Cadence Design Systems, Inc. (CDNS) Earnings Call Transcript & Summary

Ladies and gentlemen, good afternoon. My name is Abby, and I will be your conference operator today. At this time, I would like to welcome everyone to the Cadence Second Quarter 2026 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.

Thank you, operator. I would like to welcome everyone to our second quarter of 2026 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. For the Q&A session today, we would ask that you observe a limit of one question only. If time permits, you can requeue 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 very pleased to report that Cadence delivered outstanding financial results for the second quarter of 2026, with all key metrics exceeding our guidance. We exited the quarter with record backlog that was above our expectations. We are seeing growing demand for our AI-driven solutions across our expanding customer base. The AI transformation is driving strong broad-based performance across both design for AI and AI for design fronts. Given the growing business momentum and accelerating demand, we are raising our guidance for the year to 19% revenue growth and with higher profitability as we become more central to our customers as a strategic and trusted partner. John will provide more details on both our Q2 results and the updated financial outlook. Let me start with the overall environment. Design activity is growing as AI drives exponential design complexity and a new generation of system architectures spanning hyperscaler infrastructure and physical AI. Customers are investing aggressively in these opportunities, led by AI and HPC, and we are also seeing continued signs of improvement across the more traditional analog and consumer verticals. Chip and system design present demanding engineering challenges that require deterministic physics-based engines, proprietary silicon correlated data and deep design knowledge. Our Three-Layer Cake framework uniquely brings these capabilities together with accelerated compute and data at the bottom layer, physically accurate simulation and optimization solvers in the middle layer and AI agents and orchestration at the top layer. Agentic AI is a demand accelerator for Cadence as autonomous agents expand the design exploration space and call our underlying physically accurate engines more often, creating a durable tailwind that represents a significant long-term TAM expansion opportunity. We extended our leadership in Agentic AI with AuraStack AI Super Agent delivering up to 15x higher productivity and 2x faster time to market for PCB and advanced packaging design. Cadence is now the only provider with agentic solutions spanning the full electronic system design flow from digital analog design and verification to advanced packaging and PCB. We see strong early traction across our AI Super Agent portfolio with initial customer results demonstrating meaningful productivity improvement and better design outcomes. Our ChipStack AI Super Agent, enabling higher verification productivity and faster design cycles has more than 20 customer engagements and is already deployed in production across multiple chip designs. At COMPUTEX 2026, together with NVIDIA, we introduced the industry's first fully autonomous virtual AI design engineer, extending ChipStack to even higher levels of autonomy. Early customer results include more than 40x faster RTL validation, reducing a typical five-week verification cycle to less than a day on a state-of-the-art advanced node design. In analog and custom design, ViraStack is seeing strong customer interest with more than 25 customer engagements, achieving 2x to 10x productivity improvements compared to traditional design flows. InnoStack is also building momentum as customers adopt Agentic AI for advanced node SoC design. During the quarter, Rapidus announced a collaboration to integrate the Cadence InnoStack AI Super Agent into its AI agent design solution, targeting up to a 2x faster design turnaround. We continue to deepen our strategic partnerships across the ecosystem. We expanded our collaboration with Intel through a multiyear engagement focused on enabling its 14A process, leveraging our design IP and agentic AI-based EDA to co-optimize tool flows and methodologies for next-generation HPC and mobile designs. This agreement is expected to be a meaningful driver of growth over the next few years. We also deepened our collaboration with Samsung Foundry on 2-nanometer and 3D-IC technologies, combining our AI-driven flows and design IP to enable next-generation AI, HPC and mobile systems. Now turning to our businesses. We are pleased that all product groups delivered double-digit year-over-year growth. Our IP business had an outstanding quarter, growing over 40% year-over-year. AI performance is increasingly constrained by data movement, memory bandwidth and advanced packaging. And our differentiated IP portfolio continued to see strong adoption. This was reflected in the strong demand for our Star IP portfolio in AI and HPC applications, including PCIe, UCIe, HBM and LPDDR6. We also expanded engagement with leading memory, semiconductor and aerospace customers. We secured our first-ever Tensilica DSP design win with STMicroelectronics, reinforcing our strength in automotive and audio applications. Core EDA grew 18% year-over-year, driven by growing adoption of our AI solutions. Proliferation of our digital full flow solutions continued, and we saw expanded adoption of Tempus and Certus signoff tools on leading-edge designs with wins across hyperscalers, top semiconductor companies and startups. We also expanded our implementation and sign-off footprint at frontier AI companies as well as at a marquee ASIC silicon vendor, underscoring their differentiated value in enabling the industry's most advanced designs. In analog, we had a significant competitive win with Spector at a leading semiconductor supplier and our FastSPICE simulator Spectre FX noted several production wins at leading customers. Our hardware business delivered another record quarter, driven by continued strength in Palladium Z3 and Protium X3. As designs approach unprecedented scale, hardware-assisted design and verification is becoming a strategic capacity layer for our customers' AI road map. These customers are designing some of the most complex chips and systems in the world, and they critically depend on our scalable, high-performance hardware platforms to realize their designs. Demand remains especially strong from AI and HPC customers, including hyperscalers and leading semiconductor companies. We added 12 new logos and saw meaningful expansion with several marquee AI customers as well as a notable competitive win with a major AI infrastructure provider. System design and analysis revenue grew 37% year-over-year. As AI system complexity increases, customers are increasingly turning to our advanced packaging and PCB solutions. Allegro X AI was adopted by several customers, driven by significant layout design time reduction. With our 3D-IC technology and collaboration with TSMC's 3D fabric advanced packaging solutions, we are enabling customers to confidently design cutting-edge silicon for increasingly demanding AI workloads. In structural simulation, our BETA CAE business several competitive displacements, while the integration of recently acquired Hexagon's D&E business is progressing well with key deals closed with top customers. There is strong customer interest in our integrated full flow that combines our multiphysics products across the electrical, CFD and structural domains to best address next-generation system design needs, including in the emerging field of physical AI. In summary, Q2 was a great quarter for Cadence, and I'm delighted with the continued momentum of our business. With accelerating design activity, we continue to execute strongly. and our competitive position has never been better as we lead the transformation to agentic AI in chip and system design. With that, I will turn it over to John to provide more details on our Q2 results and our updated 2026 outlook.

Thanks, Anirudh, and good afternoon, everyone. Cadence delivered excellent results for the second quarter of 2026 with accelerating momentum in AI and broad-based strength across all our businesses. Robust design activity and customer demand drove 24% year-over-year revenue growth for Q2 with double-digit growth across all our product groups. With strong execution, we generated Q2 operating margin of 45.5% and second quarter bookings resulted in a record backlog of $8.1 billion. Here are some of the financial highlights from the second quarter, starting with the P&L. Total revenue was $1.584 billion. GAAP operating margin was 28.4%. Non-GAAP operating margin was 45.5%. GAAP EPS was $1.33, and non-GAAP EPS was $2.11. Next, turning to the balance sheet and cash flow. Our cash balance was $1.440 billion, while the principal value of debt outstanding was $2.5 billion. Operating cash flow was $635 million. DSOs were 65 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 useful assumption that export control regulations that exist today remain substantially similar for the remainder of the year. For our updated outlook for 2026, we now expect revenue in the range of $6.260 billion to $6.340 billion. GAAP operating margin in the range of 27.75% to 28.75% non-GAAP operating margin in the range of 43.75% to 44.75%; GAAP EPS in the range of $4.76 to $4.86, 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 Cadence shares in 2026. For Q3, we expect revenue in the range of $1.595 billion to $1.625 billion. GAAP operating margin in the range of 27.5% to 28.5%; non-GAAP operating margin in the range of 43.5% to 44.5% GAAP EPS in the range of $1.11 to $1.17 and non-GAAP EPS in the range of $2.01 to $2.07. 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 GAAP to non-GAAP reconciliations. In conclusion, I'm pleased with our strong first half results and the robust pipeline and momentum heading into the second half of the year. At the midpoint, we now expect revenue growth of 19%, operating margin of 44.25%, EPS of $8.10 and operating cash flow of $2 billion for the year. 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.

Thank you. [Operator Instructions] As a courtesy to all participants we ask that you please limit yourself to one question. [Operator Instructions] And our first question comes from the line of Joe Quatrochi with Wells Fargo.

Maybe first, just wondered if you could give us any help. You talked about Agentic AI as being a long-term TAM expansion opportunity. Is there any quantification that you could give us on that TAM at this point? And maybe how do we think about that as driving EDA as a percent of R&D expense to maybe higher over time?

Yes. Joe, thanks for the question. So, like we've said before, I mean, the great thing about Agentic AI is it opens up a new TAM opportunity. At the same time, it calls more of our underlying physically accurate software. So going back to the three-leg framework. So it's a new opportunity at the top layer and reinforces the middle layer. And I think we are pleased by the interest. I mean the interest is amazing, actually, almost all the big customers, almost all customers want to engage in our agent stack. And now we have four super agents. So I think it's a great opportunity for us. Now in terms of results, what I -- of course, we had great results in Q2 and the year so far, and there's a lot of strength in different parts of the business. But what I'm particularly proud of is the strength in the software businesses, if you look at our recurring growth, and that was particularly driven by strength of add-on business. And so both -- we are seeing add-ons driven both basically for design for AI as our customers design more chips and also AI for design, which is our Agentic and AI portfolio. And you can see that in our results. So, what is particularly impressive, and this is, I think, the highest raise we ever had is that it is broad-based, including software and AI contributing to that growth. So we'll see how things progress for rest of the year.

Yes, Joe, I'll just add that like if I could just add, the customer engagement, as Anirudh said, continues to accelerate. We're seeing increased evaluations and pilots and early deployments. And we continue to expect monetization through both new workflow products as well as increased usage of underlying engines. But just to be clear, we're still not assuming a sudden step function in our guidance. The opportunity is continuing to develop well though.

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

Staying on this topic, I wanted to ask about open source models designing chips. And maybe if I just take Kimi at face value, it seems like an agent sought out EDA tools and then orchestrated the flow when tasked with chip design. So I guess my question is the implication for Cadence from all of this and two things come to mind. One, if customers now have agents capable of accessing your EDA tools, does that drive higher usage and more net consumption ultimately? And then two, where do you think the differentiation lies with a customer buying the Cadence mental models for orchestration versus customers maybe deciding to build on their own?

Yes. Thanks for the question. I mean, like I said before, I've said this for years now, like four, five years that the real AI orchestration and monetization will happen through this Three-Layer Cake. Just to remind everybody, the top layer is AI agents and orchestration. The middle layer is these -- our traditional physically accurate tools, ground truth and bottom layer is compute and data. So the recent news just confirms that framework. And by the way, this will happen in all markets. The value of AI will go more and more vertical than horizontal. -- and I've said this for a long time. So even in chip design, the value is in the Agentic framework and all the mental model, all the knowledge graphs, then calling the physically accurate tools on a rich set of hardware. And this latest news in case of Kimi doing that, I mean, I think that the -- I mean, they said a chip, but I think it's a small block, which is about technology, which is like 20 years old on frequency that is 20, 30x lower than current frequency. So even to design a small block at such an old node, they needed kind of EDA tools to do that. So this is going to happen again and again. And there is -- there have been open source EDA tools for a while, I don't know, for decades, and they're used in some university or specialized settings. But to really do real designs, people use Cadence to do that. Now the differentiation will be in all three. We want to differentiate in all three parts of the cake. So our Knowledge Graph and our mental model and how we do the reinforcement loops at the agents is really differentiated. How we call then the middle layer through deep API access and the strength of our middle traditional tools is differentiated. And then even in the bottom layer, as you know, we have Palladium, we have Millennium, we have special hardware to do that. So our differentiation will be in all three. And then all three together, we are more differentiated than we have ever been. So I'm very proud of our differentiation of the moat we have. And then the fact that these three layers will reinforce each other. Now the customers may always have their own agents, just like they have their own flows right now. But to really do mission-critical tasks, they increasingly depend on Cadence as you're seeing that in our engagements.

Yes. Joe, Anirudh has always said that like Agentic AI actually increases demand because agents invoke EDA tools continuously while exploring more design alternatives and Kimi was a really good example of that.

And our next question comes from the line of Vivek Arya with Bank of America Securities.

I know the IP business has accelerated to over 40% growth. I'm curious what's driving this? How much is organic versus inorganic? And what is kind of the sustainable growth rate for IP? And then if we zoom out, I just wanted to clarify with John, what the contribution is now with Hexagon and the EPS dilution.

Yes. John, do you want to start on that? Yes.

Yes, sure, sure. Just in terms of Hexagon contribution, I mean, Hexagon is delivering as we originally expected, and it continues to contribute to SD&A growth, but the strength in our SD&A numbers is much broader. We're seeing momentum in 3D-IC in advanced packaging in PCB, multiphysics and physical AI. And the integration of Hexagon D&E is progressing well, and we see a significant opportunity to strengthen both the technology portfolio and go-to-market over time. But yes, also, I guess, on the IP side, IP had an outstanding quarter, driven by AI, HPC, advanced node activity, memory bandwidth, chiplets and advanced packaging. There were strong customer engagements and meaningful wins, but IP revenue can be timing dependent from quarter-to-quarter. we're pleased with the momentum. But I wouldn't annualize anyone forte. Our competitive position continues strengthening across interface IP, memory IP and foundation IP. Intel, as Anirudh called out, it represents another example of customers choosing broader strategic engagement with us. Anirudh, would you like to add?

Yes, absolutely. Yes. Thanks, John. So, Vivek, very pleased with the IP performance and SDA performance. I mean before I get into specific IP, the good thing is, I mean, these things are growing. Of course, IP is growing very well. SDA is growing very well, but also they have enough scale now. So, EDA, we are always I believe, the leading EDA provider with analog, digital verification, packaging, 3D-IC. But both our -- roughly speaking, both IP and SDA are approaching like $1 billion run rate, okay? So at this point, it gives a lot of strength in our portfolio to engage with our customers. Now IP, particularly -- and I've mentioned this before, as you know, like I think there are three big megatrends. One is, of course, our IP is much better than before. The quality of our IP, the PPA, power performance in area for like TSMC and the leading nodes is better. So we are getting a lot of competitive wins in IP that two years ago, we would not participate in. So that's one thing. Second reason is our IP strategy is more focused, has always been focused and will continue to be focused to leading nodes to star IP to AI and HPC segments. So I've talked about these five key IPs, which interface IP, memory IP. And then we have expanded to foundation and other, but this especially chip-to-chip IP, memory IP, interface IPs are super critical, and they are growing well, okay? And then the third thing is there are more and more foundries we talked about Intel. I'm very proud of this new partnership with Intel and it's, of course, much broader than IP, but IP is a part of it. And then our engagement with Samsung, we mentioned last quarter and Rapidus. So the foundry ecosystem is much more diverse than before. So I think these three reasons, our IP business is doing phenomenal. And also, most of it is, just to clarify, is organic growth. I mean this great growth we posted, most of it is organic growth. Now how does it proceed in the future, we'll see, but all the signs are positive at this time.

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

Apologies for the background noise. I'm at DAC conference. And I can tell you the key theme here is Agentic AI, which kind of validated what you said. So, my key question is, you talked about some of this agent, Super Agent, ChipStack, ViraStack that your customers has been using. So wondering what kind of feedback you are getting and the cost saving and the value that you bring to the customer? And then I know, John, earlier, you talked about monetization, which might take contract renewal or cycle time. But as you see the usage, are you seeing any kind of accelerating adoption where the time line can be compressed?

Yes, Siti, the demand is great, like I mentioned, for these agents. And we have -- I mean, the exciting thing is that the use cases are -- I mean, we have publicly talked about so many of them and like 2x to 10x to, in some cases, 40x improvement. And this is only the ones that we can publicly talk about. This is a very small subset of our engagement. So the amount of use cases and the benefit is real, okay? And the interest is definitely real in terms of number of engagements and how many customers want to engage with us. And our strength of our portfolio with the Three-Layer Cake is very well differentiated. So I'm very pleased. I mean this is like we are maybe six months into our launch of these products. We launched them in Q1, but we're working, I would say, roughly six months with our customers. And we'll see how it progresses. But like I said, the early add-on business is encouraging, but we have to -- still in the early days. So we'll see how it goes. But so far, the demand is tremendous.

Yes, Siti, I think we view this as a demand accelerator. Customers are not trying to do any less design work. They're trying to keep up with design complexity, which is accelerating faster than engineering headcount and scale. We've always said that. As agents expand the design exploration space and call the underlying cadence engines more often, that creates opportunities for new Agentic workflow products and increased use of our core tools.

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

Continuing on the Agentic AI theme, could you maybe talk a little bit about some of the add-on engagements you're seeing for those tools? And to what extent you're seeing them across more than the sort of 20 to 25 customers you've already noted. And maybe if you could quantify the impact of those add-ons in terms of either the guidance raise or what it could mean for core EDA software revenue in the next year, that would be great.

Yes. I think like you know us, right, we are very careful about projecting future, next year numbers. But I think to step back a little bit, I think the three things that I'm super excited about is one is that the overall environment is much better. I mean this also helps us a lot. I mean not just the AI companies, the hyperscalers are -- I mean the commitment to silicon is much higher than like 12 months ago. And you can see that you're following all the hyperscalers. So the amount of designs and the number of designs each hyperscaler is doing is impressive. And then the AI semi companies are growing immensely. And then like the analog and memory and the consumer semi companies are also doing well now. So overall environment is much better than one year ago, which, of course, helps us, right? So that's number one. Number two, I think I just want to emphasize our competitive position, I feel, has never been better. So we are taking a lot of share in different customers, getting to much, much deeper engagements, whether it's Agentic AI or hardware or IP. And you can see that in the numbers. And then the third part is this new TAM expansion opportunity, which is Agentic, which we are clearly super excited about. We're still in the early stages. So if you combine those three things, I think that is what is leading to such good results and such good guidance. Just to remind you, this is the highest we have raised annual revenue in a single quarter, okay, and to about 19% revenue growth with improved profitability. So I think I would like to say that some of the benefit is already there of the Agentic and other next year and year after, I mean, you know us, we are prudent as ever, and we'll see how things progress.

Yes. Jim, I think just -- I know we get a lot of questions about Agentic AI, but I think it's important to highlight that the raise that we just did for Q2 for the rest of the year reflects broad-based strength across the business rather than any single customer or product. We saw strong Q2 execution across core EDA, IP, hardware and SD&A. That, of course, is all benefiting from continued strength in AI-driven demand as well. But the strength is broad-based across all businesses and across all regions.

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

Anirudh, as the volume of AI inferencing compute workloads surpassed training workloads in the second half of last year. And we know that inferencing is much more memory intensive, right? So we've seen this diversification of different types of memory architectures emerging to address inferencing. In addition to HBM DRAM, we've seen development of SRAM-based offload architectures. We've seen CXL-based conventional DRAM offload and even using enterprise SSD or flash-based memory, right? So given all of the focus on these memory architectures and memory controller architectures, is this translating into some tailwinds for your custom Virtuoso family of EDA tool solutions or tailwinds for your CXL-based or memory compiler IP portfolios or both?

Yes, Harlan, that's a great point. So yes, like John mentioned, the strength is broad-based. And definitely, the analog group, which is part of EDA, is also seeing very strong momentum because all of these -- whether it's memory or analog is all done and Virtuoso is the leading platform for analog and mixed signal and custom design in the industry. So I'm very pleased to see overall environment plus the special -- all this innovation that is driven by inferencing, helping both all our businesses, analog, digital and verification. But what is exciting to me in this -- I mean, you know this anyway, with this inferencing is that there is much more varied architectures you mentioned and also much more varied customers. So all the big customers believe at this point that, of course, they will use standard products from semiconductor companies, from the really big semiconductor companies like NVIDIA, who are doing great, but also believe that they will have their own custom silicon. And then on top of that, different versions of that custom silicon for memory access and also networking, right? There's a lot of activity in networking as well. And then I would say, like over the last six months, I see a lot more activity in start-ups. Start-ups were kind of dormant. But in the last six months, there are like some very high-profile start-ups that are starting, not just in AI, but in networking and even CPU, right? So I think the overall environment is good, and it is affecting all our businesses. Analog for sure, verification with hardware, IP business, digital implementation, 3D-IC is a big thing where we have leadership. So that's what leading to this broad-based trend. But the conviction of the hyperscalers to do their own silicon and try, like you pointed out, different architectures, and that's bound to happen. I mean if there is one bottleneck, the customers come up with different memory architectures to solve that bottleneck or different networking architecture. So I expect this to continue. I mean this is -- as the market gets bigger, you know that, as the AI infrastructure market gets bigger, there will be more and more innovation to optimize each part of that market. And all that innovation will require Cadence products to make that happen.

And the next question comes from the line of Charles Shi with Needham & Company.

Anirudh, I can ask about AI for 100 ways, but I think the most important question top of many people's mind right now or I should say, the scenario, a very extreme scenario that people fear about the most is where you actually prompt, I don't know when we could get that, but prompt on a very, very powerful LLM in the future with your chip design requirement, then that LLM can autonomously generate GDS II codes that get sent to foundry directly for tape-out without running them through any of the commercial EDA tools. So this is one of the scenarios that some people were envisioning. We strongly disagree, but do you think this end-to-end, so-called end-to-end LLM-based chip design is a real possibility at all or since you mentioned the Three-Layer Cake.

Yes, Charles, I mean, like I said -- I mean, before, I said this for years, the way this improvement will happen and of course, there will be a lot of improvements with will be through this Three-Layer Cake. So we will have agents like we have super agents. Our tools are central, will continue to be central to that. And of course, we'll run on a varied set of hardware. I don't see that changing. Of course, some people may get worried about it from time to time. But the ground truth will prevail, okay? This Three-Layer framework will prevail. And what -- if you talk about commoditization, I mean, I think what is likely to happen is not the EDA tools get commoditized. What is likely to happen is at the Agentic layer, there will be a lot of choices for LLM. So if you look at what is really happening right now in the marketplace is that the customers are demanding choice in their LLMs. And so -- which is Kimi is an example of that and GLM 5.2 and Nemotron, of course, great release by NVIDIA and then all the commercial models. So what the customers are asking me is like, can you -- can the agent be more intelligent in choosing the right model for the right task given the rapid progress in the LLMs. I think that's most likely to happen. But the Three-Layer framework, criticality of our tools will be here to stay.