Cadence reported a strong Q1 with record backlog of $8B, raised full-year revenue guidance to $6.125-6.225B (17% growth), and introduced new agentic AI products. The company highlighted expanding partnerships with Google, NVIDIA, MediaTek, and Intel, and noted acceleratio in IP and hardware demand from AI, HPC, and automotive. Physical AI and foundry diversification were key themes. Q1 revenue $1.474B (+19% YoY), non-GAAP EPS $1.96, operating margin 44.7%.
Buzzberg 분석Raising 2026 revenue growth outlook to 17%Cadence reported a strong Q1 with record backlog of $8B, raised full-year revenue guidance to $6.125-6.225B (17% growth), and introduced new agentic AI products. The company highlighted expanding partnerships with Google, NVIDIA, MediaTek, and Intel, and noted acceleratio in IP and hardware demand from AI, HPC, and automotive. Physical AI and foundry diversification were key themes. Q1 revenue $1.474B (+19% YoY), non-GAAP EPS $1.96, operating margin 44.7%.전체 분석 보기분석 접기
Cadence reported a strong Q1 with record backlog of $8B, raised full-year revenue guidance to $6.125-6.225B (17% growth), and introduced new agentic AI products. The company highlighted expanding partnerships with Google, NVIDIA, MediaTek, and Intel, and noted acceleratio in IP and hardware demand from AI, HPC, and automotive. Physical AI and foundry diversification were key themes. Q1 revenue $1.474B (+19% YoY), non-GAAP EPS $1.96, operating margin 44.7%.
Raised FY2026 revenue guide to $6.125-6.225B (17% growth) and expects rule of 60 (revenue growth + operating margin ≥60).
Record backlog of $8B reflects strong customer confidence, especially in agentic AI portfolio.
New agentic AI super agents (ChipStack, VeraStack, InnoStack) expected to expand TAM and drive base tool consumption.
Revenue$1.4742B
+2% QoQ
EPS$1.96
-2% QoQ
Op margin29.26%
reported
Free cash flow$0.307B
-40% QoQ
이번 분기에 달라진 점
01
Guidance
Raising 2026 revenue growth outlook to 17%
Guidance · revenue to $6.175B
02
Demand
Record backlog of $8 billion
Management expressed strong optimism, citing one of the best Q1s in company history, record backlog, accelerating AI demand, and a raised 2026 revenue growth outlook to 17% — with no notable shift in confidence from prior calls.
03
AI
Agentic AI era is here
Management said the agentic AI era is here and Cadence is leading the transformation of semiconductor and system design with new AI superagents (AgentStack, VeraStack, InnoStack) that expand EDA consumption and drive higher usage across platforms. They also noted that agentic…
04
Demand
Closed largest IP engagement with a leading foundry
Record backlog of $8 billion. Management expressed strong optimism, citing one of the best Q1s in company history, record backlog, accelerating AI demand, and a raised 2026 revenue growth outlook to 17% — with no notable shift in confidence from prior calls.
AI, 자본지출 및 수요 분석
AI
플랫폼 및 수익화
Management said the agentic AI era is here and Cadence is leading the transformation of semiconductor and system design with new AI superagents (AgentStack, VeraStack, InnoStack) that expand EDA consumption and drive higher usage across platforms. They also noted that agentic AI solutions are becoming an important part of customer renewals and expansions, and that the collaboration with Google and
수요
수주 및 전환
Record backlog of $8 billion. Management expressed strong optimism, citing one of the best Q1s in company history, record backlog, accelerating AI demand, and a raised 2026 revenue growth outlook to 17% — with no notable shift in confidence from prior calls.
톤 · upbeat
Management expressed strong optimism, citing one of the best Q1s in company history, record backlog, accelerating AI demand, and a raised 2026 revenue growth outlook to 17% — with no notable shift in confidence from prior calls.
공급망 알파
A1
Intel needs to invest more in 14A and be more ready for its foundry ramp, indicating Intel's advanced-node foundry business is still in early stages and may require significant EDA/IP support.
Great. Thanks for squeezing me in. I just wanted to ask about physical AI. I mean, you've made some pretty good acquisitions. You've now announced collaborations, especially with NVIDIA. So I'm just trying to get a sense for the momentum here and what really is still the early years in this breakout. And I think in particular, the take-up of your emulation tools, especially as it relates to closing the SIM to real gap in robotics and probably even self-driving chips as well, whether or not that's going to really lead to an outsized value capture for cadence, and when do we actually see this in the numbers as well? Thanks.
경영진 답변
Anirudh DevgnPresident and Chief Executive Officer, Cadence
Yeah, thanks for the question, Lee. So, I mean, you know, like I talked about it forever now that we look at this thing as a three-layer cake, right, and there are multiple slices of the cake, and the first slice was data center AI or infrastructure AI, and the second big slice is physical AI. And, of course, I've said this for five years now, but I believe physical AI will be bigger than data center AI by a long shot because you're talking about like trillions of dollars of product opportunity, and it will reconfirm the data center layer, data center slice, because to deploy, for example, an AI model in the car, you need to train it on the data center anyway. So I think it will even help the data center slice Now, for our portion, yes, we made this acquisition we are super excited about, and we have this now training flow for word models and also more complete simulation environment. So what is exciting about Hexagon is with combination of our previous technologies like Millennium and Cascade and Beta, we do have finally a complete solution for physical AI in the middle layer, kind of principal simulation and optimization layer. And then that can be used to do these word models, which will be different in the top layer. But the other thing I want to emphasize, apart from the SDNA and the AI part, that physical AI itself will drive a lot of silicon design. So it is also good for EDA and IP. And this is, you're starting to see that, you know, of course, companies like Tesla mentioning that they don't have enough silicon because of physical AI. So physical AI not only is good for SDNAI, it is also really good for silicon. And it also is the sweet spot of Cadence because Cadence always had both analog and digital solutions. And that's why we're always good with all the major semiconductor companies for automotive solutions. And now with all the system and OEM companies for automotive, and as that translates to drone and robots, it will also turbocharge the silicon business. That's why I have always been excited about physical AI, not just for the AI and SDA part, but also for EDN IP.
MediaTek is expanding its use of Cadence's newest AI-driven EDA offerings, indicating deepening engagement and likely increased spending.
“we furthered our long-standing partnership with MediaTek through a wide-ranging expansion across our new agentic AI offerings and core EDA, 3DIC, and system analysis solutions.”
Anirudh DevgnPresident and Chief Executive Officer, Cadence
… verification, and implementation engines at scale, we expect them to materially expand EDA consumption and drive higher usage across our platforms. We announced a strategic collaboration with Google to optimize the chip stack AI super agent with Gemini on Google Cloud. By combining LLM reasoning with GCP scalable compute, this collaboration delivers a cloud-native platform for next-generation chip development. In Q1, we furthered our long-standing partnership with MediaTek through a wide-ranging expansion across our new agentic AI offerings and core EDA, 3DIC, and system analysis solutions. Physical AI is emerging as the next big wave of intelligence as AI moves into autonomous systems, autos, drones, and robotics. And Cadence is uniquely positioned to lead this transition. The addition of Hexagon's D&E leading structural and multi-body dynamics technologies transforms our system analysis portfolio to a leadership position in physical AI. enabling customers to build and train fundamentally new AI word models by narrowing the critical SIM to real gap. At Cadence Live Silicon Valley, we announced an expanded partnership on AI and robotics with NVIDIA. By combining our …
Anirudh DevgnPresident and Chief Executive Officer, Cadence
… principle simulation and optimization as the critical middle layer, and agentic AI as the top layer. As I've said before, we believe the greatest value comes from the tight coupling of these layers, reinforcing each other to deliver much better results. As these super agents invoke our simulation, verification, and implementation engines at scale, we expect them to materially expand EDA consumption and drive higher usage across our platforms. We announced a strategic collaboration with Google to optimize the chip stack AI super agent with Gemini on Google Cloud. By combining LLM reasoning with GCP scalable compute, this collaboration delivers a cloud-native platform for next-generation chip development. In Q1, we furthered our long-standing partnership with MediaTek through a wide-ranging expansion across our new agentic AI offerings and core EDA, 3DIC, and system analysis solutions. Physical AI is emerging as the next big wave of intelligence as AI moves into autonomous systems, autos, drones, and robotics. And Cadence is uniquely positioned to lead this transition. The addition of Hexagon's D&E leading structural and multi-body dynamics technologies transforms our system …
The collaboration combines Cadence's agentic AI with NVIDIA technologies to accelerate engineering workflows, benefiting both companies' positions in physical AI.
“we announced an expanded partnership on AI and robotics with NVIDIA.”
Anirudh DevgnPresident and Chief Executive Officer, Cadence
… the next big wave of intelligence as AI moves into autonomous systems, autos, drones, and robotics. And Cadence is uniquely positioned to lead this transition. The addition of Hexagon's D&E leading structural and multi-body dynamics technologies transforms our system analysis portfolio to a leadership position in physical AI. enabling customers to build and train fundamentally new AI word models by narrowing the critical SIM to real gap. At Cadence Live Silicon Valley, we announced an expanded partnership on AI and robotics with NVIDIA. By combining our agentic AI-driven solutions with NVIDIA's advanced technologies, we are accelerating engineering workflows and boosting productivity across chip design, physical AI systems, and hyperscale AI factories. Now let me provide an update on our businesses. Our IP business continued its strong momentum with 22% year-over-year revenue growth driven by accelerating demand of AI, HPC, and automotive workloads. Growing complexity of advanced node designs and chiplet-based architectures is driving strong demands of our differentiated star IP portfolio across interface, memory, and foundation IP. We achieved meaningful competitive wins and …
Samsung's advanced-node foundry requires more EDA and IP as design activity increases, providing cross-company tailwinds for Cadence.
“there are at least three other major foundries, as you know, Samsung, Intel, and Rapidus at advanced nodes, and then Global and others at mainstream nodes.”
Great. Thank you. I want to switch to the IP business. Anirudh, you talked about IP entering now, third year of strong growth. Could you give an update, like what you saw in Q1, and are the HPM, LP, DDR6, and all that remaining still the key drivers? And the newer foundries, like Rapidus, Intel foundry, are they contributing meaningfully to the IP demand yet? And, Jun, just to clarify also on your EPS guidance, you said $0.28 dilution, but you lowered only $0.20. Just want to clarify that your organic basis, you raised by $0.08 EPS. Thank you.
경영진 답변
Anirudh DevgnPresident and Chief Executive Officer, Cadence
… team, just the performance, because these things are standard-based IPs, like DDR or PCIe. So the spec is same, but if our power or area is better than the competitor or what the customer can do, then they will buy our IP. So the most promising thing to me is Because of the strength of our R&D team, our PPA is better. And that is leading to a lot of competitive wins at pretty significant major customers. And I highlighted some of them in Cadence Live. So these are like really big kind of marquee names. So that gives me strength that the team is operating well. So that's number one. Number two, our portfolio is expanding, you know, like we have highlighted with like HBM. And some of it is organic. Some of it is... acquired like HBM we acquired from Rambus and then we improved it but UCIE which is a critical chip to chip technology was all developed organically okay so the second reason is that our portfolio is expanding the third reason is these new foundries okay and it's very encouraging to see of course we want to make sure we are best in class in TSMC which is the leading foundry But now there are at least three other major foundries, as you know, Samsung, Intel, and Rapidus at advanced nodes, and then Global and others at mainstream nodes. So the amount of design activity with AI and number of increasing foundries requires more IP. So that's why I'm actually pleased to note today, like in the prepared remark, that we had a pretty significant IP deal, one of the largest ones. At a leading global foundry. Okay. And just to clarify, you know, that is not Intel. Okay. We are actually pleased with our discussions with Intel, you know, with Libbo and team on 18A and especially on 14A. I think Intel realizes they need to invest more in 14A and this time be more ready, you know, because Availability of IP and EDA solutions as 14A is critical as they go talk to their customers. So we are making very good progress with Intel. And we'll have, you know, soon we'll have more to say on our engagement with Intel. But I'm also pleased with this engagement with the other global foundry. So overall, you know, IP growth seems robust. And I'm very pleased where we are. And we're already always very strong in EDA. But historically, last few years, you know, we have not done as well in IP. But right now, I think we are very well positioned and also well positioned in SDA.
Intel needs to invest more in 14A and be more ready for its foundry ramp, indicating Intel's advanced-node foundry business is still in early stages and may require significant EDA/IP support. — Intel's increased investment in 14A IP and EDA readiness could lead to a large IP deal for Cadence, but also signals that Intel's foundry customer traction is still scaling.
“We are actually pleased with our discussions with Intel, with Lip-Bu and team on 18A and especially on 14A. I think Intel realizes they need to invest more in 14A and this time be more ready.”