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 fourth quarter and fiscal year 2025 earnings conference call all lines have been placed on mute to prevent any background noise after the speaker's remarks there will be a question and answer session if you would like to ask a question during that time simply press star and then the number one on your telephone keypad. Thank you. And I will now turn the call over to Richard Gu, Vice President of Investor

Relations for Cadence. Please go ahead. Thank you, operator. I would like to welcome everyone to our fourth quarter of 2025 earnings conference call. I'm joined today by Anur 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 oscillation from or as a substitute for gap results. Reconciliations of gap to non-gap measures are included in today's earnings release. For the Q&A session today, we would ask that you observe a limit of one question only. If time permits, you can recue with additional questions. Now I'll turn the call over to Anirudh.

Thank you, Richard. Good afternoon, everyone, and thank you for joining us today. I'm pleased to report that Cadence delivered excellent results for the fourth quarter, closing an outstanding 2025 with 14% revenue growth and 45% operating margin for the year. We finished 2025 with a record backlog of $7.8 billion, well ahead of plan, reflecting broad-based portfolio strength, and increasing contributions from our AI solutions. I would like to emphasize the essential nature of Cadence's engineering software. As I have stated previously, our platform is best viewed as a three-layer cake framework. Accelerate compute being the base layer, principle simulation and optimization as the critical middle layer and AI as the top layer to drive intelligent exploration and generation. This holistic approach ensures that our AI solutions are not just fast but physically accurate and grounded in scientific truth. Building on this foundation, we are deploying agentic AI workflows powered by intelligent agents that autonomously call our underlying tools. AI flows act as a force multiplier, enabling our customers to significantly expand design exploration and accelerate time to market, while driving increased product usage and deeper engagement across our entire platform. We see growing momentum on both AI for Design and Design for AI fronts. On AI for Design, our Cadence AI portfolio continues to gain traction with market-shaping customers. Last week, we launched ChipStack AI Superagent, the world's first agentic AI solution for automating chip design and verification. is built upon our proven, physically accurate product and provides up to 10x productivity improvement for various tasks, including design coding, generating test benches, and debugging. ChipStack has received compelling endorsements from Qualcomm, NVIDIA, Altera, and Tenstorin, among others. Our other AI products, such as Cadence Cerebris, Varisium, and Allegro XAI are proliferating at scale, and our LLM-based design agents powered by JEDI data platform are delivering impressive results. On design for AI, the infrastructure AI phase is in full swing, with AI architectures growing in scale and complexity. Customers are increasingly standardizing on cadence's full flows to address their performance, power, and time-to-market challenges. We continue to closely collaborate with market leaders on their next-generation AI designs, spanning training, inference, and scaling. We deepened our long-standing partnership with Broadcom through a strategic collaboration to develop pioneering agentic AI workflows to help design Broadcom's next-generation products. We also expanded our footprint at multiple marquee hyperscalers across our EDA, hardware, IP, and system software solutions. And we are particularly excited by the emerging physical AI opportunity. And our broad-based portfolio uniquely positions us to enable autonomous driving and robotic companies to address multimodal silicon and system challenges. In addition, we are increasingly applying AI internally to improve efficiency across engineering, go-to-market, and operations. In 2025, we also furthered our partnerships with leading foundries. We expanded our collaboration with TSMC to power next-gen AI flows on TSMC's N2 and A16 technologies. We strengthened our engagement with Intel Foundry by officially joining the Intel Foundry Accelerator Design Services Alliance. Rapidus made a wide-ranging commitment to our core EDA software portfolio across digital, custom analog, and verification solutions. And Samsung Foundry expanded its collaboration with Cadence, leveraging our AI-driven design solutions and IP solutions. Now turning to product highlights for Q4 and 2025. Accelerating compute demand. driven by the AI infrastructure build out and demanding next generation data center requirements continue to create significant opportunities for our core EDA portfolio. Our core EDA business delivered strong performance with revenue growing 13% in 2025. Our recurring software business re-accelerated to double-digit growth in Q4, a testament to the strength and durability of our model. Our hardware business delivered another record year with over 30 new customers and substantially higher repeat demand from AI and hyperscalers. Seven out of the top 10 customers in 2025 were dynamic duo customers, underscoring the differentiated value provided by our hardware systems. With a strong backlog entering 2026 we expect this year to be yet another record year for hardware our digital portfolio delivered a strong year driven by continued proliferation of our full flow solutions as we added 25 new digital full flow logos in 2025 we expanded our footprint at a top hyperscaler growing our AI-driven synthesis and implementation solutions, including our 3DIC platforms. A marquee hyperscaler embraced the Cadence Digital Full Flow for its first full customer-owned tooling AI chip tape-out. Broad proliferation of Cadence Cerebrus continues, and adoption of our Cadence Cerebrus AI studio is accelerating. Recently, Samsung US used it to tape out a SF2 design, achieving 4X productivity improvement. In custom and analog, our Spectre circuit simulator saw significant growth at leading AI and memory companies. Our flagship virtuoso studio, the industry standard for custom and mix signal design, saw continued traction in AI-driven design migration across its vast install base. A top multinational electronics and EV customer reported a 30% layout efficiency gain using our AI-driven design migration. Our IP business saw strong momentum, with revenue growing nearly 25% in 2025, reflecting both the strength of our expanding IP portfolio and the critical role our star IP solutions play in the AI, HPC, and automotive verticals. We achieve both significant expansions and meaningful competitive wins at marquee customers, demonstrating the superior performance and capabilities of our IP solutions across HBM, UCI, PCI, DDR, and CERDIS titles. We are seeing particularly strong adoption of our industry-leading memory IP solutions, including our groundbreaking LPDDR6 memory IP, which is enabling customers to achieve the memory performance and efficiency required for next-generation AI workloads. In Q4, we launched our Tensilica Hi-Fi IQDSP, offering up to 8x higher AI performance and more than 25% energy savings for automotive infotainment, smartphone, and home entertainment markets. Our system design and analysis business delivered 13% revenue growth in 2025. Earlier in the year, we introduced the new Millennium M2000 AI supercomputer, featuring NVIDIA Blackwell, which is ramping nicely and with growing customer interest across multiple end markets. Our 3DIC platform has become a key enabler for the industry's transition to multi-chip architectures, which are increasingly critical for next-generation AI infrastructure, HP, PC, and advanced mobile application. Adoption of our AI-driven Allegro X platform is accelerating. Earlier in Q3, Infineon standardized on Allegro X, and in Q4, ST Microelectronics decided to adopt our Allegro X solution to design printed circuit boards. Our reality data center digital twin solution continued its strong momentum and was deployed at several leading hyperscalers and marquee AI companies. Beta CAE continues to unlock tremendous opportunities, particularly in the automotive segment. With our previously announced acquisition of Hexagon's DNE business, we'll be poised to accelerate our strategy around physical AI, including in autonomous vehicles and robotics. In closing, I'm pleased with our strong performance in 2025, and I'm excited about the strong momentum across our business. As the AI era continues to accelerate, our AI-driven EDA, SDA, and IP portfolio, powered by new AI agents and accelerated computing positions Cadence extremely well to capture these massive opportunities. Now, I will turn it over to John to provide more details on the Q4 results and our 2026 outlook. Thanks, Anirud, and good afternoon, everyone.

I'm pleased to report that Cadence delivered an excellent finish to 2025 with broad-based momentum across all our businesses. Robust design activity and strong customer demand drove 14% revenue growth and 20% EPS growth for the year. Productivity improvement across the company helped us achieve an operating margin of 44.6% for the year. Fourth quarter bookings were exceptionally strong and we began 2026 with a record backlog of $7.8 billion. Here are some of the financial highlights from the fourth quarter and the year, starting with the P&L. Total revenue was $1,440,000,000 for the quarter and $5,297,000,000 for the year. Gap operating margin was 32.2% for the quarter and 28.2% for the year. Non-GAAP operating margin was 45.8% for the quarter and 44.6% for the year. GAAP EPS was $1.42 for the quarter and $4.06 for the year. Non-GAAP EPS was $1.99 for the quarter and $7.14 for the year. Next, turning to the balance sheet and cash flow, our cash balance was $3 billion and $1 million at year end, while the principal value of debt outstanding was $2 billion and $500 million. Operating cash flow was $553 million in the fourth quarter and $1 billion and $729 million for the full year. DSOs were 64 days, and we used $925 million to repurchase Cadence shares during the year. Before I provide our outlook for 2026, I'd like to share that it contains our usual assumption that export control regulations that exist today remain substantially similar for the remainder of the year. And our current 2026 outlook does not include our pending acquisition of Hexagon's design and engineering business. For our outlook for 2026, we expect revenue in the range of $5.9 billion to $6 billion. Gap operating margin in the range of 31.75 to to 32.75%, non-GAAP operating margin in the range of 44.75% to 45.75%, GAAP EPS in the range of $4.95 to $5.05, non-GAAP EPS in the range of $8.05 to $8.15, operating cash flow of approximately $2 billion, and we expect to use approximately 50% of our free cash flow to repurchase Caden shares in 2026. For Q1, we expect revenue in the range of $1,420,000,000 to $1,460,000,000. Gap operating margin in the range of 30% to 31%. Non-gap operating margin in the range of 44% to 45%, GAP EPS in the range of $1.16 to $1.22, and non-GAP EPS in the range of $1.89 to $1.95. And 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 GAP to non-GAAP reconciliations. In conclusion, I am pleased that we delivered strong top-line and earnings growth for 2025. And we finished the year with a record backlog and ongoing business momentum, setting ourselves up for a great 2026. As always, I'd like to thank our customers, partners, and our employees for their continued support. And with that

operator, we will now take questions. Thank you. And at this time, I would like to remind everyone who wants to ask a question to please press star and then the number one on your telephone keypad. As a courtesy to all participants, we ask that you please limit yourself to one question. And we will pause for just a moment to compile the Q&A roster. And our first question comes from the line of Vivek Arya with Bank of America Securities. Your line is open.

Thanks for taking my question. Now, Anirudha, I'm curious, have you seen any disruption or change of thinking whatsoever at your customers in terms of them using AI to reduce or eliminate a demand for EDA or IP or any other computer-aided engineering tools. Is there a scenario at all that you have discussed, right, or your customers might contemplate where they can use more of their internal tools or AI to displace what you're doing right now? Thank you.

Yeah. Hi, Vivek. Thank you for the question. I know this is a topical, you know, question on top of mine for investors. But like I said before, I mean, for us, you know, we always look things as a three-layer cake. And, you know, there's different kinds of software. You know, there's a lot of discussion in terms of will AI replace, you know, some form of software. But, you know, well, anyway, there are different kinds of software. So our software is engineering software. You're doing very, very complex, you know, physics-based mathematical operations. So any AI tools that we are developing or our customers are using, basically in the end, call our software to get the job done properly. So what we are saying instead is that, and you can see that in our results, we can see this in our discussion with customers, is as we move to these agentic flows, it uses more of our software to get the job done rather than the other way around. So even like our own super agent, which is ChipStack, it is doing a part of the flow, first of all, that was not automated. Even in regular AI, there is a lot of automation and coding. That's one of the big applications. But if you move that over to chip design, if you look at our flow, So, you know, there is an equivalent of coding, which is RTL code, which describes the chip or the system, but that part has been mostly manual. And then after that, our tools kick in, you know, to optimize the RTL, to simulate, verify the RTL. So, what we are doing with our AI flow is the top layer is we are adding extra tools that will automate the writing of RTL, but then still it calls a lot of middle layer tools, you know, a lot of the base tools to implement and verify that. And, and I've said before, like what we are seeing at our customers, you know, they want to use more AI and, and I think they will all, they will invest more in R&D. I think they will also hire more engineers, but as a percentage of spend, the more spend will go to automation and compute because the other thing which is unique to our end market is that the workload is exponential. You know, the chip goes from $100 million now to $1 trillion in a few years. They need to do a lot more work, and some of the work will be done by AI agents, you know, calling our base tools. So overall, to answer your question, we have seen absolutely no discussion with customers of reducing the usage. On the contrary, you know, all these AI tools are increasing the usage of our tools. And of course, and the AI build out also, you know, as customers design more and more chips, you know, that is also

increasing the usage of our tools. And our next question comes from the line of Joe Verink with

Baird. Your line is open. Great, thanks. I maybe wanted to ask about how you're approaching the outlook for 2026. Looks like recurring revenue is set to accelerate and that's normally well supported by backlog maybe can you talk about the key contributors to the recurring improvement and then just on the 20 or so rubs that come from upfront sources i obviously had an incredible 2025 uh with your your hardware platforms and sounds like you're expecting growth there again um i think we're in year two of that platform now can you kind of see a repeat of what you observed back in 2023 that was a very strong year too for the second gen product how how maybe are you thinking about that product and just where it is in its life cycle yeah thanks for the question

joe this is john um you know as usual at this time of the year our guidance will reflect what we believe to be a prudent and well calibrated view of the year um we finished the year with with very strong momentum on backlog and we saw that strength right across the board across all lines of business. And as Andrew says, you know, our view of the AI era is that it increases workload faster than headcount grows and Cadence monetizes workload through broad portfolio proliferation across EDA, IP hardware and SDA. And we're seeing that flow through into all lines of business for us. Now, typically at this time of the year, our hardware is a pipeline business. we're expecting very strong first half for hardware but because we only typically see two quarters in the pipeline we're quite prudent in the second half of the year in this current guide but that's no different to what we normally do same we typically try to de-risk the guide for things like hardware and and China at this time of the year and if you look at you know how China's performed the last two years I think it was 12% of our revenue in 2024 or 13% in 2025, and we expect it to be in that kind of range, 12% to 13% of our revenue as well for this year. But yeah, we're seeing absolutely huge strength across the board, delighted with the strength of the guide, and just a key transparency metric you'll see in the CFO commentary that around 67% of 2026 revenue is coming from beginning backlog, and that gives us strong visibility into the multi-year recurring base so we're very very happy to see that recurring base um uh get back to kind of uh you know double digits kind of low team growth and our next

question comes from the line of joe kotrocki with wells fargo your line is open yeah thanks

for taking the questions just kind of curious maybe following up on that um you know the verification and emulation hardware cycle any sort of help on just kind of where you think you are at in that cycle and then is there anything we should think about just in terms of you know memory availability from that perspective or just anything about margins given pretty significant price increases we've seen across the DRM spectrum yeah good question uh so hardware

like you know like you know is in a you know multi every year is a record for hardware and and I expect that trend to continue and the reason being of course you know these hardware systems become indispensable to the design of complex chips and systems. Actually, no complex AI chip or any other, you know, mobile or automotive chip, any complex chips are not designed without hardware systems. And we have the best hardware system on the market because we design, just to remind you, we design our own chips, you know, made by TSMC. And we maybe sell full racks. You know, these things have, you know, trillions of transistors to emulate, you know, other chips. So even though it is reported up front, as you know, because the customers will buy and use the systems, you know, for multiple years, the big customers are buying them almost every year. Okay. And I don't see that trend changing. And like even I indicated, like when we launched Z3, even Z2 was a very good system. So the fact that the system is second year now, I think it's still, it has capacity to design systems of 1 trillion transistors, okay, which will last for several years to go. And, you know, in a few years anyway, we launch our next system. So we're always ahead of what the market will need. But in terms of demand, you know, we don't see any difference, you know, versus if you ask me this year versus last year, the demand is only stronger, you know, and you can see that in the backlog. And then how much this will grow, we will see. Like John said, you know, beginning of the year, we are a little careful with hardware, but we'll update you middle of the year depending on how things are going. But hardware systems are performing well. We are taking share. And actually, what I feel is we are taking share in all our major product segments. So we are taking share in hardware. We are taking share in IP, which is really good to see now. This will be almost, you know, third year of strong IP growth. You know, that's right. One year doesn't make a trend for us. But after three years, I can see that I feel good about our IP business. Hardware has been strong for a while. EDA, you know, our core business is doing phenomenal. 3DIC, we are taking share. Agentec AI, we are first to market. We already have a lot of customers using our Agentec AI flow. So not only I feel good about the hardware business and where it is, actually I feel really good at our overall portfolio and how we are performing.

And our next question comes from the line of Jim Schneider with Goldman Sachs. Your line is open.

Good afternoon. Thanks for taking my question. I was wondering if you could talk a little bit more about your AI workflows And if it's possible to quantify any of the benefits that your customers are getting from those workflows today, whether that be time market, enhanced productivity per seat, or so on, and maybe separately kind of address how you're able to monetize that and then how broad that is across your portfolio today. Thank you.

Yes, Jim. I mean, first of all, the results are quite remarkable with AI. You know, and like a few years ago, there was some skepticism of how much AI can benefit. But now, I mean, this is true in other areas too, but definitely in chip design, the results are fantastic and real. And I think there is a difference, I believe, in chip design versus other industries. Because, you know, one of the issues with AI flows is that you really don't know whether the AI result is correct or not. And this has been one issue, even in wipe coding or software, like, okay, generate some code, but, you know, you spend a lot of time verifying that it is correct or not. And in some other industries, you know, there is no, like, formal languages to design things. But in chip design, first of all, we have formal languages to design things, which is RTL. Plus, over the last, you know, 20, 30 years, we have built all these products whose job is to make sure that the RTL is correct, okay? So, all our, you know, middle-layer tools, you know, verification, simulation, optimization. So, therefore, AI can be a force multiplier and accelerant to chip design versus other areas, okay? And so, the way – and the results, you know, just to highlight, like we talked about Samsung getting 4X productivity. You know, this is code from the customer or, you know, Altera talking about, you know, 7 to 10x productivity improvement. Now, they're on parts of the flow, you know, for like RTL writing, which has been kind of manual. You know, there can be massive improvement in productivity. And in the back end, for example, physical design, you know, there could be 7%, 10%, PPA improvement, 12% in that range. so just that you know that you know when you go from one node another node like five to three or three nanometers two nanometer the gain could be like 10 20 percent so you're getting half the gain or almost the same gain as a node migration through better optimization with AI okay so I think the results are real we have demand from almost all customers now to engage rapidly because they want to deploy AI in their R&D function. And you have to remember the way our customers deploy R&D in their, apply AI in their R&D function is through cadence and cadence tools, right? So they are all very anxious to try all these things. We have all these engagements with all the top customers. And our monetization, and I'm, you know, I always said in the past that it takes some time for monetization to happen. You know, it takes two contract cycles. And I think we are, you know, well into that now. So I think we are seeing the monetization now, which is reflected in our results, is reflected in our record backlog. And agentic AI can give further monetization, you know. So the way we go to market with agentic AI will be different because this is a new tool category of something that EDA never automated. You know, writing of RTL or test benches was manual right so we will price it as like a virtual engineer or agent so that would be you know extra business and our customers are willing to spend on that because it is it is productive improvement for them and then on top of that just like before it will call the base tools and and they become a lot more a lot more licenses or usage will happen our base tools And the reason for that is like in the non-AI flow, this is a misnomer that we are like seed count limited. We are exploration limited. Even if a user like a manual user is running our tool, they will run like three or four or five experiments in parallel to see what is the best PPA. But with the agentic AI flow, it could run 10 or 100 experiments in parallel. So our plan for monetization, which is working well, we'll add the agentic AI part. we will charge for the agentic flows from a virtual engineer things like rtl writing and then of course for the licenses in the base layer and and see how that goes but from a customer standpoint i mean there's a lot of demand to try all these new tools and our next question comes

from the line of gary mobley with loop capital your line is open hi guys let me extend a

congratulations on to on the strong finish of the year uh john i believe there's been a an effort to move your SDNA customers into one-year license terms, and if I'm not mistaken, that's been an impediment to growth. So the question is, you know, is that the reason why SDNA revenue grew only 13% in 2025, and what's the consideration for 2026, and then what's the consideration for Hexagon when you roll that business in? I believe they were at a $240 million revenue run rate? Does that see a more limited, is a number limited because of this one-year license term

transition? Yeah, thanks for the question, Gary. Yeah, and you're right in terms of SDNA. You know, we lapped some tough comps in SDNA in Q4 2025, partly due to the multi-year business. We did some multi-year business in Q4 2024 through our beta subsidiary, and we have deliberately been moving to more annual subscription arrangements for for beta in 2025 and that impacts the year over year numbers and seeing all that we're very pleased with uh sdna's uh strategic uh trajectory and it's and its role in the chip to systems thesis from from a mixed standpoint sdna was like 16 percent of revenue and 25 consistent with uh with 24 when you look at the year um the and we expected to grow we expect all product groups to grow but we're not guiding by segment. In relation to Hexagon, I think the annualized, I think we've said this before at some fireside chats, that the annualized revenue for Hexagon is about $200 million on a year basis. Now, what that means, of course, it's kind of like Beta, where Beta did a lot of January 1 deals. If that deal closed by the end of Q1, you're probably looking at $150 million revenue for the year but we're not guiding we don't have final numbers for anything like that now but um so we haven't got anything to do with hexagon in this guys and our next question comes from the line of

charles xi with needham your line is open hi thanks for taking my question uh aniru i i thought that the best the best highlight of the quarter uh was the announcement around the marquee hyperscaler customer adopting cadence full digital full flow uh i think you characterize it as for the first the clot uh chip that they're gonna tape out um so it sounds like that we should expect that particular hyperscaler having a cot chip uh coming out in two or three years down the road and uh just kind of want to ask a question like how many hyperscaler customers right now are are are doing COT and even for that particular customer having the first chip on COT wonder what's your what do you think at the ramp is going to be like how how will they proliferate COT for the other other chips they are developing because every hyperscaler these days have more than one chip that's my

understanding and just want to get some sense for you where you are in terms of that whole COT

proliferation, and I believe this is one of the great stories about the cadence about EDA in general, but I want to get your stance. Thank you. Yeah, thanks for the question, Charles.

I mean, without getting into, like, specifics of a particular customer, but, you know, I have said for some time now, because we work with our customers confidentially, you know, we share our roadmap with them, you know, they share a roadmap with us, and we are in a unique position to work with all the leading companies across the globe, right? And so I have said for a while that, you know, this trend of, first of all, the trend that the customers, especially these big hyperscalers, will do their own chips is even more firm now than one or two years ago. And it's evident now with some of the big hyperscalers, the success they're having with their own chips, right, especially in the last six months, that has become evident. Because it was not clear, like one or two years ago, people thought, you know, people will not design their own chips. It doesn't mean that the merchant semi will not do well. A merchant semi will do fabulous. But the big customers will design their own chips. And then this is also true that over time, the big customers will do more and more things in-house, you know, starting with ASIC to hybrid COT to COT. because these chips are, I mean, this is more, there's another step these days versus the old days, which is hybrid COD, because these chips have multiple chiplets in them. So the customers can do some of the chiplets themselves, some can be outsourced, and then they can do all of them themselves. So I think this trend is going to happen. And the reason we talk about it, it is happening, you know, and different customers will do it at different pace. But eventually, I think there will be multiple customers with their own chips. There will be multiple, of course, very significant semi-standard, you know, general purpose chips. And almost all of them will over time do more and more COT. And like you said, they do multiple chips now, at least three major platforms for each hyperscaler. So all this is good for us, good for more EDA consumption at the system companies, more IP being used internally, of course, more hardware, more system tools because they are system companies in nature. So we just want to make sure we are well positioned for that. But the trend is only accelerating of these big companies doing more themselves. And then, as you know, this will also then apply to other verticals like automotive and robotics and things like that.

And our next question comes from the line of Sidi Panagrahi with Mizuho. Your line is open.

Thanks for taking my question. You talked about robust design activity. Can you give us some color, any kind of improvement on your traditional semi-segment versus AI or automobile? If you could give some color, that would be helpful. And on the physical AI side, that was a big focus at CES recently. Have you started seeing any traction in that space? When do you think that will be a significant contributor?

Yes, thanks for the question, Citi. On both, I mean, the design activity is accelerating, you know, like I was saying. And that's true for system companies and semi-companies. And actually, you know, I mean, a lot of the projections are that we might hit as the industry, you know, semi might hit one trillion this year, which is like, you know, it used to be 2030 and we are like four years ahead of that. So this is very good news for the industry. And, of course, we have deep partnerships with all the major semi-players and definitely the AI leaders, you know, like with NVIDIA and with Broadcom. Actually, in this prepared remarks also, we highlighted our new collaboration with Broadcom, which are, of course, doing phenomenally well, and so is NVIDIA. And then, of course, all the memory companies are doing phenomenally well. So overall, I think the semi-companies along the system companies are doing great. And I do see, especially in AI and memory, but we do see the general market. I'm sure you follow that. The mixed signal companies, the regular, let's call it the regular semi-companies, are also, I think, have a better outlook for 26 than 25. So it's good to see a broad-based strength in the semi-business, which is about 55% of our business. And that just creates a better environment for us to deploy our new solutions. And they all want to deploy AI, you know, like we discussed earlier. And that's true for both semi and system companies. So overall, I feel that the environment is much more healthier starting 26 than it was like a year ago.

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

your line is open. Great. Thanks for squeezing me in here. I just wanted to go back to ChipStack if I could. I mean, it seems relatively clear that you see the super agent as something that can transform from Verilog to RTL or the coding thereof at least. And then it would pull in basically our tools for debug and optimization. So you get a more deterministic outcome for customers. But you tease this a little bit with the idea about where the further monetization would come. It didn't sound like it would be on a subscription basis. It would be on a sort of value to customer basis. So I wonder if you can maybe just expand a little on that and how that would be monetized and maybe in particular whether or not this would be margin accretive. You're at 45% now already. So could this help kick that on? Thanks. That's a great question, Lee. If I might

jump in here on the monetization side, that we don't see AI forcing a wholesale change from subscriptions to consumption. Our customers still want predictable access to trusted sign-off engines and certified flows, so multi-year subscription remains the core of our business. What AI does is it changes how much customers run the tools and where value is created. There's more automation, there's more iterations, there's more compute, so we'll attach more usage-based pricing for incremental capacity and AI-driven optimization. We have card models and token models that handle all those things and then in a few areas on the services side we can offer outcome oriented packages that you know structured around measurable improvements like cycle time closure productivity with clear scope and governance and and um and that's kind of how we've been going to market in in recent times and it's worked out well for us and you can see how it's turning around already our recurring revenue now we've been prudent in our outlook and we're we're not expecting an uptick in that but it definitely is um there's plenty of opportunity for for cadence in ai that uh you know as andrew said at the beginning when he when he in his opening comments there that you know there's two real things that differentiate cadence first were engineering software anchored in physics and mathematically rigorous optimization and that's not a nice to have it's a core truth that our customers require is complexity rises and then secondly ai is not replacing our products. It's amplifying demand and accelerating adoption. And you see that in our results for 2025. And I think you see it in our guide for 2026. Anything to add?

That's great, John. And our next question comes from the line of Jason Salino with KeyBank Capital

Markets. Your line is open. Hey, great. Thank you for taking my question. Looks like IP had a phenomenal year I know you have a slate of new exciting titles coming out but I just wanted to ask how that translates the pipeline like does it take time to sell these new IP titles and then with the with the guide overall it looks mostly first half weighted you know is your visibility in the IP today look

more first half IP is doing great I mean like I said you know we want to see multiple years of performance before we call it out and you know starting last year i started to call it out because we saw like multiple years and and good outlook into 26 which i think should come true so our starting backlog and everything in ip is is strong and then we are also talking to I mean, not just our traditional business with TSMC, which is doing phenomenal, but we have opportunity to engage with, you know, the newer foundries. So overall, I think IP will be good this year and we'll see how it progresses. We'll keep you updated, but it should be a strong year

for IP in 26. And our next question comes from the line of Jay Flesauer with Griffin Securities. Your line is open.

Thank you. Good evening. Anirudh, if we think about what's currently occurring with the AI phenomenon in large EDA historical terms, the last time I would argue that there was a major, let's call it generational, technical, and procedural change in the industry was in the early 2000s. And I'd like to ask how this time might be different from that phenomenon in the sense that the last time it was fairly narrowly based in terms of the number of products that grew or were newly adopted. We saw the very interesting phenomenon where average contract durations actually shrank, I think, as customers were looking to perhaps mitigate technical risk and wanted to retain some vendor flexibility or optionality, hence the shorter durations at that time. Would you say that this time around, the adoption phenomenon might last longer than just a few years of the earlier generation I mentioned, that there wouldn't be necessarily an adverse effect on contract durations, perhaps maybe even a lengthening with longer commitments from customers? And maybe talk about how in those big respects, this phenomenon might be broader and more long-lasting than what occurred, again, many years ago, but it has some similarities.

Yeah, that's a great point, Jay. And, I mean, we have to see how it unfolds, you know, because each time is similar but different. But we are not seeing any change in the duration, which is good. You know, we don't want to – but there is always more opportunity to see more and more add-ons, you know, like we have mentioned in the past. And it will affect all parts of the flow, you know, like in the three-layer cake, you know, the top two layers will fuse together, you know, AI and our core engines. And I think there is opportunity to add, like I said, add new product categories, especially in the front end, you know, this kind of super agent to write RTL, which, and write, not just write RTL you know which is this is different from uh regular kind of vibe coding you know so what is exciting about chip stack is not just writing RTL but also writing test benches writing verification flows because you know you know that Jay anyway that you know chip verification is as important as chip design you know if you can't verify then the thing you know because all our customers want things to be first time right so I think the opportunities of AI and verifications are huge, because that's the NP-complete exponential problem. So I think what is also exciting to me on the Agentec AI new tools is the ability to verify much more accurately. And then we go from there. I mean, I think I feel good about the strength of the, you know, at this point, I feel good about all the three layers of the cake. You know, we have been innovating. We have been first to market, importing our software to new hardware platforms, whether they're parallel CPUs or GPUs or custom chips, you know, our base tools are performing remarkably well. We are taking share in almost all segments. And then we are first to market with agentic AI. So I feel good about the portfolio. I feel good about the engagement. Now, how exactly it will unfold, I think it should be more long lasting, but we'll, you know, it's very difficult to predict. So we'll keep you posted, but so far, so good. Yeah. This is John. Just, I mean, you know,

we've been around a long time, you know, in terms of chasing Moore's law for the longest time. And we've built sales models that generally adapt to aligning price with value while preserving the durability of our recurring revenue model. I think what you can count on us to do is that we won't undermine customer predictability, that subscriptions will remain the anchor in terms of our primary engagement with our customers. And then we won't take unbounded outcome risk either. outcomes will be scoped and measurable and we'll value will price on value metrics customers can control things like jobs and runs and compute and throughput and things like that but so it'll will be very very deliberate and thoughtful in terms of how we grow as we always are and our

next question comes from the line of John Marco Conti with Deutsche Bank your line is open

Thank you, Ian. Congrats on a great quarter. Could we start by where it evolved and whether you're seeing...

Yeah. Hi. Sorry. There's some noise on the line. So I think I got the gist of the question, but I may not have gotten all the points. So sorry. Apologize in advance. I think your question is also about the front-end agent versus Cerebras and also startups. So first of all, I think Cerebrus is super critical. I mean, so I think there will be several kind of AI agentic flows that will be needed. Now, we highlighted ChipStack because it's kind of new and it's a new category of, you know, RTL design and verification. But there are at least several agents that we are actively developing. You know, Cerebrus, we also extended the Cerebrus to full flow. So there has to be a front-end design agent like Cerebrus. There's a back-end agent for physical implementation because that takes a lot of time right now, and there's a lot of demand for making the implementation more efficient. And there's similar principles apply in Cerebrus AI Studio. We do more exploration, and the customer gets better results as a result of that. But there will be a lot of activity we will highlight in the future on the back-end,

on physical design.

So there's digital design and verification is one area. Physical design, another area. Analog, of course, is ripe for. Finally, we have new technology to see if we can automate more and more of analog and, you know, migration flows. And then on packaging and system design. So, you know, we highlight ChipStack because we're super excited about it, but that doesn't mean that all the other, you know, there are four or five big agentic flows that we are developing. on on the startups we always watch all the startups you know you know we have history of also acquiring them if they are if they are good but more in the earlier stages like we did with chip stack i think that was the best ai startup out there and we are very confident in our own r&d you know we have like 10 000 people the best r&d team in computational software you know half of them have advanced degrees you know we have 3 000 people with customer support engineers you know we regularly meeting with customers you know with big customers on a given week we'll have multiple r&d meetings with their r&d so so we keep track of what the customer wants we have massive investment in r&d and typically i think the startups are successful in areas we don't focus in, or if you want to enter in new areas. But in terms of AI, we are completely focused. And, you know, we always use startup as an accelerant if need to, but we will have massive investment in this space in all the major domains that our customers want.

And our next question comes from the line of Ruben Roy with Stifel. Your line is open.

Yes, thank you. Anurud, you answered bits and pieces of what I'm about to ask. But I was hoping to put together a question on SDNA and just understand sort of the longer-term strategy. It seems like some companies, enterprises, industrials, otherwise are maybe thinking about pulling some simulation workloads in-house or partnering with the AI infrastructure ecosystem. We've seen Synopsys and NVIDIA talk about targeting Omniverse digital twins for that type of thing. how should investors think about your strategy? Is it sort of a neutral strategy and you'll work with, you know, accelerated compute providers, et cetera, and their, you know, tools, or, you know, are you trying to build sort of an ecosystem that's cadence specific? I'm just trying to understand, you know, kind of longer term strategy and thinking around SDNA. Thank you.

Well, yeah, thank you for the question. So in SDNA, like, you know, there are two critical areas for us. So one is 3DIC and all the innovation that's happening, you know, both at the package level analysis. And then the other is physical AI, you know, physical simulation, like for planes and cars and robots and drones. And that's one of the big reasons to acquire beta and then hexagon. But we are focused on building the core engines, okay? And the core engines will work with, you know, with the accelerated compute. Like we have a lot, you know, we have done GPU joint work with Jensen in India for years, you know, and we were the first to port all our solvers to kind of accelerate compute platform because the physical simulation word just, you know, is a lot of the simulation and physical, you know, like cars and planes and robots, kind of CFD and structural simulation. and i've said this before is is naturally without getting too technical is naturally matrix multiply okay and gpus and you know nvidia is exceptional at that because ai at score is matrix multiply so it's a good fit uh and then we work with omniverse and all but that is not in you know omniverse is a great platform but when they actually run omniverse they will run our tools you know through that so this is another way to go to market and then also directly you know with customers so we are neutral to that but omniverse is a great platform to deploy our products and you know and nvidia has highlighted that with several of our customers but our goal is to build the basic you know we are engineering software company we build the basic solver that can solve the most difficult problems combine them with ai combine them with compute and deploy it to all platforms so i feel good about our position that way yeah and our next question comes from the

line of Andrew DeGasperi with BNP Paribas. Your line is open. Thanks for putting me in. I just

had a question. You mentioned several times in prepared remarks about taking chair across the board. And I was just curious, is this kind of a change relative to previous quarters? And is it focused in any particular area? And are you surprised by this relative to what you've seen

in the past. Thank you. Yeah, I think our competitive position has improved. So we are noticing that and calling that out. And definitely in hardware, given the uniqueness of our platforms in IP. And I mean, a lot of it, you can see it in the results as well. You know, our growth is much higher than the market. So IP is doing well, hardware is doing well, EDA, you know, 3DIC. and we are holding of course our traditionally you know good position in analog and gaining in digital and verification so i feel very good about you know we are technology centric r d centric company first and i think all those investments are paying off with customers adopting more of

our flows and our next question comes from the line of kelsey chio with city your line is open

Hi. Hi, Sunny Road and John. Congrats on the great results. I would like to dive a little on China. So, John, you mentioned that you contemplated more prudent guidance from China. China revenue grew 18% last year, outpacing corporate average, and also well above your initial guidance heading into 2025. How should we think about the sustainability of this strength, Then also, what are the assumptions you have embedded in that guidance?

As we said earlier, the assumptions embedded in the guidance is that we saw 12% of revenue coming from China in 2024 and 2013 in 2025, and we expect it will be in a similar range, 12% to 13% for 2026. But what we've seen in China is design activity remains very, very strong, and we're seeing strong bookings growth in the region. um the but you know visibility is uh visibility in the pipeline is near term uh in the first half of the year so the second half of the year there's there's uh there's probably more prudence in the second half of this this year's guide um for china than there would be in the first half because we more more visibility in the first half anything to add on design activity in china design activity

is good in china and i think uh it has stabilized i mean we had mentioned this last year also second a half had stabilized and i think it continues to be strong i mean china is all the trends that are in the u.s are also in china you know a lot of ai chips a lot of physical ai is even stronger with cars and uh and you know autonomous driving evs so it's good to see china doing well and our next

question comes from the line of joshua tilton with wolf research your line is open hey guys

thanks for uh sneaking me in and i will echo my congratulations on a strong quarter uh i i kind of have a high level one uh i know a lot of times we focus on like what the three-year taker has been and i think on this call andrew mentioned that semi's companies now represent or still represent i think from my understanding about 55 of the business so my question is how do we think about growth over the next three years as the mix of semis and systems levels out and what feels like the mix of upfront and recurring levels out at what I'm assuming is kind of more sustainable levels than the shifts you've seen over the last few years? Yeah, I think, you know, we are super

excited about the system companies doing more silicon. And, you know, there have been some questions in the past. And like I had said before, I think this is irreversible and accelerating trend okay and of course we gave several examples this time and and especially because of ai you know the system companies will do a lot and then with physical ai they will do even more now that number 55 45 first of all moves very very slowly because the semi companies are doing well too i mean we are growing at a at a record pace but both of them are growing so you know Semi-companies, okay, what NVIDIA has done, of course, you know, is phenomenal. What is happening with Broadcom is phenomenal. And then Qualcomm, MediaTek, there are so many semi-companies are doing phenomenally well. So the ratio, I think more and more system companies will contribute more, but it doesn't move as fast as you would think, which is a good thing because the semi-companies are also growing rapidly. and of course semi-companies will have an essential role in the build-out of AI which is driving all this growth so that's what I would like to say

Yeah and Josh, I think I mentioned before we expect the recurring revenue mix to remain around 80% in fiscal 26 and that's consistent with 2025 and when we say that we have a prudent guide for 2026 I think there's as much upside in our recurring revenue side of the business as there is in the upfront side. Strategically, we like the balance. Recurring provides durability. You know, upfront reflects areas where customer demand is accelerating and we have differentiated assets. But we're seeing strength right across the board. And I think that's why Anarud is talking about share gains.

And our final question comes from the line of Neso 9 with Berenberg. Your line is open.

Hi, thank you for taking my question. Maybe one for John. I think you've mentioned about leveraging AI internally And I was wondering how we should think about that in our models. How should we think about your incremental margin going forward? I think with your 26th guide, what you're implying is incremental margins of about 51%, which is slightly below the rate that you've been trending in the last few years as well. So I just wanted to triangulate with the internal AI leverage and how you're guiding for margin for 26 and how we should think about margin a bit longer term in the age of AI. Thank you.

Yeah, thanks for the question. I think if you have a look at what we achieved in 2025, we achieved incremental margin of 59%, I think. And I think that points to the fact that there's no near term ceiling on operating leverage for the company. I mean, the company's performed at about 45% operating margin. So there's a lot of upside to that incremental margin of 59% that we achieved in 2025. Now, generally, we're more prudent with our guide at the start of the year, and we try to build from there. But so I think if you compare, the right compare for the 51% that's in the current guide is probably against what we would guide for incremental margin at the start of each year. that I think is one of the strongest guides that we've ever had. And then in relation to your commentary about AI and our use of that internally, that's absolutely right. That's what Anirut's talking about for years now, that it's design for AI and AI for design internally at Cadence. We learn a huge amount from our own internal group in terms of how AI is used. And if you like, I mean, we've built a great business around emulating hardware and a lot of our ai usage is like emulating engineering flows but um and yeah we take advantage of those and they're helping us to um to get more value out of the r d investments that we're making um but we expect to do the same as our customers in that when you have access to to more engineering capability and being able to do things faster and leverage AI, we'll probably do more R&D, and it'll be more people, more AI, not less people.

And I will now turn the call back to Anirudh Devgin for closing remarks.

Thank you all for joining us this afternoon. It's an exciting time for Cadence as we begin 2026 with product leadership and strong business

momentum.

Our continued execution of the intelligent system design strategy, customer-first mindset, and our high-performance culture are driving accelerated growth. Great Place to Work and Fortune Magazine recognize Cadence as one of the Fortune's 100 best companies to work for in 2025, ranking at number 11. And on behalf of our employees and our board of directors, we thank our customers, partners, and investors for their continued trust and confidence in Cadence.

And ladies and gentlemen, thank you for participating in today's Cadence Fourth Quarter and Fiscal Year 2025 Earnings Conference Call. This concludes today's call, and you may now disconnect.