益華電腦 (CDNS) 2026 Q3 法說會逐字稿

Good afternoon. My name is Jade, and I will be your conference operator today. At this time, I would like to welcome everyone to the Cadence third quarter 2026 earnings conference call.

下午好。我叫 Jade，今天將擔任本次會議的接線員。此刻，我謹代表主辦方歡迎各位參加 Cadence 2026 年第三季財報電話會議。

(Operator Instructions)

(接線員指示)

I will now turn the call over to Richard Gu, Vice President of Investor Relations for Cadence. Please go ahead.

現在我將把電話交給 Cadence 投資人關係副總裁 Richard Gu。請開始。

Thank you, operator. I'd like to welcome everyone to our third 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.

謝謝，接線員。歡迎各位參加我們 2026 年第三季財報電話會議。今天與我一同出席的有總裁暨執行長 Anirudh Devgan，以及資深副總裁暨財務長 John Wall。

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.

本次電話會議的網路直播以及今日預先準備的講稿，將可於我們的網站 cadence.com 取得。今日討論將包含前瞻性陳述，包括我們對未來業務與營運結果的展望。

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 in today's earnings release.

由於存在風險與不確定性，實際結果可能與今日討論中所預測或暗示者有重大差異。關於可能導致實際結果不同的因素，請參閱我們向 SEC 提交的文件，包括最新的 10-K 與 10-Q 表格，以及今日財報新聞稿中的 CFO 評論。

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.

本次電話會議中的所有前瞻性陳述，均基於截至今日我們可取得的估計與資訊。且我們不承擔更新這些陳述的任何義務。此外，除非另有說明，本次電話會議所討論的所有財務衡量指標均為非 GAAP。

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, I would ask that you observe a limit of one question only. If time permits, you can re-queue with additional questions. Now I'll turn the call over to Anirudh.

非 GAAP 指標不應被孤立看待，亦不應作為 GAAP 結果的替代。GAAP 與非 GAAP 指標之間的調節表已包含於今日的財報新聞稿中。在今日的問答環節，我想請各位每次僅提一個問題。若時間允許，您可以重新排隊提出其他問題。現在我把電話交給 Anirudh。

Thank you, Richard. Good afternoon, everyone, and thank you for joining us today. I'm pleased to report that Cadence delivered another outstanding quarter with all key metrics coming in well above our guidance.

謝謝你，Richard。各位下午好，感謝今天加入我們。我很高興報告，Cadence 再次交出一個非常出色的季度，所有關鍵指標均明顯優於我們的指引。

Backlog reached a record of $8.2 billion, reflecting strong bookings driven by growing customer demand. Given our strong 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.

積壓訂單（backlog）創下 82 億美元新高，反映在客戶需求成長帶動下的強勁接單。鑑於我們強勁的業務動能、持續擴大的技術領先地位，以及具吸引力的 AI 成長機會，我們將全年營收展望上調至成長 21%，並將每股盈餘（EPS）展望上調 0.30 美元至 8.40 美元。

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.

John 將就我們第三季業績與更新後的財務展望提供更多細節。Agentic AI 代表一個具變革性的市場機會，而 Cadence 具備極佳的條件把握此機會。

Our differentiated three-layer framework is anchored by our physically accurate simulation and optimization engines in the critical middle layer, tightly integrated with AI agents and orchestration at the top and accelerated compute and proprietary data at the base.

我們具差異化的三層架構，以關鍵的中間層為核心：具備物理精準度的模擬與最佳化引擎；並在上層與 AI 代理與編排（orchestration）緊密整合，在底層則以加速運算與專有資料為基礎。

Agentic AI continues to evolve at a remarkable pace. With our AI super agents gaining strong traction, we are now addressing the long-standing customer demand for domain specialized models.

Agentic AI 仍以驚人的速度持續演進。隨著我們的 AI 超級代理（AI super agents）獲得強勁採用，我們現在正回應客戶長期以來對領域專用模型的需求。

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.

我們相信，基於 Agentic AI 的設計未來，將日益走向「領域專用模型」結合「智慧模型路由」以提升效能，並透過與底層工具相連的強化學習迴圈，實現遞迴式自我改進。

Today, I'm excited to introduce my stroke, a portfolio of domain specialized AI models, purpose build for chip and system design.

今天，我很興奮地介紹 Maestro——一套領域專用 AI 模型組合，專為晶片與系統設計量身打造。

By controlling all three layers, our AI super agents, 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.

透過掌控三個層面——我們的 AI 超級代理、Maestro 模型，以及經驗證的 EDA 與 SDA 工具——我們具備獨特優勢，能為客戶提供最佳的效能、效率與吞吐量成果。初步結果非常具說服力：相較於通用基礎模型（foundation model），品質最高可提升 30%，token 效率最高可提升 5 倍。

Moreover, the Maestro models can be further post trained on customers' proprietary data to deliver even better outcomes.

此外，Maestro 模型還可在客戶的專有資料上進一步進行後訓練（post-train），以帶來更佳成果。

Our model router chooses among our models and other leading frontier and open wide models as needed for optimal results. Customers can opt to deploy Maestro models in the cloud or in their on-prem environment.

我們的模型路由器會視需要在我們的模型與其他領先的前沿模型及開源模型之間進行選擇，以取得最佳結果。客戶可選擇在雲端或其自有機房（on-prem）環境部署 Maestro 模型。

Maestro is gaining strong early customer tractions 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 chip stack for RTL generation and early PP optimization.

Maestro 已在早期客戶中獲得強勁動能，並已有多項部署正在進行。我們的 AI 超級代理動能持續加速，早期成果令人振奮，且已有超過 100 個活躍的客戶合作案。我們在 ChipStack 新增了一個用於 RTL 生成與早期 PPA 最佳化的新代理。

That created RTL delivering an 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 engines to achieve outcomes that foundation models alone cannot deliver.

該代理所產生的 RTL，相較於純粹由基礎模型生成的程式碼，平均可降低 24% 面積並降低 18% 功耗。更重要的是，這展示了將我們的 AI 超級代理、AI 模型與底層 EDA 引擎結合的威力，能達成僅靠基礎模型無法實現的成果。

Honda is using the RTL generation agent and AI-powered automation to improve productivity from specification to RTL development.

Honda 正在使用 RTL 生成代理與 AI 驅動的自動化，提升從規格到 RTL 開發的生產力。

In Q3, MediaTek deployed chip stack into its production digital verification flow, achieving 50% to 70% improvement in verification coverage and 1.4 to 2x reduction in engineering efforts with deployment now scaling across design teams. In analog and custom design.

在第三季，聯發科（MediaTek）將 ChipStack 部署到其量產級數位驗證流程中，使驗證覆蓋率提升 50% 至 70%，並將工程投入降低 1.4 至 2 倍；目前部署正擴大至各設計團隊。在類比與客製化設計方面。

ViraStack saw 4x increase in customer engagement with deployments in various production designs at multiple customers.

ViraStack 的客戶互動增加了 4 倍，並已在多家客戶的多個量產設計中進行部署。

The combination of agentive workflow, embedded skills and our Virtuoso platform is unlocking significant new productivity opportunities in a traditionally difficult to automate domain.

代理式工作流程（agentic workflow）、內嵌技能（embedded skills）與我們 Virtuoso 平台的結合，正在一個傳統上難以自動化的領域中，釋放出顯著的新生產力機會。

We are seeing strong customer interest in InnoStack, our digital AI super agent ad customers push to improve PPA, accelerated design closure and boost productivity.

隨著客戶推動改善 PPA、加速設計收斂並提升生產力，我們看到客戶對 InnoStack（我們的數位 AI 超級代理）展現強勁興趣。

In Q3, the Renesas MCU team successfully deployed InnoStack across a wide range of engineering costs, achieving a 34x productivity improvement with plans to expand its usage to layout automation.

在第三季，瑞薩（Renesas）MCU 團隊成功在廣泛的工程工作中部署 InnoStack，實現 34 倍的生產力提升，並計畫將其使用擴展至佈局自動化。

Also in Q3, Samsung Foundry successfully used InnoStack to dramatically improve engineering efficiency and accelerate PPA exploration, reshaping its approach to technology migration and BTCO optimization.

同樣在第三季，Samsung Foundry 成功使用 InnoStack 大幅提升工程效率並加速 PPA 探索，重塑其技術遷移與 BTCO 最佳化的方法。

Socionext is deploying InnoStack in its production design environment. And I expect its combination with our advanced physical design tools to deliver up to a 5x overall productivity gains while maintaining design quality.

Socionext 正在其量產設計環境中部署 InnoStack。我預期其與我們先進的實體設計工具結合後，在維持設計品質的同時，整體生產力最高可提升 5 倍。

In PCB and 3DIC 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.

在 PCB 與 3DIC 設計方面，市場對我們 AuraStack AI 超級代理的早期回饋極為正面。Nokia 正在我們的 Millennium 超級電腦上部署 AuraStack，以推進大規模電子系統設計。

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.

透過在安全的自有機房平台上整合 Agentic AI、我們基於物理的求解器（solvers）與加速運算，Nokia 在關鍵設計與分析工作流程上實現了 5 倍加速。

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.

接下來談我們的業務。我們很高興所有產品群都交出亮眼成績：核心 EDA 年增 20%、IP 年增 24%、以及 SD&A 年增 30%。設計活動加速持續帶動對我們核心 EDA、SDA 與 IP 產品的強勁需求。

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.

同時，我們也看到客戶對我們 Agentic AI 產品組合展現驚人的動能，這也帶動了對我們底層產品日益增加的需求。我們很高興經常性收入延續強勁動能，年增 18%。

I'm 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.

我尤其為我們與頂尖客戶簽署的重要且涵蓋廣泛的協議感到自豪。我們透過對核心 EDA、硬體與 SDA 解決方案的大幅且廣泛擴展，進一步深化與一家全球指標性系統客戶的長期合作夥伴關係。

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 SDA solutions, establishing Cadence as their primary design partner.

在第三季，Cadence 與一家頂尖電信業者透過在我們 AI 產品、EDA 軟體、硬體與 SDA 解決方案上的廣泛擴展，深化其長期策略夥伴關係，並確立 Cadence 為其主要設計合作夥伴。

Core EDA revenue growth was driven by broad-based strength across the portfolio. Our digital and sign-up business continue to expand, achieving 16 new full flow wins during the quarter.

核心 EDA 營收成長由產品組合各面向的廣泛強勁表現所帶動。我們的數位與 sign-up 業務持續擴張，本季新增 16 個完整流程（full flow）勝案。

As agentic flows increasingly require full vertical workflows, there is growing demand for our synthesis and sign-off solutions.

隨著 agentic 流程日益需要完整的垂直工作流程，市場對我們的綜合（synthesis）與簽核（sign-off）解決方案需求正在增加。

Our sign-up product saw growing adoption and our verification software product had strong growth in big digital and memory designs with increasing usage at major hyperscaler and memory companies.

我們的 sign-up 產品採用度持續提升，而我們的驗證軟體產品在大型數位與記憶體設計方面實現強勁成長，並在主要超大規模雲端業者與記憶體公司中的使用量持續增加。

As AI and HPC designs continue to grow in scale and complexity, hardware-assisted verification has become an increasingly strategic capability for our customers.

隨著 AI 與 HPC 設計在規模與複雜度上持續提升，硬體輔助驗證已成為客戶日益具策略性的能力。

This is driving sustained unprecedented demand for our Palladium and Protium 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.

這正推動對我們 Palladium 與 Protium 仿真（emulation）平台持續且前所未有的需求，並再度創下單季新高紀錄。我們新增了多個新客戶標誌（logos），並在多個垂直領域與指標性客戶實現顯著擴展。

Our hardware cloud offering showed strong growth with a leading semiconductor company adopting more hardware cloud services to accelerate new product development.

我們的硬體雲端產品展現強勁成長，一家領先的半導體公司採用更多硬體雲端服務，以加速新產品開發。

In analog and custom design, Spectre FX continues to gain momentum, highlighted by major competitive displacement at a marquee infrastructure silicon provider with multiple new 2-nanometer projects adopting our platform.

在類比與客製化設計方面，Spectre FX 持續增強動能，亮點包括在一家指標性基礎設施矽晶片供應商處實現重大競品替換（competitive displacement），其多個新的 2 奈米專案採用我們的平台。

Our IP business delivered another outstanding quarter, driven by deepening engagements with leading hyperscalers and semi customers.

我們的 IP 業務再度交出亮眼的一季，主要受惠於與領先超大規模雲端業者及半導體客戶更深度的合作。

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.

我們持續受惠於 AI 驅動的強勁順風，推動 AI 基礎設施投資加速、客製化矽晶片採用增加，以及對高效能 IP 的需求提升。

Along with the transition to advanced nodes and chiplet-based architectures, these AI-driven trends are creating a strong full for our differentiated STAR IP portfolio across interface, memory and foundation IP.

隨著先進製程節點與以 chiplet 為基礎的架構轉型，這些 AI 驅動趨勢正在為我們具差異化的 STAR IP 產品組合在介面、記憶體與基礎 IP 方面創造強勁的完整流程（full flow）需求。

We are well positioned for sustained growth as we continue to deliver superior power performance and area across our expanding advanced IP portfolio.

隨著我們持續在不斷擴大的先進 IP 產品組合中提供更優異的功耗、效能與面積（PPA），我們已具備持續成長的良好定位。

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.

一家領先的太空科技公司為其客製化晶片計畫選擇了我們的 IP 產品組合，為更廣泛的服務與矽晶片合作鋪路。Tensilica 創下單季營收新高，我們也宣布與 Analog Devices 在下一代音訊應用上進行聯合開發。

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.

我們的系統設計與分析業務再度交出強勁的一季，主要受惠於客戶對我們整合式解決方案的採用增加，以及我們擴展後的電子與物理系統智慧（intelligence）產品組合加速普及。

Allegro momentum continued, including a competitive displacement at a leading EV customer that chose Cadence's integrated PCB design and multiphysics analysis platform as its primary solution.

Allegro 動能持續，包括在一家領先電動車客戶處實現競品替換，該客戶選擇 Cadence 的整合式 PCB 設計與多物理分析平台作為其主要解決方案。

Our Millennium platform had strong adoption driven by deployment of our GPU-accelerated electronic and mechanical systems suite, along with our reality digital twin solution.

我們的 Millennium 平台採用度強勁，主要由我們 GPU 加速的電子與機械系統套件部署所帶動，並結合我們的 Reality 數位孿生解決方案。

During the quarter, Switch, a leader in sustainable high-density AI infrastructure selected our Millennium and reality digital twin solutions to advance the design and simulation of its next-generation AI factories.

本季期間，永續高密度 AI 基礎設施領導者 Switch 選擇我們的 Millennium 與 Reality 數位孿生解決方案，以推進其下一代 AI 工廠的設計與模擬。

The MSE business is the integral part of our physical AI strategy, and its integration is progressing well. MSC Adam our industry-leading multibody dynamic solution helped secure a competitive displacement at a leading power company, along with adoption of other cadence products.

MSE 業務是我們物理 AI 策略的核心組成部分，其整合進展順利。MSC Adams（我們業界領先的多體動力學解決方案）協助我們在一家領先電力公司取得競品替換，同時也帶動其採用其他 Cadence 產品。

In summary, Cadence delivered exceptional Q3, and I'm delighted with the accelerating momentum of our business.

總結來說，Cadence 在第三季表現卓越，我對我們業務加速的動能感到非常振奮。

We are executing extremely well in a vibrant AI market, have our strongest competitive position ever and are extending our leadership in AI.

我們在充滿活力的 AI 市場中執行力極佳，擁有史上最強的競爭地位，並持續擴大我們在 AI 領域的領導地位。

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.

我們高度經常性且可平滑認列（ratable）的商業模式，結合客戶研發投資的成長，使我們在這個動態的 AI 環境中具備持續強勁表現的良好定位。

With that, I will turn it over to John to provide more details on our Q3 results and our updated 2026 outlook.

接下來，我將交給 John，請他提供更多關於我們第三季業績以及更新後 2026 年展望的細節。

Good afternoon, everyone. Cadence delivered strong third quarter results driven by robust demand across our businesses and growing momentum from AI-driven designs.

各位下午好。Cadence 第三季交出強勁成果，主要由我們各項業務的穩健需求，以及 AI 驅動設計帶來的動能提升所帶動。

Growth is accelerating and broadening Q3 revenue grew 22% year-over-year with strong double-digit growth across all products.

成長正在加速並擴大：第三季營收年增 22%，所有產品均呈現強勁的雙位數成長。

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.

我們在每一項關鍵財務指標上都超越指引，並以 82 億美元的創紀錄在手訂單（backlog）結束本季。以下是第三季的一些財務重點，先從損益表開始。

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.

總營收為 16.33 億美元。GAAP 營業利益率為 26.2%。Non-GAAP 營業利益率為 44.1%。GAAP 每股盈餘（EPS）為 1.05 美元。Non-GAAP EPS 為 2.11 美元。

Next, turning to the balance sheet and cash flow. Our cash balance was $1.452 billion, while the principal value of debt outstanding was $2.650 billion.

接著看資產負債表與現金流。我們的現金餘額為 14.52 億美元，而未償還債務的本金金額為 26.50 億美元。

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.

營運現金流為 4.24 億美元。應收帳款週轉天數（DSO）為 66 天，本季我們動用 4 億美元回購 Cadence 股票，反映我們對業務的信心以及回饋股東的承諾。

Underscoring that commitment, our Board has authorized an additional $2.5 billion for our share repurchase program.

為強化該承諾，我們董事會已核准額外 25 億美元用於股票回購計畫。

Before I provide our updated outlook, I'd like to highlight that it contains the usual assumption that export control regulations that exist today remains substantially similar for the remainder of the year.

在我提供更新後的展望之前，我想強調其中包含一項慣常假設：目前存在的出口管制法規在今年剩餘期間將大致維持相近。

For our updated outlook for 2026, we now expect revenue in the range of $6.387 billion to $6.417 million. 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.

針對我們更新後的 2026 年展望，我們目前預期營收介於 63.87 億美元至 64.17 百萬美元之間。GAAP 營業利益率介於 28.2% 至 29.2%。Non-GAAP 營業利益率介於 44.2% 至 45.2%。GAAP EPS 介於 4.84 美元至 4.90 美元。

Non-GAAP EPS in the range of $8.37 to $8.43. Operating cash flow of approximately $2 billion, we expect to use more than 50% of our free cash flow to repurchase Cadence shares in 2026.

Non-GAAP EPS 介於 8.37 美元至 8.43 美元。營運現金流約 20 億美元；我們預期在 2026 年將使用超過 50% 的自由現金流回購 Cadence 股票。

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%.

針對第四季，我們預期營收介於 16.95 億美元至 17.25 億美元。GAAP 營業利益率介於 30% 至 31%。Non-GAAP 營業利益率介於 44% 至 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 document on our Investor Relations website which includes our outlook for additional items as well as further analysis and GAAP to non-GAAP reconciliations.

GAAP EPS 介於 1.23 美元至 1.29 美元，Non-GAAP EPS 介於 2.19 美元至 2.25 美元。照例，我們已在投資人關係網站發布 CFO 評論文件，其中包含其他項目的展望、進一步分析，以及 GAAP 與 Non-GAAP 的調節表。

Overall, I'm pleased with our Q3 results, especially our recurring revenue growth of 18% year-over-year.

總體而言，我對我們第三季的業績感到滿意，尤其是我們的經常性收入年增18%。

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'd like to close by thanking our customers, partners and our employees for their continued support.

以我們更新後的2026年展望中點來看，我們目前預期營收成長21%、營業利益率44.7%，以及每股盈餘（EPS）為8.40美元。如同以往，我想在結尾感謝我們的客戶、合作夥伴以及員工持續的支持。

And with that, operator, we will now take questions.

那麼，接線員，我們現在開始提問。

(Operator Instructions) Jason Celino, KeyBanc Capital Markets.

(接線員指示) Jason Celino，KeyBanc Capital Markets。

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

嗨，謝謝讓我提問。Anirudh，很高興看到Maestro的發布公告。你知道我不是EDA工程師，也不是AI科學家，所以也許你可以更清楚地解釋一下這是什麼。聽起來它有點像模型路由器，但也可能包含特定領域模型。所以這些特定領域模型是Cadence在開發嗎？能否再多談一些，以及這個新產品的變現方式會如何運作？謝謝。

Yeah. Hi, Jason, and thank you for the question. Yes, there's a lot in that release. So let me try to unpack it a little bit. First of all, we are very pleased with the momentum of our agent stack and all the four super agents.

好的。嗨，Jason，謝謝你的問題。是的，那份發布內容涵蓋很多。我試著把它拆解說明一下。首先，我們對我們的代理（agent）技術堆疊以及四個超級代理的動能感到非常滿意。

And you can see there are like more than 100 engagements now. So as we work with customers over the last 6 to 9 months, several trends became pretty clear, okay?

你可以看到目前已經有超過100個合作案。因此，在過去6到9個月與客戶合作的過程中，有幾個趨勢變得相當明確，好嗎？

And to me, we are launching Maestro as what I would call the next generation of agents. And there are three big factors in the next generation of agents.

對我而言，我們推出Maestro，是我所稱的下一代代理。而下一代代理有三個重要因素。

So one is, like what has happened in the last one year is that, of course, we work with all the Frontier labs from the very beginning, whether they're doing chip design themselves, or we are using their LLMs.

第一個是，過去一年發生的事情是，當然，我們從一開始就與所有前沿實驗室（Frontier labs）合作，不論他們是否自己做晶片設計，或是我們使用他們的LLM。

But over the last one year, there is this emergence of very, very good open rate models, okay? And I always wanted to do like domain specialized models, but now it's finally possible with open weight models.

但在過去一年，出現了非常、非常優秀的開放權重模型（open weight models），好嗎？我一直想做領域專用模型，但現在終於因為開放權重模型而成為可能。

And it's actually very cost effective to post train these models, to deliver like domains intelligence, which is remarkable. We're getting up to 30% better quality by using our tools and data to post train these models. And also, you don't need like -- it's a portfolio of model.

而且對這些模型進行後訓練（post-train）以提供領域智慧，其實非常具成本效益，這相當了不起。我們使用自家的工具與資料對這些模型做後訓練，品質可提升多達30%。此外，你也不需要只靠單一模型——而是一個模型組合。

So all the way to like small decisions LLMs to small and medium LLM all the way up to fronter class open wage models post trained on our data and intelligence. So that's the first part of Maestro.

從用於小型決策的LLM，到小型與中型LLM，一直到以前沿等級的開放權重模型，並以我們的資料與智慧進行後訓練。這就是Maestro的第一部分。

So it gives really customization for chip and system design and gives much, much better results. It's actually quite remarkable how much these models can be improved by post training, okay. Now the second part of that is in our agents and when they do these tasks have a variety of tasks, right?

因此，它能為晶片與系統設計提供真正的客製化，並帶來更好、好得多的結果。這些模型透過後訓練能改善到什麼程度，確實相當驚人，好嗎。第二部分則是，我們的代理在執行任務時，會有各式各樣的任務，對吧？

So we don't need only one size or type of model to do the task. So the second part is model routing. Just like you don't need to use an airplane to go to your local grocery store, right?

所以我們不需要用單一尺寸或單一類型的模型來完成所有任務。因此第二部分是模型路由（model routing）。就像你不需要搭飛機去家附近的雜貨店一樣，對吧？

So similarly with agents, you have a variety of tasks that we need to do from simple task to like deep thinking and reasoning tasks. So the moderator will efficiently knowing what the task is from our super agents use the right model.

同樣地，對代理而言，我們需要處理各種任務，從簡單任務到需要深度思考與推理的任務。因此，路由器會有效率地辨識任務類型，並從我們的超級代理中選用合適的模型。

And that can easily give like up to 5x improvement in token efficiency. So either much lower cost or 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.

這很容易就能在token效率上帶來最高達5倍的改善。也就是要嘛成本大幅降低，要嘛在相同成本下完成更多工作。第三點則是我一直在談的：與底層工具結合的強化學習迴圈（reinforcement learning loop）。

And we have great examples we talked about our new RTL agent that one of the customers publicly endorsed Honda gave 24% area and 18% power because the integration with the underlying tools, and how we call them, and continuous self-improvement whether it's skills or models gives us a unique advantage.

我們有很好的例子：我們談到新的RTL代理，其中一位客戶本田（Honda）公開背書，因為與底層工具的整合、以及我們如何呼叫這些工具，再加上不斷自我改進（不論是技能或模型），讓面積改善24%、功耗改善18%，這給了我們獨特優勢。

So if you combine these three things together, domain specialized models -- domain specialized family of models, plus model routing plus deep integration with our tools and data, it gives a unique differentiation that nobody else can do.

因此，如果把這三件事結合起來：領域專用模型——領域專用的模型家族，加上模型路由，再加上與我們工具與資料的深度整合，就能形成一種獨特差異化，是其他人做不到的。

And it also allows us to control all three layers of the cake and innovate in all three layers of the cake. So I'm actually super excited. And I think this is what's going to happen in all industries as these LLMs mature, this domain specialized intelligence model routing and integration with underlying engines.

而且也讓我們能掌控這個蛋糕的三個層次，並在三個層次上都能創新。所以我其實非常興奮。我認為，隨著這些LLM逐漸成熟，所有產業都會走向這種模式：領域專用智慧、模型路由，以及與底層引擎的整合。

Jim Schneider, Goldman Sachs.

Jim Schneider，高盛（Goldman Sachs）。

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

下午好。謝謝讓我提問。我想請你們更新一下你們所看到的Agentic AI解決方案的變現進展。我記得上季你們談到經常性收入成長20%。這一季是18%。能否談談其中差異，以及經常性收入的構成？另外，在這之下，Agentic部分的經常性收入是否有任何加速？

Yeah. Thanks for the question. I'll start, and then John can comment. The -- I'm very proud of the recurring growth. And I mean, this quarter, there were some specific things.

好的，謝謝你的問題。我先回答，然後John可以補充。我——我對經常性收入的成長非常自豪。而且這一季確實有一些特定因素。

Like if you compare it to Q3 of last year, there were some specific things with China revenue moving around, which 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 it's 18% for this quarter, and it was very good last quarter.

例如，如果你拿去跟去年第三季相比，當時有一些與中國營收在不同期間移轉相關的特定因素，今年就沒有了。但整體而言，經常性收入表現非常出色。如果你退一步看，去年經常性收入成長是11%，而這一季是18%，而且上一季也非常好。

So I expect recurring revenue to do very well in 2026. And this is a result of, of course, our Agentic AI solutions, but also Agentic AI solutions driving more usage of our base tools, which, as we always said, is going to happen.

所以我預期2026年的經常性收入會表現得非常好。這當然是我們Agentic AI解決方案的成果，但同時Agentic AI解決方案也帶動了我們基礎工具的更多使用，而我們一直說這會發生。

So that's what we see. 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.

所以這就是我們看到的情況。很多合作案是Agentic的，且我們的基礎工具使用量也很高。因此這為經常性收入帶來很大的成長動能，再加上我們在IP與硬體方面持續的強勁表現，就得到一組非常、非常好的結果。

Yeah, I'd agree with that, Anirudh. I mean it basically reflects strong demand across our software portfolio and healthy customer expansions and continued strength in core EDA. Yes, I think that's the way to look at it in terms of strong high teen growth in recurring revenue. We're very pleased with this.

是的，我同意，Anirudh。我的意思是，這基本上反映了我們軟體產品組合的強勁需求、客戶健康的擴張，以及核心EDA持續的強勢。是的，我認為從經常性收入維持在十幾個百分點後段的強勁成長來看，就是這樣解讀。我們對此非常滿意。

Vivek Arya, Bank of America Securities.

Vivek Arya，美國銀行證券。

Thanks for taking my question. Anirudh, we recently heard three things from your competitors that they can grow sales kind of at a mid-teens pace next year and then compound it that they can achieve 50% operating margins? And then also, interestingly, there is a royalty-based model that can help add nearly $1 billion to their top line over the next several years.

感謝讓我提問。Anirudh，我們最近從你們的競爭對手那裡聽到三件事：他們明年銷售額可以以大約中十幾%的速度成長，並且之後還能持續複利成長；他們也能達到 50% 的營業利潤率？另外也很有意思的是，有一種以權利金為基礎的模式，未來幾年可讓他們的營收增加將近 10 億美元。

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

所以我理解，對，這不是一通要給出多年期成長展望的電話會議，但我只是希望聽聽你的看法：你如何看待 Cadence 的成長以及權利金這一塊的組合？Cadence 在維持或擴大市占率，以及長期維持領先的營業利潤率方面，定位有多好？

Yeah. Thanks for the question, Vivek. So overall, I'm very pleased with our growth and not just growth, but profitability and margin. And we always talk about like a rule of 40 metric or revenue growth plus margin. So I think we will end the year, if you look at our guide, about 21% revenue growth and slightly less than 45% margin.

好的。謝謝你的問題，Vivek。整體而言，我對我們的成長非常滿意，而且不只是成長，還包括獲利能力與利潤率。我們也一直談到所謂的「40 法則」指標，也就是營收成長加上利潤率。所以我想如果你看我們的指引，我們今年將以大約 21% 的營收成長、以及略低於 45% 的利潤率作結。

So we will end up north of 65% in 2026, okay? That's the important thing to point out Okay. And we still have one more quarter to go. So we'll see -- it's an important quarter for us. Fourth quarter is always important.

所以到 2026 年我們會在 65% 以上，好嗎？這是需要強調的重點，好嗎？而且我們還有一個季度要走。所以我們會看看——這對我們來說是很重要的一季。第四季一向都很重要。

So we'll 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.

所以我們會看看最後結果如何，我們也會像往常一樣在二月針對下一年更新給各位。但整體而言，我認為外部環境對我們非常正面。

As you know, the AI build-out continues the 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.

如各位所知，AI 的建置持續進行，在 AI 的各個面向都有大量設計活動；甚至傳統公司、類比混合訊號公司、數位公司、記憶體公司、系統公司也是如此，所以設計活動的強度是我所見過最強的一次。

And our -- we're gaining share in almost all segments of our business, whether it's IP or hardware or EDA, Agentic AI. So our product portfolio, I think, is the strongest it has ever been.

而且我們——幾乎在業務的所有區隔都在提升市占，不論是 IP、硬體、EDA，或是 Agentic AI。

And then we have this huge opportunity with Agentic AI. And I think we are redoing how agent 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 three things, I feel Cadence is in a very, very strong position.

此外，我們在 Agentic AI 上也有巨大的機會。我認為我們正透過自有的領域專用模型，以及能持續與所有前沿模型合作的彈性，重新定義「代理（agent）」在各行各業中的樣貌。

Now in terms of your specific question on royalty, we are always looking at different kind of business models. So in IT, we always had royalty for a while in Tensilica, and now we have royalty in our design IP business as well.

至於你特別問到的權利金，我們一直在看各種不同的商業模式。所以在 IT 方面，我們在 Tensilica 早就有一段時間採用權利金模式；而現在在我們的設計 IP 業務中也有權利金。

But to me, that's just one vector. We're always looking at how to best serve -- give value to our customers and then get, of course, value and return.

但對我而言，那只是其中一個向量。我們一直在思考如何以最佳方式服務——為客戶創造價值，然後當然也取得價值與回報。

Siti Panigrahi, Mizuho.

Siti Panigrahi，瑞穗。

Thank you. Congrats on a good quarter. I just want to ask on hardware I see the inventory again grew this quarter, I'm wondering hardware is a strong quarter. How sustainable hardware growth for heading into next year 2027. Any color would be helpful there. And a quick clarification, John. There was a spike in G&A expense in Q3. Was there anything onetime there?

謝謝。恭喜本季表現不錯。我想問硬體方面：我看到本季庫存又增加了，我在想硬體本季很強。展望明年 2027 年，硬體成長的可持續性如何？如果能提供一些說明會很有幫助。另外一個快速釐清，John：第三季 G&A 費用有一個跳升，那裡面有沒有任何一次性因素？

Yeah. Sure, Siti. Great. Look, I'll take the hardware question first. The hardwood continues to perform exceptionally well.

好的。當然可以，Siti。我先回答硬體的問題。硬體持續表現得非常出色。

I mean we delivered another record quarter, supported by strong demand from AI and HPC customers. And we're also seeing growing interest in cloud-based hardware access.

我的意思是，我們又交出了一個創紀錄的季度，主要受 AI 與 HPC 客戶的強勁需求所支撐。而且我們也看到市場對雲端式硬體存取的興趣正在增加。

The hardware-assisted verification is becoming increasingly important because customers are designing systems of unprecedented complexity. They need the capacity to verify those designs before committing to silicon. We have a strong pipeline entering Q4.

硬體輔助驗證變得愈來愈重要，因為客戶正在設計前所未有複雜的系統。他們需要在投入製作晶片之前，有能力去驗證這些設計。我們在進入第四季時有很強的案源（pipeline）。

We continue to expect another record year for hardware as always, harder could be lumpy from quarter to quarter depending on product deliveries and customer stellate schedules. But the underlying demand environment remains very strong, very healthy, and we're very, very encouraged by the pipeline of customer engagement.

我們仍預期硬體今年會再創紀錄；一如既往，硬體業務可能會因產品交付與客戶排程而在季度間出現波動。但底層需求環境依然非常強勁、非常健康，我們也對客戶互動的案源感到非常、非常鼓舞。

In terms of inventory, the increase in hardware inventories to support customer orders that we have a significant backlog that we're trying to work our way through, but there are no capacity or supply chain constraints in terms of addressing that.

至於庫存，硬體庫存的增加是為了支援客戶訂單；我們有相當可觀的積壓訂單（backlog）正在努力消化，但在處理這些訂單方面並不存在產能或供應鏈限制。

We're just building inventory to take those numbers. I think you asked about that's in part of the quarterly movement this quarter reflects the timing of annual cherishable contributions, which occurred in Q3 this year compared to Q4 last year.

我們只是建立庫存來承接那些數量。我想你問到的——本季的季度變動有一部分反映了年度慈善捐款的時點差異：今年發生在第三季，而去年是在第四季。

That would extrapolate that timing difference to the underlying G&A run rate. So there's a slight impact on G&A in Q3 because of that -- those cherishable contributions.

如果把這個時點差異外推到基礎的 G&A 常態水準（run rate）。因此第三季的 G&A 會因為——那些慈善捐款而有些微影響。

Yes. And Siti, just to add on the hardware piece. I mean Palladium and Protium performing exceptionally well. Not just for AI. And of course, we are working with all the major AI companies, but also any other kind of chip design right now, hardware became a indispensable, almost indispensable way to design these things.

是的。Siti，我再補充一下硬體部分。我的意思是，Palladium 和 Protium 的表現都非常出色。不只是用在 AI。當然，我們正與所有主要的 AI 公司合作，但就目前任何其他類型的晶片設計而言，硬體已經成為設計這些產品不可或缺、幾乎不可或缺的方式。

Now one thing is always like will this trend continue? And we'll see, but there's one megatrend, okay? So hardware is -- you probably know this already, but just to highlight it even further. Hardware is normally sold or consumed based on design size. So if the design size is bigger, then you need more and more hardware.

現在有一個問題總是：這個趨勢會不會持續？我們會再觀察，但有一個大趨勢（megatrend），好嗎？所以硬體——你可能已經知道了，但我再更進一步強調。硬體通常是依設計規模來銷售或使用的。所以如果設計規模更大，你就需要越來越多的硬體。

So actually, I was recently just an example of what is going to happen to design, I mean the design sizes are already big, but what's going to happen to design size in the future.

所以其實我最近——只是舉個例子，說明設計將會發生什麼，我是說，設計規模已經很大了，但未來設計規模會變成什麼樣子。

So just to give you an example, I was that IMEG recently, I gave a talk at IMEG, which is a European research consortium. And TSMC will also gave a talk same session.

舉例來說，我最近在 IMEG，我在 IMEG 做了一場演講；IMEG 是一個歐洲研究聯盟。而台積電也在同一場次做了演講。

So TSMC showed their process road map and said in the next five years, the chip size will go up by 48x. Now typically, this would happen to be like 5 to 10x in the old days, but I think it's going to be 48x because you have to add regular technology scaling plus 3D IC.

台積電展示了他們的製程路線圖，並表示在未來五年，晶片規模將增加 48 倍。過去通常可能是 5 到 10 倍，但我認為會是 48 倍，因為你必須把傳統製程微縮再加上 3D IC。

So all these 3D IC packaging wafer scale integration. So that's going to even further create more and more demand for hardware and die-to-die IP and things like that.

所以包含各種 3D IC 封裝、晶圓級整合。因此這將進一步帶來對硬體、die-to-die IP 等等越來越多的需求。

But -- so now our customers are not only verifying one chip or one chiplet, they're verifying those chiplet working with other chiplets and the size of the chips is going up and then a amount of chiplits are going up. So I think this trend, one criticality of hardware-based design and verification combined with the growth in size is going to continue for some time.

但是——所以現在我們的客戶不僅是在驗證單一晶片或單一晶粒（chiplet），他們也在驗證這些晶粒與其他晶粒協同運作；同時晶片尺寸在變大，晶粒的數量也在增加。因此我認為，這個趨勢——以硬體為基礎的設計與驗證的重要性，再加上尺寸成長——在未來一段時間仍將持續。

Joe Quatrochi, Wells Fargo.

Joe Quatrochi，富國銀行。

Yeah, thanks for taking the question. I was curious if you could just kind of talk about the change in the '26 outlook, particularly from an operating profit perspective because I think when you flow through just kind of the incremental margin on the upside of revenue, it's quite significant relative to maybe your kind of targeted over 50%. So maybe just any help there in terms of understanding what's going on there.

是的，謝謝讓我提問。我想請您談談對於 2026 年展望的變化，特別是從營業利益的角度來看；因為我認為，若把營收上行帶來的增量利潤率（incremental margin）帶入計算，這個數字相當可觀，且相較於你們可能目標的「超過 50%」還要顯著。所以想請您協助我們理解，這裡到底發生了什麼。

Sure. Yes. Look, we continue to be very pleased with the underlying profitability of the business, despite integrating Hexagon's DD business and making targeted investments in our strategic growth opportunities, we're now expecting approximately 44.7% non-GAAP operating margin for 2026, which is slightly above last year.

當然。是的。你看，儘管我們正在整合 Hexagon 的 DD 業務，並對我們的策略性成長機會進行有針對性的投資，我們仍然對業務的基本獲利能力感到非常滿意；目前我們預期 2026 年非 GAAP 營業利益率約為 44.7%，略高於去年。

But if you look at the revenue growth this year over last year, it's about $1.1 billion. Non-GAAP operating profit is growing about $500 million.

但如果你看今年相較去年的營收成長，大約是 11 億美元。非 GAAP 營業利益大約成長 5 億美元。

And would you consider the Hexagon's DEV being part of that. And that's not really contributing much to the way of operating profit at all this year. But -- and I think we said at the start of the year, we're expecting Hexagon to be about $160 million for the year, is doing slightly better than that, but it's pretty much on target.

那你會把 Hexagon 的 DEV 視為其中一部分嗎？而且今年它在營業利益方面其實幾乎沒有什麼貢獻。不過——我想我們在年初有說過，我們預期 Hexagon 全年大約 1.6 億美元，目前表現略好一些，但基本上符合目標。

But I mean, if you back that out, we'd be where you typically expect us to be, which is kind of mid-teens for revenue growth of high teens for EPS growth in our usual kind of 54%, 55% incremental margin rate. So the Hexagon DD is kind of impacting the incremental margin for this year.

但我的意思是，如果把那部分扣除掉，我們就會回到你們通常對我們的預期：營收成長約在十幾個百分點中段，而 EPS 成長在十幾個百分點高段，並且維持我們一貫約 54%、55% 的增量利潤率。所以 Hexagon 的 DD 今年確實在影響增量利潤率。

But we'd expect that to help us next year because the integration go really well. And we're taking steps now to improve things for next year in the same way as we did with paid the last couple of years.

但我們預期明年它會對我們有幫助，因為整合進展非常順利。而且我們現在正在採取措施，為明年改善狀況，就像過去幾年我們對「paid」所做的一樣。

Charles Shi, Needham & Company.

Charles Shi，Needham & Company。

Thanks for taking my question. Hey, Anilu, glad to hear about the Metro model portfolio just announced today. In light of your competitor who announced the GPG synopsis, can you tell us what your thoughts are regarding collaborating maybe with the Frontier labs for a specialized model, given that Maestro based on what you just described, it sounds like it's a collection of open models post train by cadence.

謝謝讓我提問。嗨，Anilu，很高興聽到今天剛宣布的 Metro 模型組合。鑑於你們的競爭對手宣布了 GPG synopsis，你能否談談你們對於可能與 Frontier Labs 合作打造專用模型的看法？因為依你剛才的描述，Maestro 聽起來像是由 Cadence 進行後訓練（post-train）的一系列開放模型集合。

And I think now your customers also have choices between your model portfolio, and let's say GPT synopsis, what do you tell your customers when they have both choices and why they should take Cadence?

而且我想現在你們的客戶在你們的模型組合與例如 GPT synopsis 之間也有選擇；當客戶兩者都有時，你們會怎麼跟客戶說、為什麼他們應該選 Cadence？

Yeah. Thanks for the question, Charles. So first of all, I just want to point out that we have worked with open AI from the very beginning of when they got started. So in terms of chip design, and we have all kinds of collaborations with open AI. And same thing with Entropic and Gemini, the three leading frontier model.

是的，謝謝你的問題，Charles。首先我想指出，我們從 OpenAI 剛開始起步時就一直與他們合作。因此在晶片設計方面，我們與 OpenAI 有各式各樣的合作；同樣地，與 Entropic 和 Gemini 也是如此，這三者是領先的 frontier model。

So we always discuss all kinds of collaborations with them. Now in terms of what we want to make sure as -- in Maestro, the key thing is Maestro is not just our own models, but it still has maximum flexibility to use the right model for the right task.

所以我們一直都在與他們討論各種合作可能。至於我們要確保的——在 Maestro 裡，關鍵在於 Maestro 不只是我們自己的模型，同時也具備最大的彈性，能針對不同任務使用最合適的模型。

So let's say, if certain for a certain percentage of task, a certain frontier model is better, we will, of course, use that to give the best performance to our customers.

例如，若在某一部分任務上，某個 frontier model 表現更好，我們當然會使用它，為客戶提供最佳效能。

But the key thing in our solution is that we want to control the three 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.

但我們解決方案的關鍵是：我們希望掌控「蛋糕的三層」，並且掌控與客戶的互動。我們希望成為客戶的主要介面，而這也是客戶所希望的。

And in return, our agents will provide them a lot of value, and we'll use the right LLM for the task, okay? But the critical thing is as we became the primary interface, and we guarantee the confidentiality of our data and their data.

作為回報，我們的代理（agents）會為他們提供大量價值，而我們也會針對任務使用合適的 LLM，好嗎？但最關鍵的是，當我們成為主要介面時，我們能保證我們的資料以及他們的資料的機密性。

So the other thing we will allow with Maestro is if a customer wants to post train Maestro further, and 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?

另外，Maestro 也會允許：如果客戶想要進一步對 Maestro 進行後訓練——這也是客戶的另一項需求——我們會允許。如果客戶想要在地端（on-prem）部署，我們會允許。如果客戶想要在雲端託管，我們也會允許，好嗎？

So it gives maximum flexibility and maximum performance by combining all three layers and only Cadence can provide this. And that will give without any doubt, the best results for our customers.

因此，透過結合三層架構，它能提供最大的彈性與最佳效能，而只有 Cadence 能提供這一點。而這毫無疑問會為我們的客戶帶來最好的結果。

Harlan Sur, JP Morgan.

Harlan Sur，摩根大通。

Yeah, good afternoon. Thanks for taking my question. I don't really last quarter, you mentioned the pickup in the more traditional analog power microcontroller segments of the market, right, targeting industrial, automotive, consumer IoT, that's the positive cyclical dynamics we're seeing now as excess customer inventories have bottomed in these end markets.

是的，午安。謝謝讓我提問。我記得上季你提到，在較傳統的類比電源與微控制器等市場區隔出現回升，對吧，主要面向工業、車用、消費性 IoT；隨著這些終端市場的客戶過剩庫存已觸底，我們現在看到正向的景氣循環動能。

Are you continuing to see the positive demand trends in this segment? And do 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 trip designs, our analog customers are designing more sensor-related capabilities into their chips more ADD/DDA converters on top DSP processing. Is this also translating into a better book of business for the Cadence team?

你們是否仍持續看到這個區隔的正向需求趨勢？另外，這些公司是否也正高度聚焦於把下一代、以實體 AI（physical AI）為基礎的能力嵌入其晶片設計中？例如你們的 MCU 客戶正在把 NPU 能力加入他們的晶片設計；你們的類比客戶則在晶片中設計更多與感測器相關的能力，在 DSP 處理之上加入更多 ADC/DAC 轉換器。這是否也正在轉化為 Cadence 團隊更好的業務訂單能見度（book of business）？

Yes, Harlan. I guess a great point. So I think the momentum is very strong in analog and mixed signal, and you can look at their results as well, driven by physical AI and overall recovery of the market. And of course, memory, which we work with all the big memory companies is having, of course, amazing improvement from a year or two ago. And I think what it shows up is, first of all, we are very, very strong in mix-signal companies.

是的，Harlan。我想你提得很好。所以我認為在類比與混合訊號方面的動能非常強，你也可以從他們的業績看出來，這主要由實體 AI 以及整體市場復甦所帶動。當然還有記憶體——我們與所有大型記憶體公司都有合作——相較一兩年前也有非常驚人的改善。我認為這反映出，首先，我們在混合訊號公司方面非常、非常強。

So because we have the most complete portfolio with both analog and digital, so these are designs like you mentioned, are more and more mixed signals. So that plays to Cadence's trend. And also ViraStack.

因為我們同時涵蓋類比與數位，擁有最完整的產品組合；因此如你所提到的這些設計，正變得越來越偏向混合訊號。這就符合 Cadence 的趨勢優勢。以及 ViraStack。

I'm really pleased by the momentum in ViraStack because as analog customers, whether they are mixed signal companies or these big AI companies also have huge team. I don't know if you realized that some of these big AI companies designing their own IP and all have huge analyst teams.

我對 ViraStack 的動能感到非常滿意，因為類比客戶——不論是混合訊號公司，或是這些大型 AI 公司——也都有龐大的團隊。我不知道你是否注意到，其中一些大型 AI 公司正在設計自有 IP，而且都有非常龐大的分析師團隊。

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, we can do a lot more in analog productivity.

因此，對於類比生產力有龐大的需求，而我們先前無法提供。我的意思是，我們一直都想做到。但有了代理式 AI（Agentic AI），我們在類比生產力方面可以做得更多。

And you can see that in some of the customer codes we have seen and the amount of engagements we have with ViraStack. So overall, I'm pretty pleased not just with the environment of analog mixed signal, but also the new capabilities we are launching with ViraStack.

你也可以從我們看到的一些客戶程式碼，以及我們與 ViraStack 的互動參與程度中看出來。所以整體而言，我不僅對類比混合訊號的環境感到相當滿意，也對我們透過 ViraStack 推出的新能力感到滿意。

Joe Vruwink, Baird.

Joe Vruwink，Baird。

(Operator Instructions) Lee Simpson, Morgan Stanley.

(接線員指示) Lee Simpson，Morgan Stanley。

Great, thanks for fitting me in here. Anirudh, it does seem as though you and your peer are pursuing very distinct routes to monetizing agent in chip design. I mean, I thought you answered one of the previous questions quite well. It really does bring out that you're looking to have your own control on the modeling your deployment flexibility comes through.

很好，謝謝你把我安排進來。Anirudh，看起來你和你的同業在晶片設計中將代理變現（monetizing agent）所走的路線非常不同。我的意思是，我覺得你對前面其中一個問題的回答相當好。這確實凸顯出你們希望對建模有自己的掌控，而你們的部署彈性也因此展現出來。

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 costs that really led you to go down this route in strategy?

因此你認為，相較於以前沿模型（frontier model）為中心的合作夥伴關係，這種你所看到的採用方式將會獲得相當不錯的採用率。但在效能上是否有什麼我們需要更深入理解的地方，或甚至在交付成本上，是否有什麼因素真正促使你們在策略上選擇走這條路？

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's anything specific to call out there. Are they taking just typical IP blocks, or does it come with any broader IP services attached?

另外再追問一題。你確實提到一家領先的太空公司正在採用你們的一些 IP。想請問那裡有沒有什麼具體可以補充的？他們是只採用典型的 IP 模組（IP blocks），還是也包含任何更廣泛的 IP 服務？

Yes. Let me answer the second part first, I come back to the first one. I mean, in general, like we have mentioned that now 45% of our business is coming from the system companies, the nontraditional versus the traditional semi, so these are new customers.

是的。我先回答第二部分，再回到第一部分。一般來說，正如我們提到的，現在我們有 45% 的業務來自系統公司，也就是非傳統半導體客戶，相較於傳統半導體客戶而言，這些都是新客戶。

And what is also encouraging to see is that it's not just big AI, hyperscalers whether doing design. But we are seeing a lot of other system companies like the one we highlighted like a space company even companies in finance doing their own chips.

而且令人鼓舞的是，這不只是大型 AI 超大規模業者（hyperscalers）在做設計。我們也看到許多其他系統公司，例如我們提到的那家太空公司，甚至金融業的公司也在做自己的晶片。

Okay, this is -- as we make chip design easier and easier, this is always the promise that more and more companies we'll do that. And when these new companies do design, we naturally have IP opportunities but also hardware and also naturally design services because they're getting started.

好的，隨著我們讓晶片設計變得越來越容易，這一直是我們的承諾：會有越來越多公司投入其中。而當這些新公司開始做設計時，我們自然會有 IP 機會，也會有硬體機會，並且也自然會有設計服務的需求，因為他們才剛起步。

And we have one of the best design services capabilities as we are the best at using our own products. So I think this is some space we have to watch, but I'm pretty encouraged by more system companies doing chip design. Now coming back to the to the AI solution, we want to have control and we want to give flexibility to our customers.

而我們擁有業界最好的設計服務能力之一，因為我們最擅長使用自家的產品。所以我認為這是一個值得關注的領域，但我對更多系統公司投入晶片設計感到相當鼓舞。現在回到 AI 解決方案，我們希望掌握控制權，也希望給客戶彈性。

So this is the right way to look at it. So -- and there is a lot of value in the model itself, and it is actually pretty cost economical to post train a frontier class model.

所以這是正確的看法。而且模型本身有很大的價值，對一個前沿等級（frontier class）的模型做後訓練（post-train）其實相當具成本效益。

Okay, this could not have happened like two years ago. But now it's actually pretty manageable cost to -- and we get pretty remarkable results, like I mentioned, by very incremental cost to post train a frontier model. And of course, that's an important thing to have in the bag along with a commercially available frontier model.

好的，這在兩年前是不可能發生的。但現在要做到這件事的成本其實相當可控——而且如我所提到的，只需要非常小幅的增量成本去對前沿模型做後訓練，我們就能得到相當驚人的成果。當然，除了商用可取得的前沿模型之外，這也是我們工具箱裡很重要的一項能力。

It's just using the best solution of the two. And then in our own genic development, right? We have our own IP team, a lot of people using our -- of course, using agent stack and all the solutions. So the benefits of costs apply to us as well. So even though there is some incremental expense to train them, there's also incremental saving in our own deployment of AI.

這就是把兩者中最好的方案拿來用。然後在我們自己的代理式（genic）開發上，對吧？我們有自己的 IP 團隊，也有很多人在使用我們的——當然，是使用 agent stack 以及所有解決方案。所以成本上的好處也同樣適用於我們。因此，即便訓練它們會有一些增量費用，我們在自身 AI 部署上也會有相應的增量節省。

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 though as we have planned for a while. But what Maestro does is this flexibility, but also gives customization ability, it gives control and then it gives cost savings. So this is best of all words.

所以整體而言，我認為這不會影響任何對 Cadence 的財務模型；隨著我們新增一種新的營收能力，它只會變得更強，而毛利率的提升等也都會如我們規劃已久的方式推進。但 Maestro 所帶來的是彈性，同時也提供客製化能力、提供控制權，並帶來成本節省。所以這是各方面都最好的結果。

Yes, Lee, if I could add there. I think that that's 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 cadences, debate expertise and deep integration with our design tools.

是的，Lee，如果我可以補充一下。我認為 Anirudh 在彈性方面提出的是非常、非常重要的一點。我們真的希望客戶在使用哪些模型上擁有選擇權與控制權，同時也能受益於 Cadence 的領域專業與與我們設計工具的深度整合。

I mean our strategy remains centered on delivering high-value engineering software rather than building a large general purpose AI infrastructure business. We're focused on improving the efficiency and the value of agentive workflows and maintaining attractive software economics as customer adoption scales, but we think the flexibility works in our model.

我的意思是，我們的策略仍然以提供高價值的工程軟體為核心，而不是去建立一個大型的通用 AI 基礎設施業務。我們專注於提升代理式工作流程（agentive workflows）的效率與價值，並在客戶採用規模擴大時維持具吸引力的軟體經濟性，但我們認為這種彈性與我們的商業模式是相符的。

Our model allows customers to use their old LLM infrastructure bear their associated bottle compute cost if they want to, a Cadence, the underlying design and orogenic orchestrate capabilities. The economics of particular deployment options could vary, of course, but the principle is that greater customer usage should create greater value for Cadence. So I think that's where we differentiate ourselves.

我們的模式允許客戶如果願意，可以使用他們既有的 LLM 基礎設施並承擔其相關的算力成本，而 Cadence 則提供底層的設計能力以及代理式編排（orogenic orchestrate）能力。當然，不同部署選項的經濟性可能會有所差異，但原則是：客戶使用越多，應該就能為 Cadence 創造越大的價值。所以我認為這就是我們的差異化所在。

Joe Vruwink, Baird.

Joe Vruwink，Baird。

Hi, can you hear me?

嗨，你聽得到我嗎？

Yes, Joe, please go ahead.

是的，Joe，請繼續。

Great. I want to go back to ViraStack and InnoStack. I think it's that the analog and back-end areas haven't 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?

很好。我想回到 ViraStack 和 InnoStack。我認為類比與後端領域，還沒有像前端設計那樣看到 AI 的普及。你們是否看到這種變化——也就是專用模型與後訓練——能更好地應對這些領域？如果這一切開始發生，對 Cadence 而言，相較於迄今為止所看到的情況，是否會帶來相應更高的營收意涵？

Yeah, hi, Joe, I mean, first of all, it there is we started with chip stack, but then we have launched like three other major super agents, as you know, ViraStack for analog, InnoStack for back end, and AuraStack, the latest one, for package and PCB.

是的，嗨，Joe。首先，我們是從 Chip Stack 開始，但如你所知，我們之後又推出了另外三個主要的超級代理：用於類比的 ViraStack、用於後端的 InnoStack，以及最新用於封裝與 PCB 的 AuraStack。

And I have to say the demand is actually phenomenal in mind is phenomenal, and especially because these chip stack is doing great, but also these other agents are even more integrated with our base tools.

我必須說，需求確實非常驚人，我的意思是非常驚人；尤其是因為 Chip Stack 表現很好，但這些其他代理與我們的基礎工具整合得更深。

So InnoStack, if you look at our endorsement, typically, when we work with customers to get a public endorsement is only happens like 1 out of 10 customers because not everybody wants to talk about what they're doing, but we have maybe 10 endorsements this quarter.

所以以 InnoStack 來說，如果你看我們的背書（endorsement），通常我們與客戶合作取得公開背書，大概只有 10 個客戶裡才會有 1 個，因為不是每個人都想談他們在做什麼，但我們這一季可能有大約 10 個背書。

So that tells you the extent of the deployment of all these agents. And if you look at InnoStack, Renesas talking about like 34x productivity improvement, Samsung Foundry, see, there are other use cases that can happen, not just physical design.

所以這能告訴你所有這些代理的部署程度。而如果你看 InnoStack，Renesas 提到大約 34 倍的生產力提升，Samsung Foundry——你看，還有其他可能發生的使用案例，不只是實體設計（physical design）。

One big use case is design technology co-optimization with the foundry. So the InnoStack a critical agent for that. Socionext talked about 5x productivity improvement. Rapido talked about 2x improvement. So there's a multiple improvement happening with InnoStack.

一個很大的使用案例是與晶圓代工廠進行設計技術協同最佳化（DTCO）。因此 InnoStack 是其中的關鍵推動者。Socionext 提到生產力提升 5 倍。Rapido 提到提升 2 倍。所以透過 InnoStack 正在發生多重層面的提升。

ViraStack take already said that demand is off the charts. And AuraStack, this the latest area where innovation hasn't happened. So Nokia showed 5x productivity improvement with AuraStack.

ViraStack 團隊已經說過需求爆量。而 AuraStack 是最新的領域，過去創新相對較少。因此 Nokia 展示了使用 AuraStack 可帶來 5 倍的生產力提升。

So ChipStack is probably a year now in deployment, and these are maybe six to nine 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.

因此 ChipStack 大概已部署一年左右，而這些可能是六到九個月，但這些（較新的）正在加速部署——而且它們與底層工具的整合更緊密。接著 Maestro 在這些能力之上再增加進一步的差異化。

So I feel very, very confident. And what's 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.

所以我非常、非常有信心。接下來會發生的是：我們在中間層的傳統工具上投入了大量研發，但現在我們正在頂層投入顯著的差異化與投資。

We are defining, I believe, what will be the identic flow for the future in all industries. So as we make the Agentic, the top layer, and more and more complicated, more and more integrated, more and more differentiated, is very difficult to compete with Cadence in the Agentic AI, whether you're a start-up or if you are trying to write -- a customer tried to write some agents, but the capabilities with motor routing with domain-specific models with tight integration with agent and the tools. This is something that our customers can't do themselves.

我相信我們正在定義未來各行各業的 Agentic 流程樣貌。因此，當我們把 Agentic（頂層）做得越來越複雜、越來越整合、越來越差異化時，無論你是新創公司，或是客戶嘗試自己寫一些代理（agents），都很難在 Agentic AI 上與 Cadence 競爭，因為我們具備動態路由、領域專屬模型，以及代理與工具之間的緊密整合能力。這些是我們的客戶自己做不到的。

So that also bodes very well for all of 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.

因此，這也非常有利於讓所有這些客戶意識到這點，並且不只是與我們在中間層合作，而是在頂層也越來越緊密地合作。所以就我們 Agentic 產品的速度與差異化而言，我感覺非常好。

Jay Vleeschhouwer, Griffin Securities.

Jay Vleeschhouwer，Griffin Securities。

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's demonstrable that over the last number of years, you've gained considerable share in core EDA. But I'd like to delve into what the components of that share gain have been.

謝謝。晚安。Anirudh，在你準備好的發言中，你提到核心 EDA 的組成要素，特別是在數位領域，這些提法很重要。很明顯在過去幾年，你們在核心 EDA 取得了相當可觀的市占提升。但我想深入探討，這些市占提升的構成來源是什麼。

In other words, when we think about the various large categories that comprise core EDA, especially digital, would it be fair to say that the single largest difference in terms of the dollar and share gain you've 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 and so forth.

換句話說，當我們思考構成核心 EDA 的各個大型類別，尤其是數位領域時，是否可以說，過去幾年你們在金額與市占上的最大差異，主要來自 Innovus 在實作（implementation）方面的表現；其次可能是在綜合（synthesis）、RTL 模擬、分析等領域的提升？

Or perhaps you can speak about the breadth of where that incremental revenue and shares come from in core EDA to the extent that it's not really largely concentrated in banks and route.

或者你也可以談談：在核心 EDA 中，這些增量營收與市占的來源範圍有多廣——如果它並不是主要集中在布局與繞線（place and route）的話。

Yeah, Jay, great question. So yes, I mean, over the -- if you look at over five, seven years, we have gained so much in digital implementation, which I was becoming basically the platform of choice for advanced nodes design.

是的，Jay，問得很好。所以是的，我的意思是，如果你看過去五到七年，我們在數位實作方面取得了很大的進展，基本上成為先進製程節點設計的首選平台。

And then what is particularly encouraging in the last 6 to 12 months is not just Innovus, but all the tools around Innovus. And we always -- I have talked about for 10 years now. Of course, there's integration at lower nodes.

而在過去 6 到 12 個月特別令人鼓舞的是，不只是 Innovus，而是 Innovus 周邊的所有工具。而且我們一直——我已經談了 10 年了。當然，在更先進節點會有更深的整合。

So that was going to happen anyway as we go to 3-nanometer, 2-nanometer, it's difficult to separate sign-off from implementation or synthesis from implementation. But then with this Agentic AI, there's a further kind of need for vertical flows, which are well integrated.

因此，當我們走向 3 奈米、2 奈米時，這本來就會發生：很難把簽核（sign-off）與實作分開，或把綜合與實作分開。但隨著這種 Agentic AI 的出現，對於垂直整合、整體流程高度整合的需求又更進一步提升。

So what I -- and I mentioned this last quarter also, I'm particularly pleased to see -- I mean, not only our tools and synthesis and sign-off are much, much better now versus a 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, we maintain our undisputed leadership in analog, okay?

所以我——我上季也提過，我特別高興看到——我的意思是，不僅我們的綜合與簽核工具相較幾年前已經好很多、很多。我們也看到真正的全流程部署，不只是在中小型客戶，還有一些非常、非常大型的客戶正在部署我們完整的數位流程，這對 Cadence 來說是很好的趨勢。同時，我們也維持在類比領域無可爭議的領導地位，好嗎？

And then because of the strength of Palladium, strength of Jasper, strength of Verasium and Agentic Flow ChipStack, it is also helping our verification business and logic simulation.

此外，憑藉 Palladium 的強勢、Jasper 的強勢、Verasium 與 Agentic Flow ChipStack 的強勢，也正在帶動我們的驗證業務與邏輯模擬。

So overall, that's what I was saying, I feel that all the three 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 advanced integration with the agentic solution. So we'll see how it is. But overall, I feel pretty good about it.

所以整體而言，這就是我所說的：我覺得 EDA 的三大部分我們都處在非常、非常強的位置，並且動能持續增強；不只是單一工具變得更好、並由大型公司驗證，也包括與 agentic 解決方案的先進整合。所以我們再看看後續如何發展。但整體來說，我感覺相當不錯。

Gary Mobley, StoneX.

Gary Mobley，StoneX。

Hi, guys. Good afternoon. Thanks for taking my question. Your bookings in the somewhere in the ballpark of, I don't know, mid-20%, call it, 26% year-over-year. If I recall correctly, this was supposed to be a low renewal period 2026 was supposed to be.

嗨，各位。午安。謝謝讓我提問。你們的訂單（bookings）大概在二十幾個百分點的區間，我不知道，算中段吧，姑且說年增 26%。如果我沒記錯，原本 2026 年應該是續約相對偏低的期間。

So my question is, what's driving the strong backlog, the strong bookings? Is it utilizing traditional EDA tools as a result of 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.

所以我的問題是：是什麼在推動強勁的待履約訂單（backlog）與強勁的訂單（bookings）？是因為 AI 代理工作流程而帶動傳統 EDA 工具的使用嗎？還是反映半導體產業景氣強勁？你能補充一些說明會很有幫助。謝謝。

Sure. Thanks, Gary. I mean, we're very pleased with the both the bookings performance and the growth in backlog, particularly given that 2026, as you mentioned, is it comparatively light new year for us. The strength reflects the underlying desire activity, expanded customer engagement and strong add-on opportunities across our portfolio.

當然。謝謝你，Gary。我的意思是，我們對訂單表現與待履約訂單的成長都非常滿意，特別是考量到你提到的 2026 年對我們而言相對是新年度較輕的一年。這樣的強勁表現反映了底層需求活動、客戶互動的擴大，以及我們整體產品組合中強勁的加購（add-on）機會。

And what we're 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.

我們看到的是：當客戶希望加速其工程路線圖並應對更複雜的設計挑戰時，Cadence 對他們而言正變得愈來愈重要；而待履約訂單本身也提供了良好的能見度。

But it's important to revert that backlog and bookings number reflects the timing of revenue recognition that depends on the structure and delivery of a digital ratio stuff like that.

但重要的是要回到一點：待履約訂單與訂單數字反映的是收入認列時點，而這取決於合約結構與交付方式、數位（相關）比率之類的因素。

But -- so there's always a blade type add value in those. But strong bookings in a lighter renew here are particularly encouraging because they reflect expanding customer engagements adoptively the renewal calendar. But we're very, very pleased with that booking strength.

但是——所以其中總會有一些時間差所帶來的附加價值。不過，在續約相對較輕的一年仍能有強勁訂單，特別令人鼓舞，因為這反映了客戶互動在續約行事曆之外仍在擴大。但我們對這樣的訂單強度感到非常、非常滿意。

So Gary, needless to say, I mean, we've done three quarters. There's still one more quarter to go, which is traditionally strong this quarter. So we'll see where we end up.

所以 Gary，不用說，我們已經走過三個季度。還有最後一個季度要走，而傳統上這一季通常很強。所以我們看看最後會落在哪裡。

Lachlan Brow, Rothschild .

Lachlan Brow，Rothschild。

Hi, Anirudh, John. Thanks for squeezing me in. Are you seeing much evidence that new AI design tools like ChipStack lowering the barriers to intrigue for custom silicon for nontraditional designers. And I appreciate that land 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.

嗨，Anirudh、John。感謝你們把我排進來。你們是否看到新的 AI 設計工具（例如 ChipStack）正在降低非傳統設計者為客製化矽晶片進行設計的門檻的跡象？我也理解市場自然擴張需要時間。但是否有跡象顯示，新客戶標誌（new logos）未來可能成為推動該 TAM 擴張更具意義的成長動能？謝謝。

Yeah, absolutely. I mean like I've talked about this for years that as we make chip design easier to do, there will be more and more people doing chip design.

是的，絕對有。我的意思是，我多年來一直在談這件事：當我們讓晶片設計更容易做，就會有越來越多人投入晶片設計。

And if you step back, we made chip design maybe over the last 20 years, 100x easier to do because maybe 20 years ago, all these IBM Intel would do like CPU design with 500 people in like five years. Now you can do a CPU design 6 months with like 50 people. So that's like 100x better.

如果你退一步看，過去 20 年我們讓晶片設計變得大概容易了 100 倍，因為大約 20 年前，像 IBM、Intel 這些公司做 CPU 設計，可能要 500 個人、花五年。現在你可以用大概 50 個人、6 個月就完成一個 CPU 設計。所以這大概是提升了 100 倍。

And that's what led to more and more designs. And with AI, we can have and add another 5 to 10x. So it will be like 1,000x easier than probably 20, 25 years ago. And this was invariably lead to more and more design activity.

而這也帶來越來越多的設計。再加上 AI，我們還可以再提升 5 到 10 倍。所以相較於 20、25 年前，可能會變得容易 1,000 倍。而這將不可避免地帶來越來越多的設計活動。

And you can see that even with the hyperscalers, if you go back one or two years ago, it was not clear that the hyperscalers will do or we always get questions will they continue to do, but now with Google and Meta and Microsoft, Amazon and Tesla, everybody is doing more and more designs.

你也可以從超大規模雲端業者（hyperscalers）看到這點：如果回到一兩年前，還不清楚他們是否會做（或我們總是被問到他們是否會持續做），但現在 Google、Meta、Microsoft、Amazon、Tesla，大家都在做越來越多的設計。

Now at the same time, the traditional semiconductor companies are also doing well, of course, the big semi companies.

同時，傳統的半導體公司當然也表現得很好，尤其是大型半導體公司。

And this is only going to accelerate, in my opinion, with -- like we talked about space companies, finance companies, physical car companies, the amount of design activity we are seeing in automotive is actually quite remarkable and robotics and things like that.

而且依我看，這只會加速——就像我們談到的太空公司、金融公司、實體車廠等；我們在汽車領域看到的設計活動量其實相當驚人，還有機器人等領域也是如此。

And then these things, robotics also require a lot of different chips, right? The amount of chips that are there in one hand, there are like 25 chips in one hand of a humanoid robot to control all the individual motors. So I think we are -- I believe this for years, and I think you will see more and more of this.

另外，這些事情——機器人也需要很多不同的晶片，對吧？一個人形機器人的一隻手裡就有大約 25 顆晶片，用來控制每一個獨立的馬達。所以我認為——我多年來一直相信這點，而且我想你會看到越來越多這樣的情況。

And our job is to make these things easier to use, have more -- give more flexibility to our customers, like we did with our agent solution in Maestro, so they can do more themselves.

而我們的工作就是讓這些東西更容易使用，為客戶提供更多——給客戶更大的彈性，就像我們在 Maestro 裡的代理（agent）解決方案所做的那樣，讓他們能自己完成更多事情。

Kelsey Chia, Citi.

Kelsey Chia，花旗（Citi）。

Hi, Anirudh and John, congrats on great results. My question is on EDA. EDA growth has been very strong for the last three quarters, 18%, 19% year-on-year growth well above our historical growth rate. And it sounds like a majority of that growth is primarily driven by hardware and agent attribution is still quite small. Is that a fair characterization?

嗨，Anirudh 和 John，恭喜你們取得很棒的成果。我的問題是關於 EDA。過去三個季度 EDA 成長非常強勁，年增 18%、19%，明顯高於我們的歷史成長率。而聽起來其中大部分成長主要是由硬體帶動，而 Agentic 的貢獻仍然相當小。這樣的描述公平嗎？

Or could you give us a sense of customer adoption levels for identic workflow today? And as much of the sort of revenue acceleration from Agentic AI as to ahead of us?

或者你們能否讓我們了解一下，目前客戶對 agentic 工作流程的採用程度？以及由 Agentic AI 帶來的那種營收加速，有多少還在未來？

Yes, 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.

是的，謝謝你的問題。是的，當然，我們對硬體成長非常自豪。但如你所知，我們會拆分經常性與非經常性成長。所以就像我先前提到的，John 也提到，我們的經常性成長率已從去年的 11% 提升到 18%。所以那不是硬體。

That's ex hardware because hardware will typically show up in nonrecurring growth. So that's 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.

那是扣除硬體（ex hardware）之後的數字，因為硬體通常會反映在非經常性成長中。因此，我們的經常性成長從去年到今年有了重大改善。而這是 Agentic AI 加上軟體端底層工具的成長與設計啟動（design starts）增加的綜合結果。

Yeah. Kelsey, I think based on lists to answer Anirudh's question there a few minutes ago that 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.

是的。Kelsey，我想接著回答 Anirudh 幾分鐘前的問題：基本上，我們認為 Agentic AI 是 EDA 的需求加速器。我的意思是，客戶一直都會圍繞 Cadence 工具建立他們自己的工作流程。我們也預期他們會持續開發自己的代理（agents）。我們的策略也能配合這點。

What's exciting because that agents could perform much more designed exploration than an individual engineer, calling our underlying engines repeatedly, and that creates a potential for significantly more consumption of our core EDA tools. And I think you're starting to see that reflected in our EDA growth this year.

令人興奮的是，代理能夠比單一工程師進行更多的設計探索，反覆呼叫我們的底層引擎，而這會帶來我們核心 EDA 工具顯著更高的使用量（consumption）的潛力。我想你今年已開始在我們的 EDA 成長中看到這點反映。

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

目前沒有其他問題。我現在把時間交回給 Anirudh Devgan 作結語。

Thank you all for joining us this afternoon. It's an 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 two among all S&P 500 companies in its 2026 Best Board list.

感謝各位今天下午加入我們。Cadence 在以 AI 驅動的產品領導力與強勁的業務動能下完成第三季，這是一個令人振奮的時刻。《華爾街日報》在其 2026 年最佳董事會名單中，將 Cadence 的董事會在所有 S&P 500 公司中排名第二。

And on behalf of our employees and of our Board of Directors, we thank our customers, partners and investors for their continued trust and confidence in Cadence.

我謹代表我們的員工與董事會，感謝客戶、合作夥伴與投資人持續對 Cadence 的信任與支持。

Thank you for participating in today's Cadence third quarter 2026 earnings conference call. This concludes today's call. You may now disconnect.

感謝各位參與 Cadence 2026 年第三季財報電話會議。今天的會議到此結束。您現在可以掛線。