking to over 20% growth for the second year. Anirudh, I was just hoping you would give us some sense for what’s driving this growth because your competitor expressed a lot of concerns about their IP business, whether it is in China or at Intel or just IP visibility in general. And I think they were talking about a new business model. So how do we square that with the growth you are seeing? How sustainable is this growth? And what is your visibility in your IP business?

Anirudh Devgan: Yes. Thanks, Vivek, for the question. I’m actually quite pleased with the performance of our IP business. And we don’t look at any one quarter. But even if you look how we performed last year, of course, this quarter was exceptional, but overall, how we performed this year and what we see backlog and activity going into next year, overall IP business is performing quite well. And there are multiple reasons for it. First, our IP business is different. I think it’s much more profitable, even though the profitability is less than our EDA business, but I think it’s more profitable than general IP business because we also have Tensilica, which is almost like software-like profitability. But a lot of the growth is coming in design IP.

And the reason for that is our IP business is focused on AI and HPC at the most advanced nodes. Since we got started later in the IP business, we focused it where the future is going, which is AI, HPC and chiplet-based architecture. So a lot of the — like SerDes and PCIe and HBM4 IPs. And that part of the market is doing well actually across the world. And then the second reason is, as you know, there is more and more foundries entering and especially at advanced nodes. And we have a long-standing partnership with TSMC, but also Samsung, Intel and now Rapidus. So there are at least 4 major foundries now at leading nodes. So that’s, I think, a second reason for our IP business to be well positioned. And as the performance of our IP business has improved, the PPA and we are — our PPA is comparatively better in design IP and a lot of customers want to shift over to Cadence.

So the customer demand, I think, is the third reason as our IP business strengthened that we are seeing strength in the IP business. So I think for these 3 main reasons, I’m pretty optimistic about the IP business. And going to next year, we’re not getting into next year, but just to give an indication, I would be surprised if our IP business does not grow better than Cadence average, which it should, given the profitability profile. We want that to happen. If the profitability is slightly lower than EDA, then the growth should be higher than Cadence average. So overall, I think that would make like 3 years trend. And overall, I’m pleased by our IP performance.

Operator: And our next question comes from the line of Jason Celino with KeyBanc Capital Markets.

Jason Celino: Great. Last quarter, I think you mentioned the second half having good renewal opportunity with some of your large customers. With the uptick in backlog, I imagine some of that strength was from some of these renewals. But as we think about Q4, do you still have renewals on the docket?

Anirudh Devgan: Yes. Thanks for the question. I’ll let John comment on the timing of the renewals. But overall, I do think that our performance in Q3 is much — is better than we expected. And the primary reason — and this is true in all geographies. But I think the primary reason is that the AI infrastructure build-out, as you know, is accelerating, okay? And we are essential to the design and build-out of the AI infrastructure. Of course, we — I have said publicly, there are 3 big phases of AI in my mind, AI infrastructure being the first one, physical AI being the second one and sciences AI being the third one. But most of our focus and investment is, of course, on the first one. And as you see in the last 6 months, it is accelerating.

And also the — we are privileged to work with all the Mag 7s and also investment in internal chip design is accelerating along with, of course, the big merchant silicon companies like NVIDIA and Broadcom and AMD. So I think that is coming through in our booking activity in Q3. And so far, we see that strong demand continuing in the future.

John Wall: Yes, Jason, I would just like to add that the mix as well is healthy across EDA, IP, hardware and SDA. And the core EDA and IP backlog is weighted towards multiyear recurring arrangements, and that supports durable double-digit growth.

Operator: And our next question comes from the line of Joe Vruwink with Baird.

Joseph Vruwink: Great. I guess I’m struck by the number of times the word acceleration has already been used on the call so far. And I guess the third quarter bookings much stronger than we were expecting, and it would support a future acceleration. I know it’s atypical to kind of get 2026 comments, but Anirudh already did for the IP business. I’m just wondering if you can maybe start to frame expectations for next year based on what you have in hand and it certainly seems like things are setting up well. Do you have the type of visibility at this point to maybe comment on it?

Anirudh Devgan: Yes. I think what I would like to say is that we always look at our business in terms of how well our products are doing, okay? And we report like 5 lines of businesses, as you know. And I would say, at this point, all 5 lines of business are performing very well. And you can see that in this year, I think we will grow double digits in all 5 lines of business. And also, we are performing well in all geographies. So in terms of products and geographies, which is our main focus, are we aligned with the leading companies? Are we trusted partner of the market-shaping companies? So if you look at products, geographies and customer alignment, I think we are well positioned. Of course, as you know, as we enter a new year, we are always prudent in our outlook, and we will give you update about next year when we come to January, February time frame.

But I think Cadence is very well positioned — better positioned than it has been, I think, for last — compared to the last several years, and we look forward to working with our customers in the future.

John Wall: Yes. Joe, we won’t guide FY ’26 today. But exiting FY ’25 with probably record backlog and broad-based momentum from deepening strategic and trusted partnerships across the ecosystem positions us well for next year. You can expect our framework will remain disciplined. We typically aim for double-digit top line ambition, continued operating leverage and balanced capital allocation. And that’s all underpinned by secular AI demand across chip to systems.

Operator: And our next question comes from the line of Lee Simpson with Morgan Stanley.

Lee Simpson: Great. Congratulations on another great quarter. I just wanted to ask around about China, really. The — it looks as though you’re up about 53% year-on-year, doing well in the mix, up to 18%. That feels more than just a sort of return of business post the restrictions on the BIS letter last quarter. It feels though there’s genuine momentum there. So I wonder if you can talk me through what is driving this. Is it IP? Is it hardware? Is it core EDA? What are the vectors here?

John Wall: Thanks for the question, Lee. Yes, I mean, we saw broad-based strength and China design activity remains very strong. The region returned to business as usual for us in the second half that with the lifting of the export regulations that changed for EDA in early July. But Q3 really was only slightly better than we expected, and we now expect China to be up year-over-year for fiscal ’25. Anirudh, do you want to add anything to what’s happening in China?

Anirudh Devgan: Yes, Lee, that’s a good question on China. I mean, overall, I would say the behavior in China, from what I can tell, is back to normal. Of course, there was a disruption in Q2 for obvious reasons, given the policy in Q2. But the behavior that we are seeing is back to normal in Q3. And a lot of it was driven by like us prioritizing hardware deliveries that we could not do in Q2 into Q3. But overall, design activity is strong in China across — I mean, semiconductors are essentials to every country, and China continues to invest in semis. But overall, I would say our strength is broad-based, not particularly tied to any one geography. And there was some makeup from Q2 to Q3. Now it’s difficult to predict the future, but what I see, I don’t see any unusual activity in China. Like question may be like is there any pull-in from future quarters. We don’t see that in terms of what we see, and we see overall broad-based strength in other geographies as well.

Operator: And our next question comes from the line of Siti Panigrahi with Mizuho.

Sitikantha Panigrahi: Great. Congratulations on another strong execution. Anirudh, I want to ask you about on your system design, mainly the simulation analysis market. Help us understand your strategy. You made acquisition last year, BETA CAE and this year, again, you’ve announced MSC software. Help us understand how you’re going to position yourself against your competitor in that market. This is definitely a growing market. I would appreciate any color on that.

Anirudh Devgan: Yes, Siti, thanks for that question. I mean, I’m pretty pleased with the overall performance of SD&A. And I mean, just to remind everybody, Cadence is the one started this whole thing in 2017, 2018. Now it is considered obvious that silicon and systems are going to come together. I mean we have been talking about this for a very long time. Now I think what the acquisition that we did this quarter is more forward-looking in the sense that, like I mentioned, these 3 horizon technologies, horizon 1 being infrastructure AI, horizon 2 being physical AI, horizon 3 being sciences AI. And that’s how we are focused. Most of our investment in horizon 1, but of course, like maybe 70%, 80% is horizon 1, about 20% horizon 2 and a few percent horizon 3.

But horizon 2 of cars, drones and robots can be a very, very big market in the future. And what happens is AI is going to change also for horizon 2. As you see, there’s a lot of reports that the world is going to move from LLM-based AI to a word model-based AI, in which robots, you have to — it’s no longer the text data that trains the robot, it is the physical movement and all that. And one of the key challenges in training robots or cars is that there is not enough data that is available. When you train an LLM model, basically, the data is available on the Internet and as well — language data is available, whereas training a robot, the data is not available, okay? So the data either has to be generated manually, like they put sensors on a human and the person picks up the object, that could be data.

But that’s a very slow form of getting data. The best way to generate data for a word model is through simulation. And this is what we have talked about also for a very long time of the 3-layer cake. So then the fundamental simulation of multi-body dynamics becomes essential in horizon 2 physical AI. And Hexagon had a leading simulator for multibody dynamics along with structured simulation, which helps in all kinds of electronics and automotive. So I think I’m pretty optimistic that this can position us well for the second horizon, which is physical AI. And so what that will do for our SD&A business, the way I look at it, our SDA business, once we complete this acquisition, we will have 2 strong pillars. And it will — actually, the run rate should cross $1 billion in 2026 if the acquisition closes.

And one pillar will be driven by 3D-IC and chiplets. Allegro is in our SD&A business. Allegro is a de facto standard for package design in the world. And so if you take Allegro, combine Sigrity and Clarity and Celsius, our kind of electromagnetics and electrothermal tools, that’s one key area of this merger of silicon and system. And we will be very, very strong in that. And our partnership with TSMC, our partnership with all the leading AI players like NVIDIA positions us very well with Allegro and 3D-IC. So that will be roughly 1/2 of our SD&A business, because there’s going to be a lot of growth in this chiplet-based architecture. And the second part will be this physical AI, structural analysis and the combination of BETA, which was the leader in pre-post processing with Hexagon, which has a lot of solvers like multibody dynamics structural.

And then we acquired a great new CFD solver from Stanford a couple of years ago. So if you put all the solvers together with BETA, that will be roughly half of our SD&A business and really well positioned for the physical AI. So if you put it all together, the benefit of Hexagon is that it will give us 2 strong pillars in SD&A in the areas that are going to grow the most in the future, one is 3D-IC and HPC, the other is physical AI and connected technologies.

Operator: And our next question comes from the line of Jim Schneider with Goldman Sachs.

James Schneider: I was wondering if you can maybe frame for us some of the tailwinds you expect you might see over the next couple of years as a result of inclusion of AI features into your products on the core EDA side. Maybe talk about any kind of productivity metrics you can give us in terms of time to market or developer productivity and how that might translate into either revenue or adoption rates of that technology and features.

Anirudh Devgan: Absolutely. Great question. As we have said before, there are 2 parts to our AI strategy, which we call design for AI and then AI for design, okay? I think the first part is the build-out of the AI ecosystem, whether it’s infrastructure or physical AI. And that we are very well positioned with all the leading players, all the Mag 7 companies. And now I think your question is on the second one, which is, of course, applying AI to design. So even this time, we highlighted several examples. So we have at least 5 major platforms. And some of the big examples are, for example, SimAI, which is using AI to accelerate verification. Verification is almost an exponential task in chip design. And we are seeing with SimAI, 5 to 10x improvement in logic simulation efficiency and coverage, which is one of the mostly heavily used tools in verification.

And even in CadenceLIVE, Samsung and Qualcomm and NVIDIA highlighted this. So these are demonstrated benefits at customer sites being highlighted by the customer themselves, okay? The other area is in physical design, the back-end physical design with Cerebrus AI Studio. Again, we had Samsung code 4x improvement in productivity and also 22% improvement in PPA. By the way, this is huge numbers because when you go from like 5- to 3-nanometer, 3-nanometer to 2-nanometer, typically, a node migration, which the industry is spending like billions and billions of dollars, will give like 10% to 20% PPA improvement. And if we can get that with better optimization, with better AI, that’s a huge value for our customers. So the good news is that I think the adoption of AI tools is almost taken as a de facto.

All the big customers are adopting our AI tools. And I’ve said even before that the monetization of that takes some time. It always takes 2 contract cycles. And I think we should be able to do that or slightly better. So — but the productivity is huge by applying AI to EDA. And the reason I think it is different in EDA than other things is, first of all, there are multiple reasons. One is we have done automation for 30 years. The chip design process is highly automated. About 80%, 90% of it is already automated. So we have a lot of history of automation and then AI is the next 10x that automation that can happen. I mean we have probably improved chip design 100x in the last 20 years, and AI can give the next 10x. And the other thing that is different in chip design versus other industries, I believe, is because the workload is exponential.

The chips in 5 years from now will be like 5, 10x bigger. The complexity will be 20, 30x more, given software and chiplet. So AI productivity is needed just to keep up. So our workload is exponential. It’s very different than a workload is not exponential. So the customers are expecting us to deliver more productivity and are accepting of deploying that in their designs.

Operator: And our next question comes from the line of Harlan Sur with JPMorgan.

Harlan Sur: Great job on the quarterly execution as always. On the third-generation upgrade cycle on your emulation and prototyping platforms, you’re about 5 quarters into the upgrade cycle, drove record revenues in Q3. If I rewind back to your second-generation launch, right, the team drove 3 years of record revenues post launch. You still have the same drivers in place, right, design, software complexity increasing exponentially, the Cadence of new chip program introductions, accelerating addition of new customers like OpenAI, as you mentioned on the call today, and proliferation of all of these challenges into new markets like automotive and software-defined vehicle. Given the lead times for your Protium and Palladium systems, I assume you’re already booking into next year. What’s the demand curve look like? And do you anticipate continued momentum and growth in 2026 for the hardware platform?

Anirudh Devgan: Yes, Harlan, as always, you’re always very perceptive in the overall trends in the market. Yes, hardware is doing phenomenally well, and I expect the trend to continue. So will ’26 be better than 25%? That’s what we would think. Now how much better? We are always prudent in that because hardware, you don’t have like a full year visibility like we would have in the software business. So when we go into any given year, we only have a 6-month visibility. So we are always prudent in our hardware guide. And then if the business comes in as expected, just like this year, we can improve our guide for the rest of the year. But that’s on the — that’s more on the guiding discipline, which we want to be — we want to derisk our guide for our investors.

Now in terms of fundamental technology trends and market trends, I mean, this is a great setup for hardware because, first of all, we are the only company that builds our own systems. We build our own chips at TSMC that are full reticle chips. You should see these things. These racks have 144 liquid cooled chips connected by InfiniBand and optical and the customers will connect like 16 racks together. That can emulate like 1 trillion transistor designs. I mean there is no other platform that can compete with that. And also the demand for hardware is increasing not just because of there are more AI designs, but as we go from 3-nanometer to 2-nanometer to 1.4 to 1, which will take next 7, 10 years, the size of the chips only increases, and so there is more and more demand for hardware.

So overall, competitively and market trend-wise, I think we are well positioned in hardware. But of course, for any given year, we are prudent in the guide. John, I don’t know if you want to add.

John Wall: Yes, yes. Harlan, what I’d add there is demand remains very strong, particularly across AI, HPC and auto markets. We’ve seen scaling — we’ve been scaling manufacturing capacity and trying to improve lead times. We’ve also had hardware gross margins become more healthy. We remain focused on throughput to meet the elevated need from AI designs. And if you look at our financials this quarter, you’ll see that we’ve been building inventory to try and meet the demand that’s reflected in the pipeline for the next 6 months.

Operator: And our next question comes from the line of Jay Vleeschhouwer with Griffin Securities.

Jay Vleeschhouwer: Anirudh, you gave several examples of customer activity, customer engagements and so forth. And I would like to ask you about the recent announcement of the joint work that NVIDIA and Intel are going to be doing. Would it be fair to presume that combined GPU and CPU work would necessarily lift up demand and capacity requirements for multiple types of EDA tools, also IP, probably hardware as well. So there would be a general uplift as a result of that combined work. But at the same time, would it also necessitate your increasing your investments, for example, in AEs as you did when you had that breakthrough with Intel several years ago?

Anirudh Devgan: Yes. Jay, that’s a good observation in terms of CPU, GPU together. By the way, I’ve said this for almost 15, 20 years that the CPU, GPUs need to work together because EDA is a very well-optimized workload. And it is computational software, mathematical software, which is very similar to AI. And what happened in the history of EDA is that, of course, there are a lot of SIMD tasks like which can be done in a GPU kind of machine, but there are also a lot of conditional tasks which need to be done on a CPU kind of machine. So we always wanted both CPU and GPU. And we also wanted CPU and GPU to be close to each other. And actually, to NVIDIA’s credit and Jensen’s credit of Grace Hopper and then Grace Blackwell, I mean, they are one of the first people to track to kind of watch this trend.

And now if you look at all the major designs from other companies, too, there is a combination of CPU and GPU together. And that’s the reason for the last several years, we are already working on porting our workload to CPU plus GPU. And a perfect example was when we announced Millennium earlier in the year, so we are moving not just system analysis workload, which are more GPU friendly, but also EDA workload, which are critical for accelerating EDA and 3D-IC to CPU, GPU combination. So what I would like to say is I’m actually very pleased to see that the whole industry now is going towards this combination of CPU plus GPU, whether you look at Apple’s chips or AMD chips and of course, NVIDIA, amazing platform. And this partnership with NVIDIA and Intel is good for us in terms of gives us a new kind of x86 plus GPU.

And also, we have a long-standing partnership with NVIDIA. And then as Intel does more work with NVIDIA, it’s also good for our overall discussions with Intel, which I think are proceeding well. And I think Intel has to invest both in its ecosystem for foundry and also its own products. And I think Lip-Bu knows that, and it’s good to see the investment on both sides.

Jay Vleeschhouwer: Just to be clear, aside from the porting that you have to do internally for your own tools, you are presuming that in terms of demand that this customer activity would necessarily increase the consumption of EDA.

Anirudh Devgan: The customer activity should — I mean, I think, first of all, if the EDA tools get better because of CPU, GPU system being optimized, typically, the customers will adopt. We are always looking at ways to improve our tools, and this gives another vehicle to improve the performance of our tools. So that’s good for all customers. And then I think in this particular partnership, there are specific design activity that needs to be done without getting into too much details, NVLink-based IP. And so yes, we are working with the particular companies on design to make this design happen, just like we would work with any of the leading designs. So yes, there is a specific customer activity connected to NVIDIA and Intel. And in general, there is customer benefit if our tools are optimized better on this platform.

Operator: And our next question comes from the line of Gianmarco Conti with Deutsche Bank.

Gianmarco Conti: Congrats on another great quarter. Maybe just going back towards China, especially given the amazing quarter you guys have had, of course, part of it was recouped from Q2. But how should we think about a sustainable growth rate in the region beyond what was recouped last quarter? And potentially, if you could give some color on if there’s any real risk from yet another ban in the region. Obviously, there was some news flow going on. And I think investors want to be a bit wary about like what was real in terms of potential risk to EDA or what is sort of like a broader macro level impact? Any commentary there would be great.

Anirudh Devgan: Yes. I think China, like I said, the design activity seems back to normal to me. And I think we mentioned — of course, when we started the year, we were very prudent because I said before, when I went to China last year, I mean, they were expecting very tough kind of macro environment — geopolitical environment, which turned out to be true in ’25. So we were very prudent in our guide of China in the beginning of the year, which turned out to be correct. Now I think at this point, like John also mentioned last time and this time, we expect China to grow. How much it grows will depend. We’ll have a better idea. It’s very difficult to predict. We’ll have better idea end of the year. But I do expect China to grow this year.

And then it’s good to see — I mean, it’s very difficult to predict the geopolitical environment, and I definitely don’t want to do that. But it’s good to see that there is a lot of discussions between the 2 presidents and through big economies. So any stability there and certainty is good for our business. So we look forward to that. But I do expect that design activity is strong. And if there is no unforeseen development and the environment is stable, it should help our business. And I just want to remind you that our strength in Q3 is helped by performance in China, but it’s very broad-based, given like all the reasons we mentioned of the build-out of the AI infrastructure, the emerging design of physical AI, the overall AI megatrend. So we are pleased.

So we are not indexed to any particular country, but it’s good to see that the environment is improving in China.

John Wall: Yes. And Gian, I’d like to remind you that our Q4 and full year outlook assumes today’s export regime remains substantially similar. And we always incorporate prudence for regulatory variability. And we’ll continue to comply rigorously with — while supporting customers globally. And as Anirudh says, we’re seeing strength right across all businesses and across all geographies.

Operator: And our next question comes from the line of Joe Quatrochi with Wells Fargo.

Joseph Quatrochi: I was wondering if you could just maybe help us understand like the OpEx dynamics. I think 3Q is a bit better than expected, but 4Q is a bit worse than expected. Is that related to just the Artisan deal timing of closing that? Or just any sort of help there would be helpful.

John Wall: Sure. Yes. But yes, I mean it’s really just the timing of some hardware delivery shifting between Q3 and Q4. But overall, the year is slightly ahead of what we were expecting, and we’re pleased by the broad-based execution, strong demand across all product categories. Core EDA software is performing very well. Hardware continues to be strong. We’re continuing to make progress in SDA, and we’ve continued IP momentum and healthy renewals set up for Q4.

Joseph Quatrochi: I guess maybe just a question on the OpEx…

John Wall: Sorry, can you repeat the question?

Joseph Quatrochi: The question was on the OpEx side, like the OpEx timing?

John Wall: Yes. So on the OpEx side, we did a small restructure that benefited Q3. The hardware gross margins were very healthy in Q3. And then it’s offset a little in Q4 by some new expenses we’re picking up from new acquisitions.

Operator: And our next question comes from the line of Charles Shi with Needham.

Yu Shi: Anirudh, congrats on the nice results, and John, similarly here. The question, I look at your growth rate for the overall company for the last 3 years, it has been maintaining around that 40%-ish plus/minus range, truly remarkable. Look feels like you didn’t really skip a bit at all. But when I look under the hood, there are lots of moving parts, right? Like let’s compare last year versus this year. Last year, China was bad. Hardware was kind of decelerating. I think that was largely due to your hardware transition into the Z3, X3. I mean I’m looking at the upfront revenue as to inform me about your hardware growth. But this year, both things kind of turned much more net positive, like your upfront revenue is probably going to grow somewhere closer to 50%.

China looks like at least it’s going to grow above the corporate average. So I wonder, when we look at — think about next year, do you think both hardware and China can maintain the current momentum? Maybe especially on hardware, based on the observation of the Z2, X2 cycle, I believe that was somewhere in between ’21 and ’24. When you go into like a third year-ish, the growth rate in the Z2, X2 cycle, it kind of decelerated a little bit. So my question is, is this time can be a little bit different in terms of the hardware growth rate going forward? And could any fear from your customers regarding hardware transition to, let’s say, Z4, X4 in the maybe the next 1 to 2 years causing some of the deceleration of hardware revenue? I know this is a long question, but I think that this is the most important when we think about the Cadence outperformance going into next year.

John Wall: Thanks for the question, Charles. We’re trying to unpack it. So I think I wouldn’t focus too much on any one quarter or even any one half in terms of results. If you recall last year, the shape of the revenue curve was kind of back-end loaded. And Q3 over Q3 comps can be a bit skewed, particularly as well with China, given that we had that temporary restriction in China from May to early July. But generally, when you’re talking about hardware, demand is very, very strong, but — and we’re seeing a secular trend in hardware demand for many years now because the growth in complexity continues unabated. But we’re seeing a very strong pipeline for the next 6 months. And we’re ramping up on inventory for some large orders that we have to fill in the next couple of quarters.

But — so we’re seeing lots of momentum. And we expect to — I mean if I go back, I think the last 5, 6 years, and it’s typical of Cadence, Q4 bookings would exceed Q4 revenue. So we just finished with $7 billion of backlog at the end of Q3, which is a new record for us. Given renewal timing in Q4 and the visibility we have, we’d expect to end ’25 at a fresh high. And with that mix being so healthy across all of the different businesses, I think it bodes well for next year.

Yu Shi: So maybe a quick follow-up. So Anirudh, from your perspective, the current hardware Z3, X3 enough to support 1 trillion transistors, but with AI really like moving really fast, do you foresee like when you probably need to like do another hardware refresh? And is there any light you can shed on this?

Anirudh Devgan: Charles, yes, I’m very confident in our hardware position. We talked about Palladium. We’re the only company that designs our own chips and also Protium with FPGA systems, and that’s also doing well with the Dynamic Duo. And like John said, we see good demand. Now I just want to remind you that when we guide, we always are prudent given hardware is not as predictable as software, but it has almost — even though we reported kind of upfront revenue, but what has happened is that all these big customers are almost buying every year. It’s not that they’re buying — so the buying behavior is different than 4, 5 years ago because they’re doing so much design that all the really big customers, it has almost become like an annual kind of subscription, even though financially, it is reported, of course, as upfront.

So now will the hardware trend continue? I mean, right now, I don’t see any reason that it won’t. And so I think ’26 will be stronger than ’25. How much stronger, we’ll have a better idea. Now in terms of our next generation, we are always investing in R&D. We have a huge investment in R&D, as you know, 35% of our revenue is invested in R&D. And — but if you look at our expense side, almost 65% of our expense is invested in R&D and about 25% is invested in application engineering. So more than 90% of our investment and headcount is in engineering, customer support and R&D. And that’s true for hardware. So we are — we don’t want to get into all the details, but you can assume we are well in our way designing the next generation of hardware systems, and they will come in time.

One thing, good thing is about our current systems already support 1 trillion transistor designs, and that is supposed to happen by 2030. But before 2030, we will have a next generation of hardware, which will support it for next 5 years. So I think I’m pretty confident in our hardware road map. And the demand itself, I think because, Harlan, you know all this area well, I mean, AI, the chips are only getting bigger. And also what’s happening is like even with like Blackwell, it’s not just one chip now, you have multiple chips and then Grace together. So the customers are also not emulating just one chip, which is growing 2x every node. They’re emulating systems of chips like Grace and Blackwell together or if you have chiplet architectures.

So the demand for hardware may move faster than just Moore’s Law or technology scaling because of this 3D-IC. But again, we will see that. We are well positioned. We’ll see how it progresses. But systemically, there is no issue in demand for hardware and our competitive position.

John Wall: Charles, there was a lot in your question. I think you referred to upfront recurring revenue as well. I mean we continue to frame ’25 around 80-20 recurring to upfront on a rolling 4-quarter basis. And I think as you mentioned in your question, the variability quarter-to-quarter is driven mainly by strong upfront businesses like hardware and IP and the timing of China ratable revenue earlier in the year. But with core EDA growing so well, we’re comfortable that 80-20 is probably the right kind of mix of business for the foreseeable future.

Operator: And our next question comes from the line of Gary Mobley with Loop Capital.

Gary Mobley: Let me extend my congratulations. I really just had a clarification or a question to get to a clarification. So if I recall correctly, given the timing of the export control repeal, which I believe is July 2, your China backlog was not in your June quarter ending backlog, but I presume now that it is. So given that $600 million revenue or $600 million delta in your backlog, how much of that was a function of the inclusion of China backlog versus the prior quarter?

Anirudh Devgan: Yes. Let me take a crack at it and then — I think you’re right, our backlog grew from $6.4 billion to $7 billion. So there’s a growth of $600 million. So I think about — I would say, about 25% of that about $150 million is catch-up from Q2 to Q3, and the rest growth is growth strength across our business. John?

John Wall: Yes, that’s right. No, that’s exactly right.

Operator: And our next question comes from the line of Clarke Jeffries with Piper Sandler.

Clarke Jeffries: Anirudh, I appreciate the comments on the mechanics of the strength in the IP business and specifically the demand for design IP you’re seeing for AI projects. I wanted to follow up with just how the wallet opportunity is changing with those AI projects. Specifically, do you see any potential for growing pains or lower profitability to serve the industry as they make more customer bespoke technologies with chiplet or custom memory designs incorporated into those AI and HPC designs. Has Cadence changed its investment plan or selling motion to serve that more custom nature required by the industry? Or is that even needed at all?

Anirudh Devgan: Yes. Great question. I mean this is a big trend, right, design of custom silicon. I mean, we have talked about it for years, system companies doing silicon. And as you know, about 45% of our business is coming from system companies and 55% is coming from semi companies. And so with this — especially with AI, there is acceleration of custom silicon. And I think one different from 6 months ago or 1 year ago to now is when I look at these big system companies, they are more and more committed to custom silicon. And of course, we have great partnership with NVIDIA and NVIDIA is going to do phenomenally well, but so will custom silicon, and we can see from Broadcom results, and we also work very closely with Broadcom and the customers themselves.

So — and there’s opportunities because the demand is so high in terms of — if you look at all these big customers, they’re projecting AI compute demand to grow like 2x every year for next several years. So I think there is growth for everyone involved in that. And the benefit of doing custom silicon, at least for the inference part, can be so high that they are willing to invest in EDA internal chip design. So I think the financial and the customization benefit for our customers, and these are, of course, the biggest companies in the world is significant doing custom silicon. You can look at all the big ones like Google and Meta and all the others like Microsoft, Amazon, Tesla. So I think there’s going to be acceleration of that. And as they do more internal design, of course, they need to invest in EDA and IP and hardware.

So I think the trend is healthy there. Profitability questions are similar. We want to have discipline on our pricing. So our profitability is similar, but the benefit to our system companies is high as they do their own chips.

Operator: And our next question comes from the line of Ruben Roy with Stifel.

Ruben Roy: Anirudh, I had a quick question, I hope on a comment you made during your prepared remarks about collaborating with a customer on next-generation agentic AI solutions. I’m wondering, is that something that you’re seeing across a wide swath of your end customers? And if so, just wondering if you could walk through maybe some of the implications of that, whether it’s how some of those collaborative efforts on that type of solution might be monetized longer term? And how you’re thinking about agentic AI overall relative to specific — it almost sounds like custom solutions by customer versus a broader agentic AI solution set that cadence might offer to the broader ecosystem.

Anirudh Devgan: It’s a great question. We could talk for a while on this one. And we are privileged to have the partnership with several companies on AI. I mean not just the design of AI, but AI for design in our solutions and especially on agentic AI because this is a new emerging area. We have like 5 major AI platforms. But what is unique about agentic AI is, of course, all the gen AI stuff. And if you look at even one of the biggest applications of AI is kind of vibe coding or software development. Well, if you look at it, part of the chip design is also coding. We have automated, like I mentioned earlier, 90% of the workflow for chip design. But one part of workflow, which is not automated is the customers still have to write RTL.

RTL is like a language, register transfer language that describes the chip. And this happens in the very beginning part of the chip design process. So that process is still manual. But the algorithm that is helping wipe coding or C++ coding for general software development, kind of these agenting methods can also help for RTL development, okay? And it can provide a lot of benefit to this 10% of the workflow that is not automated. So therefore, we have a massive investment in agentic AI, which you will see as we announce more products going forward. And we already have several partnerships in there, and we are highlighting one of them. And the way we are going to market there is, this is longer — is through JedAI. I’ve talked about JedAI before.

So JedAI is joint enterprise data and AI platform. So it does have some standardized components. The database is standard. All the models are available. AI models has interface to all our AI tools. So part of JedAI is standard across all customers, and we work with foundries and all to kind of train our models. Now part of it could be customer-specific, okay? And in that case, the data is held at the customer site. And that’s where we architected JedAI from the very beginning to be both on-prem and cloud-based, because sometimes the customers want it cloud-based, but sometimes if they want data to be localized, they want it on-prem. So that’s why for years, we have invested in this kind of unique platform, JedAI that allows us not just to build unique solutions like RTL development and verification plan development, but also deploy it either in a general way or more specialized to a particular big customer.

But I’m pretty optimistic in how agentic AI can automate the remaining kind of part that was manual and again, focus our customers to do higher-level tasks and remove some of the mundane task of RTL coding, verification plan generation, things like that.

Operator: And our final question comes from the line of Joshua Tilton with Wolfe Research.

Joshua Tilton: Congrats on a very strong quarter. Given the time, I’m just going to actually ask a pretty direct clarification question. John, I think it’s pretty much for you. In the event that you do see some impacts in the China region, given the ongoing tariff negotiations this coming quarter, do you feel or can you help us understand how you kind of handicap the updated guidance for some, if any, potential negativity in the region?

John Wall: Josh, I mean, that’s a great question. I’d love to be able to tell the future. The — I mean, as always, we incorporate prudence for all kinds of regulatory variability. And we base our guidance assuming that today’s export regime remains substantially similar going forward through the end of 2025. But it’s very, very hard to predict what’s going to happen. But by all reports that we’ve heard that we believe that geopolitical tensions are lower than people expect.

Operator: And I will now turn the call back to Anirudh Devgan for closing remarks.

Anirudh Devgan: Thank you all for joining us this afternoon. It’s an exciting time for Cadence with strong business momentum and growing opportunities with semiconductor and system customers. With a world-class employee base, we continue delivering to our innovation road map and working hard to delight our customers and partners. On behalf of our Board of Directors, we thank our customers, partners and investors for their continued trust and confidence in Cadence.

Operator: And ladies and gentlemen, thank you for participating in today’s Cadence Third Quarter 2025 Earnings Conference Call. This concludes today’s call, and you may now disconnect.