Image source: The Motley Fool.

DATE

Monday, Oct. 26, 2026

CALL PARTICIPANTS

• Vice President of Investor Relations - Richard Gu
• President and Chief Executive Officer - Anirudh Devgan
• Senior Vice President and Chief Financial Officer - John Wall

TAKEAWAYS

• Revenue -- $1.633 billion, representing 22% growth driven by strong double-digit expansion across all product groups.
• Non-GAAP EPS -- $2.11, compared to $1.93 in the third quarter of 2025.
• Backlog -- $8.2 billion, a record level reflecting robust bookings and increased customer demand for AI-driven design.
• Recurring Revenue -- 18% growth, representing an acceleration from the 11% growth rate reported in the prior year.
• Core EDA Revenue -- 20% growth, fueled by broad-based strength across the digital and verification portfolios.
• Semiconductor IP Revenue -- 24% growth, driven by investments in AI infrastructure and high-performance IP for advanced nodes.
• System Design and Analysis Revenue -- 30% growth, reflecting adoption of integrated solutions and the Millennium platform.
• GAAP Operating Margin -- 26.2%, compared to 31.8% in the prior-year period.
• Non-GAAP Operating Margin -- 44.1%, exceeding internal guidance for the quarter.
• Cash and Cash Equivalents -- $1.452 billion at the end of the third quarter.
• Principal Debt Value -- $2.65 billion, compared to total current liabilities of $2.466 billion.
• Share Repurchases -- $400 million during the quarter, with an additional $2.5 billion newly authorized by the board.
• Full-Year Revenue Guidance -- $6.387 billion to $6.417 billion, raised to reflect 21% growth at the midpoint.
• Full-Year Non-GAAP EPS Guidance -- $8.37 to $8.43, with the midpoint raised to $8.40.
• Full-Year Operating Margin Guidance -- 44.2% to 45.2% on a non-GAAP basis for fiscal 2026.
• Operating Cash Flow Guidance -- approximately $2 billion expected for the full fiscal year.
• Maestro Performance -- 30% higher quality and fivefold greater token efficiency compared to general-purpose foundation models.
• RTL Area Optimization -- 24% area reduction and 18% power reduction achieved by the new ChipStack agent versus foundation-model-generated code.
• Verification Coverage Improvement -- 50% to 70% increase in coverage for MediaTek following the deployment of ChipStack.
• Renesas Productivity -- 34-fold improvement in MCU team productivity after deploying the InnoStack agentic AI solution.
• Inventory -- $448.8 million, up from $303.5 million at the end of 2025 to support growing hardware platform orders.
• Twelve-Month Revenue Backlog -- $4.2 billion, representing the portion of performance obligations to be recognized within the next year.
• Diluted Shares Outstanding -- 275,278,000 weighted average shares used for non-GAAP calculations during the quarter.
• Days Sales Outstanding -- 66 days at the end of the third quarter.

Need a quote from a Motley Fool analyst? Email [email protected]

RISKS

• John Wall stated, "[the outlook] contains the usual assumption that export control regulations that exist today remain substantially similar for the remainder of the year," noting the company's reliance on a stable regulatory environment.
• Wall indicated that the Hexagon D&E acquisition is currently having a minimal impact on operating profit, with more significant financial contributions not expected until the next fiscal year.

SUMMARY

Cadence Design Systems, Inc. (CDNS +3.31%) reported third-quarter results that surpassed management's guidance across all primary financial metrics, supported by record backlog and accelerating demand for artificial intelligence infrastructure. The company increased its full-year projections for revenue and earnings per share, reflecting business momentum in its core software and hardware platforms. Strategic developments during the quarter included the introduction of the Maestro portfolio of domain-specialized AI models and the expansion of the agentic AI super agent framework. Segment performance remained strong, with double-digit growth in Electronic Design Automation, Intellectual Property, and System Design and Analysis as system companies increasingly pursue custom silicon and electromechanical system intelligence.

• CEO Anirudh Devgan introduced Maestro, noting, "The future of Agentic AI based design is increasingly domain specialized models," which are designed for recursive self-improvement through reinforcement learning loops.
• Management highlighted that chip sizes are projected to increase 48-fold over the next five years, driving sustained demand for Palladium and Protium hardware-assisted verification platforms.
• Management reported that 45% of total business now originates from system companies, including marquee expansions with global telecommunications and space technology providers.
• The company reported more than 100 active customer engagements for its agentic AI super agents, including successful production deployments at MediaTek, Samsung Foundry, and Nokia.
• Devgan stated that Maestro "gives maximum flexibility" by allowing customers to deploy models in the cloud or in their own secure on-premise environments.
• CFO John Wall noted that the board authorized an additional $2.5 billion for share repurchases, underlining the company's "commitment to returning capital to shareholders."

INDUSTRY GLOSSARY

• Maestro: A portfolio of domain-specialized AI models purpose-built by Cadence for chip and system design.
• Palladium: An enterprise-grade hardware emulation platform used for high-speed functional verification of complex chip designs.
• Protium: A FPGA-based prototyping platform designed to accelerate software development and system validation.
• EDA: Electronic Design Automation, software and hardware tools used to design and verify integrated circuits.
• PPA: Power, Performance, and Area; the three critical metrics used to evaluate the efficiency and quality of semiconductor designs.
• SD&A: System Design and Analysis, a segment focused on PCB design, packaging, and multi-physics analysis.
• DTCO: Design Technology Co-Optimization, a process to improve semiconductor performance by simultaneously optimizing design and manufacturing processes.
• RTL: Register Transfer Level, a high-level representation used in the digital design of integrated circuits.
• MCU: Microcontroller Unit, a compact integrated circuit designed to govern a specific operation in an embedded system.
• 3D-IC: Three-Dimensional Integrated Circuit, a design architecture that stacks multiple silicon wafers or dies vertically.

Full Conference Call Transcript

Operator: Good afternoon. My name is James, and I will be your conference operator today. At this time, I would like to welcome everyone to the Cadence third quarter 20 Earnings Conference Call. All lines have been placed on mute to prevent any background noise. After the speakers' remarks, there will be a question-and-answer session. If you would like to ask a question during this time, simply press star then the number 1 on your telephone keypad. Thank you. 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 26 earnings conference call. I am 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, operating results. Due to risks and uncertainties, actual results may differ materially from those projected or implied. 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 1 question only. If time permits, you can re queue. Additional questions. Now I will turn the call over to Anirudh.

Anirudh Devgan: Thank you, Richard. Good afternoon, everyone. And thank you for joining us today. I am pleased to report that Cadence delivered another outstanding quarter. With all key metrics, coming in well above our guidance. Backlog reached a record of $8.2 billion. Reflecting strong bookings driven by growing customer demand. Given our business momentum, expanding technology leadership, and compelling AI growth opportunities, we are raising our revenue outlook for the year to 21% growth and our EPS outlook by $0.30 to $8.40. John will provide more details on both our Q3 results and the updated financial outlook. Agentic AI represents a transformational market opportunity. And Cadence is exceptionally well positioned to capitalize on it.

Our differentiated 3 layer framework is anchored by our physically accurate simulation and optimization engine in the critical middle layer. Tightly integrated with AI agents and orchestration at the top, and accelerated compute and propriety data at the base. Agentic AI continues to evolve a remarkable pace. With our AI super agents gaining strong traction. We are now addressing the long standing customer demand for domain specialized models. We believe the future of Agentic AI based design is increasingly domain specialized models. Combined with intelligent model routing for performance, and reinforcement learning loops with underlying tools for recursive self improvement. Today, I am excited to introduce Maestro.

A portfolio of domain specialized AI models purpose build, for chip and system design. By controlling all 3 layers, our AI super agent, Maestro models, and proven EDA and SDA tools, we are uniquely positioned to deliver optimal performance efficiency, and throughput results for our customers. Initial results are very compelling. Demonstrating up to 30% higher quality and up to 5x greater token efficiency versus general purpose foundation model. Moreover, the Maestro models can be further post trained on customers' proprietary data to deliver even better outcomes. Our model router chooses among our models and other leading year and open rate models as needed for optimal results.

Customers can opt to deploy Maestro models in the cloud or in their on prem environment. Maestro is gaining strong early customer traction. With several deployments underway. Momentum of our AI super agents continues to accelerate. With compelling early results and more than 100 active customer engagements. We added a new agent to ChipStack. For our deal generation and early PPA optimization. That created RTL delivering average of 24% area and 18% power reduction. Versus pure foundation-model-generated code. Importantly, this demonstrates the power of combining our AI super agents with AI models and our underlying EDA engine. To achieve outcomes that foundation models alone cannot deliver.

Honda is using the RTL generation and AI-powered automation to improve productivity, from specification to RTL development. In Q3, MediaTek deployed chip stack into its production digital verification flow. Achieving 50% to 70% improvement in verification coverage, and 1.4x to 2x reduction in engineering effort. With deployment now scaling across design teams. In analog and custom design, ViraStack saw a 4x increase in customer engagement. with deployments in various production designs at multiple customers, The combination of agentic workflow, embedded skills, and our Virtuoso platform is unlocking significant new productivity opportunities in a traditionally difficult to automate domain. We are seeing strong customer interest in InnoStack. Our digital AI super agent.

At customers' push to improve PPA, accelerate design closure, and boost productivity. In Q3, the Renesas MCU team successfully deployed InnoStack across a wide range of engineering tasks. Achieving a 34x productivity improvement with plans to expand its usage to layout automation. Also in Q3, Samsung Foundry successfully used InnoStack to dramatically improve engineering efficiency and accelerate PPA exploration. reshaping its approach to technology migration and DTCO optimization. Socionext is deploying InnoStack in its production design environment. And expects its combination with our advanced physical design tools to deliver up to a 5x overall productivity gain while maintaining design quality. In PCB and 3D-IC design, the early response to our AuraStack AI super agent. Has been overwhelmingly positive.

Nokia is deploying AuraStack on our Millennium supercomputer. To advance electronic system design at scale. By unifying Agentic AI, our physics based solvers, and accelerated compute in a secure on prem platform. Nokia is achieving a 5x acceleration in key design and analysis workflows. Moving on to our businesses. We are delighted that all product groups delivered outstanding results. With year over year revenue growth of 20% in core EDA, 24% in IP, and 30% in SD&A. Accelerating design activity continues to drive strong demand for our core EDA SDA, and IP products. At the same time, we are seeing amazing customer momentum for our Agentic AI portfolio. Which is also fueling increased demand for our underlying products.

We are pleased that recurring revenue sustained its strong momentum. growing 18% year over year. I am particularly proud of the significant wide ranging agreement we have signed with top customers. We furthered our long standing partnership with a global marquee systems customer through a significant wide ranging expansion of our core EDA hardware and SDA solutions. In Q3, Cadence and a top telco deepened their long term strategic partnership. With a broad expansion across our AI offering EDA software, hardware, and SD&A solutions. Establishing cadence, as their primary design partner. Core EDA revenue growth was driven by broad based strength across the portfolio. Our digital and sign up business continued to expand.

Achieving 16 new full flow wins during the quarter. As agentic flows increasingly require full vertical workflows. There is growing demand for our synthesis and sign off solution. Our sign off product saw growing adoption. And our verification software product had strong growth in big digital and memory design. With increasing usage at major hyperscaler and memory companies. As AI and HPC designs, continue to grow in scale and complexity, hardware assisted verification, has become an increasingly strategic capability for our customers. This is driving sustained unprecedented demand for our palladium and proteome emulation platforms. Which delivered yet another record quarter. We added several new logos and saw a meaningful expansion with marquee customers. Across a wide range of verticals.

Our hardware cloud offering showed strong growth. With a leading semiconductor company adopting more hardware cloud services to accelerate new product development. In analog and custom design, SpectreFX continues to gain momentum. Highlighted by major competitive displacement. At a marquee infrastructure silicon provider. With multiple new 2-nanometer projects adopting our platform. Our IP business delivered another outstanding quarter. Driven by deepening engagements with leading hyperscalers and semi customers. We continue to benefit from strong AI driven tailwinds. Fueling accelerating AI infrastructure investments growing adoption of custom silicon, and increasing demand for high performance IP.

Along with the transition to advanced nodes, and chiplet based architectures, These AI driven trends are creating a strong pull for a differentiated star IP portfolio, across interface memory, and foundation IP. We are well positioned for sustained growth as we continue to deliver superior power performance, area across our expanding advanced IP portfolio. A leading space technology company. Selected our IP portfolio for their custom chip program. Paving the way for a broader services and silicon engagement. Tensilica delivered a record revenue quarter and we announced a joint development with Analog Devices across next generation audio applications. Our system design and analysis business delivered another strong quarter.

Driven by growing adoption of our integrated solutions and proliferation of our expanded electronics and physical systems intelligence portfolio. Allegro momentum continued. Including a competitive displacement at a leading EV customer. That shows Cadence's integrated PCB design and multiphysics analysis platform as its primary solution. Our Millennium platform had strong adoption driven by deployment of our GPU accelerated electronic mechanical system suite. Along with our reality digital twin solution. During the quarter, Switch a leader in sustainable high density AI infrastructure. Selected are Millennium and Reality Digital Twin solutions to advance the design and simulation of its next generation AI factory. The MSC business is an integral part of our physical AI strategy. And its integration is progressing well.

MSC Adams, our industry leading multi body dynamic solution. Help secure a competitive displacement at a leading power company along with adoption of other Cadence products. In summary, Cadence delivered exceptional Q3, and I am delighted with the accelerating momentum of our business. We are executing extremely well. in a vibrant AI market, have our strongest competitive position ever, and are extending our leadership in AI. Our highly recurring and ratable business model, combined with growing customer R&D investments. Is positioning us very well for continued strength in this dynamic AI environment. With that, I will turn it over to John. To provide more details on our Q3 results and our updated 2026 outlook.

John Wall: Thanks, and good afternoon, everyone. Cadence delivered strong third quarter results driven by robust demand across our businesses, and growing momentum from AI driven designs. Growth is accelerating and broad-based. Q3 revenue grew 22% year over year with strong double digit growth across all product groups. We exceeded our guidance on every key financial metric, and ended the quarter with record backlog of $8.2 billion Here are some of the financial highlights from the third quarter starting with the P&L. Total revenue was $1.633 billion. GAAP operating margin was 26.2%, Non GAAP operating margin was 44.1%. GAAP EPS was $1.05. Non GAAP EPS was $2.11. Next, turning to the balance sheet and cash flow.

Our cash balance was $1.452 billion, while the principal value of debt outstanding was $2.65 billion. Operating cash flow was $424 million. DSOs were 66 days, and we used $400 million to repurchase Cadence shares during the quarter reflecting our confidence in the business and our commitment to returning capital to shareholders. Underscoring that commitment, our board has authorized an additional $2.5 billion for our share repurchase program. Before I provide our updated outlook, I would 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.

For our updated outlook for 2026, we now expect revenue in the range of $6.387 billion to $6.417 billion GAAP operating margin in the range of 28.2% to 29.2%, Non GAAP operating margin in the range of 44.2% to 45.2%, GAAP EPS in the range of $4.84 to $4.90. Non-GAAP EPS, in the range of $8.37 to $8.43. Operating cash flow of approximately $2 billion and we expect to use more than 50% of our free cash flow to repurchase Cadence shares in 2026. For Q4, we expect revenue in the range of $1.695 billion to $1.725 billion.

GAAP operating margin in the range of 30% to 31%, Non GAAP operating margin in the range of 44% to 45%, GAAP EPS in the range of $1.23 to $1.29 and non GAAP EPS in the range of $2.19 to $2.25 And as usual, we published a CFO commentary doc on our investor relations website which includes our outlook for additional items as well as further analysis and GAAP to non GAAP reconciliations. Overall, I am pleased with our Q3 results especially our recurring revenue growth of 18% year-over-year. At the midpoint of our updated 2026 outlook, we now expect revenue growth of 21% operating margin of 44.7%, and EPS of $8.40.

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

Operator: Thank you. At this time, I would like to remind everyone who wants to ask a question to please press star then the number 1 on your telephone keypad. We ask that you pick up your handset when asking a question to allow for optimum sound quality. And if you are muted locally, please remember to unmute your device. As a courtesy to all participants, we ask that you limit yourself to 1 question. We will pause for a moment to compile the Q&A roster. Your first question comes from the line of Jason Celino from KeyBanc Capital Markets. Please go ahead.

Jason Celino: Thank you for taking my question. Anirudh, it is really nice to see the Maestro, announcement. I am not an EDA engineer. I am not an AI scientist. So maybe can you just explain what this is a little bit better? It sounds like it is part model router, but also maybe domain specific models. So is Cadence developing these domain-specific models? Maybe just elaborate and then, how monetization of this product will work. Thank you.

Anirudh Devgan: Yeah. Hi, Jason. Thank you for the question. there is a lot in that release. So let me try to unpack it a little bit. You know, first of all, you know, we are we are very pleased with the momentum of our agent stack and all the 4 super agents. And you can see there are, like, more than 100 engagements now. So as we work with customers over the last, you know, 6 to 9 months, and the several trends became pretty clear. Okay? And to me, you know, we are launching Maestro as what I would call the next generation of agents. And there are 3 you know, big factors in the next generation of agents.

So 1 is, you know, like, what has happened in the last 1 year is that of course, we worked with all the Frontier Labs from the very beginning. You know, whether they are doing chip design themselves or we are using their LLMs. For over the last 1 year, there is this emergence of very, very good open-weight rate models. Okay? And I always wanted to do, like, domain specialized models. But now it is finally possible with open rate models. And it is actually very cost effective to post train these models. To deliver, like, domains intelligence, which is which is remarkable. Now we are getting up to 30% better quality.

By using our tools and data to post train these models. And, also, you do not need, like. it is a portfolio of models. So all the way to, like, small decision LMs, to small and medium LLMs all the way up to, you know, frontier class open weight models post trained on our data and intelligence. So that is the first part of Maestro. So it gives really, you know, customization for chip and system design. And gives much, much better results. it is actually quite remarkable how much these models can be improved by post training. Okay. Now the second part of that is the. In our agents, when they do these tasks, have variety of tasks. Right?

So we do not need only 1 size or type of model to do the task. So the second part is model routing. You know, just like you do not need to use the airplane to go to your local grocery store. Right? So similar deal with agents. You have a variety of tasks that we need to do from simple task to, like, deep thinking. And reasoning task. So the model router will efficiently knowing what the task is from our super agents, use the right model. And that can easily give, like, up to 5x improvement in token efficiency. So either much lower cost much more work for the same cost.

And then the third thing, is which I always talked about, this reinforcement learning loop with the underlying tools. And we have great example. For example, we talked about our new RTL agent. That, you know, 1 of the customers publicly endorsed Honda, gave 24% area and 18% power because the integration with the underlying tools, how we call them and continuous self improvement, you know, whether it is skills or models, gives us a unique advantage.

So if you combine these 3 things together, you know, domain specialized model, domain specialized family of models, plus model routing, plus deep integration with our tools and data, gives a unique differentiation that nobody else can do, and it also allows us to control all 3 layers of the cake and innovate in all 3 layers of the cake. So I am actually super excited, and I think this is what is going to happen in all industries. As these LLMs mature, you know, this domain specialized intelligence routing and integration with underlying engines.

Operator: Your next question comes from the line of Jim Schneider from Goldman Sachs. Please go ahead.

Jim Schneider: Good afternoon. Thanks for taking my question. I was wondering if you can maybe give us an update on the monetization of the Agentic AI solutions you are seeing. I believe last quarter you talked about recurring revenue growth of 20%, this quarter was 18%. Maybe talk about what the difference there in the recurring was? And maybe underlying that, whether there was any acceleration in the in the agentic part of that recurring revenue? Thank you.

Anirudh Devgan: Yeah. Thanks for the question. I will start, and then John can comment. You know, the I am I am very proud of the recurring growth. and I mean, this quarter, there were some specific things, like you compare it to Q3 of last year, there were some specific things with China revenue moving around. is not there this year. But in general, recurring revenue is doing phenomenally well. And if you step back and compare last year, recurring revenue was 11%. And, you know, it is 18%. For this quarter, and it was very good last quarter. So I expect recurring revenue to do very well in 2026.

And this is a result of course, our agentic AI solutions, but also agentic AI solutions driving more usage of our base tools, which is we always said, is going to happen. So that is what we see. You know, a lot of engagement is agentic. And a lot of usage of our base tools. So that provides a lot of growth for recurring and then you add that with, our ongoing strength in IP and hardware. And you get a very, very good set of results.

John Wall: Yeah. I would agree with that, Anirudh. I mean, it is basically a reflection of strong demand our software portfolio and healthy customer expansions and continued strength in core EDA. Yeah. I think that is the way to look at it in terms of strong IT growth to recurring revenue. We are very pleased with this. Your next question comes from the line of Vivek Arya from Bank of America Securities.

Operator: Please go ahead.

Vivek Arya: Thanks for taking my question. Anirudh, we recently heard 3 things from your competitor that they can grow sales at a mid-teens pace next year and then compounded to 30%, that they can achieve 50% of the margins. And then also, interestingly, there is a royalty based model that can help add nearly a billion dollars to their top line over the next several years.

So I realize, right, this is not the call to a multiyear growth outlook, but I was just hoping to get your perspective on how you envision sort of this growth and royalty component for Cadence and how well is Cadence positioned to maintain or expand your, market share and your leading operating margins over time? Thank you.

Anirudh Devgan: Yeah. Thanks for the question, Vivek. So overall, I am very pleased with our growth and not just growth, but profitability and margin. And, we always talk about, like, the rule of 40 metrics or revenue growth plus margin. So I think we will end the year, if you look at our guide, about 21% revenue growth slightly less than 45% margin. So we will end up north of 65 in 2026. Okay? that is the important thing to point out. Okay. And we still have 1 more quarter to go. So we will see. it is an important quarter for us. Fourth quarter is always important.

So we will see how that finishes, and we can update you like we usually do in February for the next year. But overall, the environment, I think, is very positive for us. You know? As you know, the customer AI build-out continues. there is an amount of design activity in all aspects of AI and even the traditional companies and analog mixed signal companies, digital company, memory companies, system companies. So the amount of design activity is the strongest that I have seen. Our. You know, we are gaining share in almost all segments of our business. Whether it is IP or hardware or EDA, or agentic AI.

So our product portfolio, I think, is strongest it has ever been. Then we have this huge opportunity with AgenTiC AI. And I think we are we are redoing, you know, how Agentic AI will be defined for all industries. With our own domain specialized models and the flexibility to continue to work with all the frontier models. So if you look at all these 3 things, I feel Cadence is in a very, very strong position. In terms of your specific question on royalty, we are always looking at different kinds of business models. So in IP, we always had royalty for a while in Tensilica. And now we have royalty in our design IP business as well.

But to me, that is just 1 vector. You know, we are always looking at how to best serve. value to our customers and then get, of course, value in return.

Operator: Your next question comes from the line of Siti Panigrahi from Mizuho. Please go ahead.

Siti Panigrahi: Thank you. Congrats on a good quarter. I just want to ask on hardware. I see even the inventory again grew this quarter. I am wondering, How did it have a strong quarter? How sustainable hardware growth heading into next year, 2027? Any color would be helpful there and quick clarification, John. There was a spike in, G&A expense in Q3. Was there any. Anything 1-time there? Thank you.

John Wall: Yes. Sure, Siti. Great. Look. I will take the hardware question first. Yeah. Hardware continues to perform exceptionally well. We delivered another record quarter supported by strong demand from AI and HPC customers, and we are also seeing growing interest in cloud based hardware access The hardware assisted verification is becoming increasingly important because customers are designing systems of unprecedented complexity and they need the capacity to verify those designs before committing to silicon. We have a strong pipeline entering Q4, and we continue to expect another record year for hardware. As always, hardware could be lumpy from quarter to quarter to quarter depending on product deliveries and customer installation schedules.

With the underlying demand environment, remains very strong, very healthy, and we are very, very encouraged by the pipeline of customer engagement. The. In terms of inventory, the increase in hardware inventories to support customer orders that we have a significant backlog that we are we are trying to work our way through. But there are no capacity or supply chain constraints in terms of addressing that. We are just building inventory to hit that. To hit those numbers. I think you asked about G and A. that is in part of the court movement. This quarter reflects the timing of annual charitable contributions which occurred in Q3 this year compared to Q4 last year.

I would extrapolate that timing difference into the underlying G and A run rate. So there is a slight impact in G&A in Q3 because of that. Those charitable contributions.

Anirudh Devgan: Yeah. And, Siti, just to add on the hardware piece. I mean, palladium and proteome performing exceptionally well. You know, not just for AI, of course, we are working with all the major AI companies, but also, even any other kind of chip design right now, hardware became an indispensable, almost indispensable way to design these things. Now 1 thing you will always ask, will this trend continue? And we will see, but there is 1 megatrend. Okay? So, as you know, hardware is. You probably know this already, but just to highlight it even further. Hardware is normally sold or consumed based on design side. So if the design size is bigger, then you need more and more hardware.

So, actually, I was recently. Just the example of what is gonna happen to design size? The design sizes are already big. But what is gonna happen to design size in the future? So just to give you an example, I was at imec recently. I gave a talk at imec, which is a European research consortium. And TSMC also gave a talk, same session. So TSMC showed their process road map and said in the next 5 years, the chip size will go up by 48x. 48x. Now, typically, this would happen to be, like, 5x to 10x. In the old days.

I think it is going to be 48x because you have to add regular technology scaling plus 3D-IC. So all these 3D-IC packaging wafer scale integration So that is going to even further create more and more demand for hardware. And, you know, die to die IP and things like that. But so now our customers are not only verifying 1 chip or 1 chiplet. They are verifying those chiplet working with other chiplets, and the size of the chiplets is going up and then amount of chiplets are going up. So I think this trend, you know, 1 criticality of hardware based design verification combined with the growth in size is going to continue for some time.

Operator: Your next question comes from the line of Joe Quatrochi from Wells Fargo. Please go ahead.

Joe Quatrochi: Yeah. Thanks for taking the question. I was curious if you could just kind of talk about the change in the 2026 outlook, particularly from an operating profit perspective. Because I think when you flow through just kind of the incremental margin on the upside and revenue, it is quite significant relative to maybe your kind of targeted over 50%. So maybe just any help there in terms of understanding what is going on there.

John Wall: Sure. Yeah. Yeah. Look. We continue to be very pleased with the underlying profitability of the business. And despite integrating the Hexagon's D and D business and making targeted investments in our strategic growth opportunities. We are we are now expecting approximately 44.7% non GAAP operating margin for 2026, which is slightly above last year. But if you look at the revenue growth this year over last year, it is about 1.1 billion Non GAAP operating profit is growing about $500 billion. And when you consider the Hexagon D&E being part of it. that is not really contributing much in the way of operating profit at all this year. But.

And I think we said at the start of the year, we were expecting D&E to be about 160 million for the year. it is doing slightly better than that. But it is it is pretty much on target. But, I mean, if you took that out, we would be where you typically expect us to be, which is kind of mid teens for revenue growth, high teens for EPS growth, and, you know, with our. In our usual kind of 54%, 55% incremental margin range. So the so the extra D&E is kind of impacting the incremental margin for this year. But we would expect that to help us next year because the integration has gone really well.

And we are we are taking steps now to improve things for next year in the same way as we did with Aeva the last couple of years.

Operator: Your next question comes from the line of Charles Shi from Needham and Company. Please go ahead.

Charles Shi: Oh, thanks for taking my question. Hey, Anirudh. Glad to hear about the Maestro model. Portfolio just announced today. In light of your competitor who announced the GPT synopsis, can you tell us what your thoughts are regarding collaborating maybe with the Frontier Labs for a specialized model, like that, Maestro, based on what you just described, it sounds like it is a collection of open models post trained by Cadence. And I think a network customers also have choices between your model of portfolio and the, let's say, Synopsys, what do you tell your customers when they have both choices and why they should pick cadence? Thank you.

Anirudh Devgan: Thanks for the question, Charles. So first of all, I just want to point out that we have worked with OpenAI from the very beginning of when they got started.? So in terms of chip design, and we have all kinds of, you know, collaborations with OpenAI. Okay. And same thing with Anthropic and Gemini, the 3 leading frontier models. So we always discuss all kinds of collaborations with them. Now in terms of what we want to make sure as we. And Maestro, the key thing is Maestro is not just our own models, but still has maximum flexibility. To use the right model for the right task. So let's say, if certain.

For certain percentage of the task, you know, certain frontier model is better, we will, of course, use that. To give the best performance to our customers. The key thing in our solution is that we want to control the 3 layers of the cake and we want to control the interaction with our customers. We want to be the primary interface to our customers, which is what our customers want. And in return, our agents will provide them a lot of value, and we will use the right LLM for the task.? But the critical thing is as we became the primary interface, and we guarantee the confidentiality of our data and their data.

The other thing we will allow with Maestro is if a customer wants to post train Maestro further, this is another request from our customers, we will allow that. If the customers want to have it on prem, we will allow that. If the customer wants to host on the cloud, we will allow that. Okay. So it gives maximum flexibility and maximum performance by combining all 3 layers, and only Cadence can provide this. And that will give, without any doubt, the best results for our customers. Okay.

Operator: Your next question comes from the line of Harlan Sur from JPMorgan. Please go ahead.

Harlan Sur: Good afternoon. Thanks for taking my question. I do not know, last quarter, you mentioned the pickup in the more traditional analog power, micro controller segments of the market, right, targeting industrial, automotive, consumer, IoT. that is the positive cyclical dynamics we are seeing now as excess customer inventories have bottomed in these end markets. Are you continuing to see the positive demand trends in this segment? And you know, these same companies are now very focused on embedding next generation physical AI based capabilities into their chip designs. Right?

Your MCU customers, for example, are adding NPU capabilities to their chip designs, your analog customers, are designing more sensor related capabilities into their chip, more A-to-D, VLA converters, on chip DSP processing, Is this also translating into a better book of business for the Cadence team?

Anirudh Devgan: Yes, Harlan. that is a great point. So the I think the momentum is very strong in analog and mixed signal, and you can look at their results as well. You know, driven by physical AI and overall recovery of the market. Of course, memory, which we work with all the big memory companies is having, you know, of course, amazing from a year or 2 ago. I think what it shows up is. You know, first of all, we are very, very strong in mixed-signal companies. Because we have the most complete portfolio with both analog and digital, So these are designs, like you mentioned, are more and more mixed-signal, so that plays to Cadence's strength and also, ViraStack.

You know, I am really pleased by the momentum in ViraStack. Because as analog customers, whether they are mixed signal companies or, you know, these big AI companies also have huge analog team. I do not know if you realize that. Some of these big AI companies, designing their own, IPs and all that, have huge analog teams. So there is a massive demand for analog productivity, which we could not provide earlier I mean, we always wanted to, but, with agentic AI now, we can do a lot more in analog productivity. And you can see that some of the, the customer codes we have seen, and the amount of engagements we have with ViraStack.

So overall, I am pretty pleased, just with the environment of analog mixed signal, but also the new capabilities we are launching with ViraStack.

Operator: Your next question comes from the line of Joe Vruwink from Baird. 1 moment, please go ahead. Joe Vruink, a reminder to unmute your device. Your line is open. Moving on for now. Your next question comes from the line of Lee Simpson from Morgan Stanley. Please go ahead.

Lee Simpson: Great. Thanks for fitting me in here. Anirudh, it does seem as though your. And your peer are pursuing very distinct routes to monetizing agentic AI in chip design. I mean, I thought you answered the. 1 of the previous questions quite well. It really does ring out that you are looking to have your own control on the modeling, Your deployment flexibility comes through. So you can see that adoption as you see it versus a frontier-model-centric partnership. Is something you think will gain quite good adoption. But is there something in the performance that we need to better appreciate or even in the delivery cost that really led you to go down this route? In strategy?

And maybe just a follow-up question. You did mention that a leading space company was adopting some of your IP. Just wonder if there is anything specific to call out there. Are they taking just typical IP blocks, or does it come with any broader IP services attached? Thanks.

Anirudh Devgan: Yeah. Lee, let me answer the second part first and come back to the first 1. I mean, in general, I have mentioned that now 45% of our business is coming from the system companies, the nontraditional versus the traditional semis. So these are new customers. And what is also encouraging to see is that it is not just the big AI you know, hyperscalers where they are doing design. But we are seeing lot of other system companies, like the 1 we highlighted, like, space company. Even companies in finance doing their own chips. Okay. This is.

As we make chip design easier and easier, this is always the promise that more and more companies will do that And when these new companies do design, we naturally have IP opportunities, but also hardware and also naturally design services. Because they are getting started and we have 1 of the best design services capabilities as we are the best at using our own, products. So I think this is a space we have to watch, but I am pretty encouraged by, more systems companies doing chip design.

John Wall: Now in coming back to the AI solution, you know, we want to have control, and we want to give flexibility to our customers. So this is the right way to look at it. So, and there is a lot of value in the model itself. It is actually pretty cost economical to post train a frontier class model. Okay. This could not have happened, like, 2 years ago. But now it is actually pretty manageable cost, and you get pretty remarkable results, like I mentioned. By very incremental cost to post train a frontier model.

And, of course, that is the important thing to have in the bag along with a commercially available frontier model. it is just choosing the best solution of the 2. And then in our own agentic development, right, we have our own IP team. You know, a lot of people using our of course, using agent stack and all the solutions. So the benefits of cost apply to us as well. So even though there is some you know, incremental expense to train them, there is also incremental saving in our own deployment of AI. So overall, I think it should not affect any financial model of Cadence.

It only gets stronger as we add, like, a new kind of revenue capability and all the margin progression and all should go as we have planned for a while. But, you know, what Maestro does is this flexibility, but also gives customization ability. It gives control. And then it gives cost saving. So this is best of all words. Yeah. Lee, I. If I could add there, I think that is a very, very important point that Anirudh makes in terms of the flexibility. We really want customers to have choice and control over the models they use while benefiting from Cadence's domain expertise and deep integration with our design tools.

Our strategy remains centered on delivering high value engineering software rather than building a large general purpose AI infrastructure business. We are focused on improving efficiency and the value of project workflows and maintaining a software economics as customer adoption scales. But we believe that flexibility works in our model. Our model allows customers to use their own LLM infrastructure, build their associated model compute cost if they want to. And can license the underlying design agents and arugenic orchestration capabilities The economics of particular deployment options can vary, of course, but the point is that greater customer usage should create greater value for Cadence. I think that is where we differentiate ourselves.

Operator: Your next question comes from the line of Joe Vruinck from Baird. Please go ahead. Hi. Can you hear me? Yes. Yes, Joe. Please go ahead.

Joe Vruwink: Yeah. Oh, great. I want to go back to ViraStack and InnoStack. I think it is fair that the analog and back end areas have not seen the AI proliferation yet, like, front end design has. Are you seeing this change? Is specialized models and post training something that helps better address these domains? And if all of this is starting to happen, is there a commensurately higher revenue implication for cadence relative to even what has been seen to date? Yeah.

Anirudh Devgan: Hi, Joe. I mean, first of all, I mean, there is a, we started with ChipsTag. But then we have launched the 3 other major super agents, as you know. We have a stack for analog, InnoStack for back end, and AuraStack the latest 1 for package and PCB. I have to say the demand is actually phenomenal. Demand is phenomenal. Especially because these chip stack is doing great, but also these other agents are even more integrated with our base tools. So, InnoStack.

And if you look at our endorsements, typically, when we work with customers to get a public endorsement, it only happens with, like, 1 out of 10 customers because not everybody wants to talk about what they are doing. But we have maybe 10 endorsements this quarter, so that tells you the extent of the deployment of all these agents. And if you look at Innostack, Renesas is talking about, like, 34 x productivity improvement. Samsung Foundry. Look, there are other use cases that can happen, not just physical design. You know, 1 big use case is you know, design technology co optimization with the foundry. So this InnoSTAG is critical agent for that Socionext talked about 5x productivity improvement.

Rapidus has talked about 2x improvement. So there is a multiple-x improvement happening within a stack. ViraStack, I already said the demand is off the charts. And Aura tag, this is the latest area where innovation has not happened. So Nokia, showed 5x productivity improvement with AuraStack. So ChipStack is probably a year now in deployment. And these are maybe 6 to 9 months. But there is acceleration deployment of these. The newer but they are even more tightly integrated with the base tools. And then Maestro adds further differentiation on top of these. Capabilities.

So I feel very, very confident And, what is going to happen is we have a lot of R&D investment in our traditional tools in the middle layer. But now we are putting significant differentiation and investment in the top layer. You know, we are defining, I believe, what will be the agentic flow the future in all industries. So as we make the agentic top layer more and more complicated, more and more integrated, more and more differentiated, it is very difficult to compete with Cadence. in agentic AI.

Whether you are a startup or if you are, a customer trying to write some agent, the capabilities with model routing, with domain specific, models, with tight integration with agent and the tools. This is something that our customers cannot do themselves. So that also brought very well for all these customers realizing that and working more and more closely, not just in the middle layer, but in the top layer with us. So I feel very good in terms of how the speed and differentiation of our agentic offerings.

Operator: Your next question comes from the line of Jay Vleeschhouwer from Griffin Securities. Please go ahead.

Jay Vleeschhouwer: Thank you. Good evening. Anirudh, in your prepared remarks, you made some important references to the components of your core EDA, particularly in digital. it is demonstrable that over the last number of years, you have gained considerable share in core EDA. But I would like to delve into what the components of that share gain have been.

In other words, when we think about the various large categories that comprise core EDA, especially digital, it would be fair to say that the single largest difference in terms of the dollar and share gain you had over the last number of years has been with Innovus in implementation and perhaps to a lesser degree in areas like synthesis, RTL simulation, analysis, so forth. Perhaps you can you know, speak about the breadth of where that incremental revenue and shares come from in core EDA to the extent that it is not really largely concentrated in place and route. Yeah, Jay.

Anirudh Devgan: Great question. So yes, I mean, over the. You know, if you look at over 5, 7 years, we have gained so much in digital implementation, with Innovus becoming basically the platform of choice for advanced-node design. And then what is particularly encouraging in the last 6 to 12 months is not just Innovus, but all the tools around Innovus. And, you know, we always. I have talked about for 10 years now, you know, first is integration at lower nodes. So that was going to happen anyway as we go to 3 nanometer, 2 nanometer. it is difficult to separate sign off from implementation or synthesis from implementation.

But then with this agentic AI, you there is a further kind of need for vertical flows which are well integrated. So what I am. And I mentioned this last quarter also. I am particularly pleased to see I mean, not only our tools and synthesis and sign off are much, much better now versus few years ago, that we are getting this real full flow deployment at not just small or medium customers, but some very, very large customers are deploying our full digital flow and this is a great trend for Cadence. At the same time, you we maintain our undisputed leadership in analog. Okay?

And then because of the strength of palladium and strength of Jasper, strength of and agentic flows chip stack, it is also helping our verification business and logic simulation and so overall, that is why I was saying I feel that all the 3 big parts of EDA, we are in a very, very strong position, and gaining momentum. Not just individual tools being better, and proven, by large companies, but also this integration that advance knows integration with the agentic solution. So we will see how it proceeds, but overall, I feel pretty good about it.

Operator: Your next question comes from the line of Gary Mobley from Stonex. Please go ahead.

Gary Mobley: Hi, guys. Good afternoon. Thanks for taking my question. Your bookings in the first half somewhere in the ballpark of I do not know, mid 20%, call it 26%. Year over year. If I recall correctly, 2026 was supposed to be a low renewal period, 2026 was supposed to be. So my question is, you know, what is driving the strong backlog, the strong bookings? Is it, you know, utilizing traditional EDA tools as a result of you know, AI agent workflows, Is it a reflection of the strength of the semiconductor industry? Any color that you can add there? Would be helpful. Thank you.

John Wall: Sure. Thanks, Gary. I mean, we are very pleased with the booking performance and the growth in backlog. Particularly given that Q3 2026, as you mentioned, is a comparatively lighter renewal year for us? The strength reflects healthy underlying design activity, expanded customer engagements, and strong add on opportunities across our portfolio. And what we are seeing is that cadence is becoming increasingly important to customers as they look to accelerate their engineering road maps and address more complex design challenges. Backlog itself provides good visibility into that But it is important to remember that back log and bookings number reflects the timing of revenue recognition, that depends on the structure and delivery of individual arrangements and stuff like that.

But there is. So there is always a blend of time and value in those. But strong bookings in a lighter renewal year particularly encouraging because they reflect expanding customer engagements and not simply the renewal calendar. Since we are very, very pleased with that booking strength. Thank you. So, Gary, need. needless to say, we have done 3 quarters. there is still 1 more quarter to go. Which is traditionally a strong quarter. Yeah.

Anirudh Devgan: We will see where we end up. Yes.

John Wall: Thank you. K.

Operator: Your next question comes from the line of Lachlan Brown from Rothschild. Please go ahead.

Analyst: Hi, Anirudh. John. Thanks for squeezing me in. Are you seeing much evidence that new AI design tools like ChipStack are lowering the barriers to entry for silicon for nontraditional designers. And appreciate that land and expand naturally takes time, but are there signs that new logos could become more of a meaningful growth driver for that TAM expansion going forward. Thanks.

Anirudh Devgan: Yes. Absolutely. I mean, I have talked about this for years that you know, as we make chip design, easier to do, there will be more and more people doing chip design. And, you know, if you step back, you know, we made chip design maybe over the last 20 years, 100 times easier to do. Because, you know, maybe 20 years ago, all these IBM Intel would do, like, CPU design with 500 people in, like, 5 years. Now you can do a CPU design in 6 months with, like, 50 people. So that is, like, 100 times better, and that is what led to more and more designs. And with AI, we can have.

And add another 5x to 10x. It will be, like, thousand times easier than probably 20, 25 years ago. This will invariably lead to more and more design activity. And you can see that you know, even with the hyperscalers, if you go back 1 or 2 years ago, it was not clear that the hyperscalers will do or, we always get questions. Will they continue to do now with Google and Meta and Microsoft and Amazon and Tesla, everybody is doing more and more designs. Now at the same time, the traditional semiconductor companies are also doing well. Of course, the big And this is only going to accelerate in my opinion. You know, with.

Like we talked about space companies, finance companies, physical AI, car companies, the amount of design activity we are seeing in automotive is actually quite remarkable. And robotics and things like that. And then and then these things, robotics also have a lot of different chips. Right? The amount of chips that are there in 1 hand, you know, they are, like, 25 chips in 1 hand. Of a humanoid robot to control all the individual motors. So I think we are. We. I have believed this for years, and I think you will see more and more of this. And our job is to make these things easier to use, you know, have more.

You know, give more flexibility to our customers. Like we did with our agent solution in Maestro, so they can do more themselves.

Operator: Your final question comes from the line of Kelsey Chia from Siti. Please go ahead.

Kelsey Chia: Hi. Hi, Anirudh and John. Congrats on the great results. My question is on EDA. EDA growth has been very strong for the last 3 quarters, 18%, 19% year on year growth. Well above the historical growth rate. And it sounds like majority of that growth primarily driven by hardware. And agentic AI attribution is still quite small. Is that a fair characterization or could you give us a sense of customer adoption levels for IdentityWorks today? And if much of the set of revenue acceleration from IdentityAI is still ahead of us.

Anirudh Devgan: Yeah. Yeah. Thanks for the question. Yes. Of course, we are very proud of the hardware growth. But as you know, we will break out recurring and nonrecurring growth. So like I was mentioning earlier and John mentioned also, our recurring growth has improved from 11% last year to 18%. So that is not hardware. that is x hardware. Because hardware would typically show up in nonrecurring growth. So that is a that is a that is a major improvement of our recurring growth from last year to this year. And that is a combination of Agentic AI plus the growth of underlying tools and design starts. On the software side. Yeah.

John Wall: And, Kelsey, I think, you know, based on, like, listening to Anirudh's answer to Lachlan's question there a few minutes ago, that I mean, essentially, we believe that Agentic AI is a demand accelerator for EDA. I mean, customers have always built their own workflows around cadence tools. And we expect them to continue to develop their own agents as well. Our strategy accommodates that. And what is exciting is that agents could perform much more design exploration than an individual engineer calling our underlying engines repeatedly, and that creates a potential for significantly more consumption of our core EVA tools. I think you are starting to see that reflected in our EDA growth this year.

Operator: At this time, there are no further questions. I will now turn it back to Anirudh Devgan for closing remarks.

Anirudh Devgan: Thank you all for joining us this afternoon. it is exciting time for Cadence as we finish our Q3 with AI driven product leadership and strong business momentum. The Wall Street Journal ranked Cadence's board number 2 among all S and P 500 companies in its 2026 best boards list. 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.

Operator: Thank you for participating in today's Cadence Third Quarter 26 Earnings Conference Call. This concludes today's call. You may now disconnect.