微软(MSFT)2026 财年第二季度财报电话会议

Microsoft Corporation (MSFT) Q2 2026 Earnings Call January 28, 2026 5:30 PM EST
微软公司（MSFT）2026 财年第二季度财报电话会议 2026 年 1 月 28 日，美国东部时间下午 5:30

Company Participants
公司参会人员

Jonathan Neilson - Vice President of Investor Relations
乔纳森·尼尔森——投资者关系副总裁
Satya Nadella - Chairman & CEO
萨提亚·纳德拉——董事长兼首席执行官
Amy Hood - Executive VP & CFO
艾米·胡德——执行副总裁兼首席财务官

Conference Call Participants
电话会议参会人员

Keith Weiss - Morgan Stanley, Research Division
基思·魏斯——摩根士丹利研究部
Mark Moerdler - Bernstein Institutional Services LLC, Research Division
马克·莫尔德勒——伯恩斯坦机构服务有限责任公司研究部
Brent Thill - Jefferies LLC, Research Division
布伦特·希尔——杰富瑞有限责任公司研究部
Karl Keirstead - UBS Investment Bank, Research Division
卡尔·凯尔斯塔德——瑞银投资银行研究部
Mark Murphy - JPMorgan Chase & Co, Research Division
马克·墨菲——摩根大通公司，研究部
Brad Zelnick - Deutsche Bank AG, Research Division
布拉德·泽尔尼克——德意志银行股份有限公司，研究部
Raimo Lenschow - Barclays Bank PLC, Research Division
雷莫·伦舍尔——巴克莱银行 plc，研究部

Presentation
演示环节

Operator
操作员

Greetings, and welcome to the Microsoft Fiscal Year 2026 Second Quarter Earnings Conference Call. [Operator Instructions] As a reminder, this conference is being recorded. It is now my pleasure to introduce Jonathan Neilson, Vice President of Investor Relations. Please go ahead.
各位好，欢迎参加微软公司 2026 财年第二季度财报电话会议。[操作员说明] 提醒各位，本次会议正在录音。接下来，我很荣幸地为大家介绍投资者关系副总裁乔纳森·尼尔森。请开始您的发言。

Jonathan Neilson
乔纳森·尼尔森
Vice President of Investor Relations
投资者关系副总裁

Good afternoon, and thank you for joining us today. On the call with me are Satya Nadella, Chairman and Chief Executive Officer; Amy Hood, Chief Financial Officer; Alice Jolla, Chief Accounting Officer; and Keith Dolliver, Corporate Secretary and Deputy General Counsel.
下午好，感谢各位今天参与本次电话会议。与我一同出席本次会议的有：董事长兼首席执行官萨提亚·纳德拉（Satya Nadella）；首席财务官艾米·胡德（Amy Hood）；首席会计官爱丽丝·乔拉（Alice Jolla）；以及公司秘书兼副首席法律顾问基思·多利弗（Keith Dolliver）。

On the Microsoft Investor Relations website, you can find our earnings press release and financial summary slide deck, which is intended to supplement our prepared remarks during today's call and provides the reconciliation of differences between GAAP and non-GAAP financial measures. More detailed outlook slides will be available on the Microsoft Investor Relations website where we provide outlook commentary on today's call.
在微软投资者关系网站上，您可查阅我们的财报新闻稿及财务摘要幻灯片资料包。该资料包旨在补充我们今天电话会议中的准备发言，并提供美国通用会计准则（GAAP）与非 GAAP 财务指标之间差异的调节说明。更详尽的业绩展望幻灯片将在微软投资者关系网站上同步发布，其中亦包含我们今日电话会议中所作的业绩展望相关评论。

On this call, we will discuss certain non-GAAP items. The non-GAAP financial measures provided should not be considered as a substitute for or superior to the measures of financial performance prepared in accordance with GAAP. They are included as additional clarifying items to aid investors in further understanding the company's second quarter performance in addition to the impact these items and events have on the financial results.
在本次电话会议中，我们将讨论若干非 GAAP 项目。所提供的非 GAAP 财务指标不应被视为对按照美国通用会计准则（GAAP）编制的财务业绩指标的替代或更优选择。这些指标仅作为补充性说明信息予以披露，旨在帮助投资者进一步理解公司第二财季的经营表现，以及相关事项与事件对公司财务结果所造成的影响。

All growth comparisons we make on the call today relates to the corresponding period of last year, unless otherwise noted. We will also provide growth rates in constant currency when available as a framework for assessing how our underlying businesses performed, excluding the effect of foreign currency rate fluctuations. Where growth rates are the same in constant currency, we will refer to the growth rate only.
本次电话会议中我们所作的所有增长对比，均基于去年同期数据，除非另有说明。此外，我们还将提供以不变汇率计算的增长率（如可获得），以便在排除汇率波动影响的情况下评估公司各业务板块的实际表现。当以不变汇率计算的增长率与报告增长率一致时，我们将仅提及该增长率。

We will post our prepared remarks to our website immediately following the call until the complete transcript is available.
我们的会议准备稿将在电话会议结束后立即发布至公司官网，直至完整文字记录稿上线。

Today's call is being webcast live and recorded. If you ask a question, it will be included in our live transmission, in the transcript, and in any future use of the recording. You can replay the call and view the transcript on the Microsoft Investor Relations website.
本次电话会议将进行网络直播并全程录音。如果您提出问题，该问题将被纳入我们的实时转播、文字记录以及录音资料的后续使用中。您可通过微软投资者关系网站回放会议录音并查阅文字记录。

During this call, we will be making forward-looking statements, which are predictions, projections or other statements about future events. These statements are based on current expectations and assumptions that are subject to risks and uncertainties. Actual results could materially differ because of factors discussed in today's earnings press release, in the comments made during this conference call, and in the Risk Factors section of our Form 10-K, Forms 10-Q and other reports and filings with the Securities and Exchange Commission. We do not undertake any duty to update any forward-looking statement.
本次电话会议中，我们将发表前瞻性声明，即对未来的预测、展望或其他陈述。这些声明基于当前的预期和假设，而这些预期和假设本身受到各类风险和不确定性的制约。由于今日 earnings 新闻稿中所讨论的因素、本次电话会议期间的发言内容，以及我们向美国证券交易委员会（Securities and Exchange Commission）提交的 10-K 表格、10-Q 表格及其他报告和文件中的“风险因素”（Risk Factors）部分所列因素的影响，实际结果可能与前述前瞻性声明存在重大差异。我们不承担更新任何前瞻性声明的义务。

And with that, I'll turn the call over to Satya.
就此，我将会议交由萨提亚主持。

Satya Nadella
萨提亚·纳德拉
Chairman & CEO
董事长兼首席执行官

Thank you very much, Jonathan. This quarter, the Microsoft Cloud surpassed $50 billion in revenue for the first time, up 26% year-over-year, reflecting the strength of our platform and accelerating demand. We are in the beginning phases of AI diffusion and its broad GDP impact. Our TAM will grow substantially across every layer of the tech stack as this diffusion accelerates and spreads. In fact, even in this early innings, we have built an AI business that is larger than some of our biggest franchises that took decades to build. Today, I'll focus my remarks across the 3 layers of our stack, cloud and token factory, agent platform and high-value agentic experiences.
非常感谢，乔纳森。本季度，微软云营收首次突破 500 亿美元，同比增长 26%，彰显了我们平台的强大实力以及市场需求的加速增长。目前，人工智能正处于普及的初期阶段，其对全球 GDP 的广泛影响才刚刚开始显现。随着 AI 普及进程不断加快并持续扩展，我们在技术栈每一层的总可寻址市场（TAM）都将大幅增长。事实上，即便尚处于早期阶段，我们已构建起一个规模超过部分耗时数十年才打造完成的最核心业务线的 AI 业务。今天，我将围绕我们技术栈的三层展开阐述：云与“令牌工厂”（Token Factory）、智能体平台（Agent Platform），以及高价值的智能体驱动型体验（High-Value Agentic Experiences）。

When it comes to our cloud and token factory, the key to long-term competitiveness is shaping our infrastructure to support new high-scale workloads. We are building this infrastructure out for the heterogeneous and distributed nature of these workloads, ensuring the right fit with the geographic and segment specific needs for all customers, including the long tail. The key metric we're optimizing for is tokens per watt per dollar, which comes down to increasing utilization and decreasing TCO using silicon systems and software. A good example of this is the 50% increase in throughput we were able to achieve in one of our highest volume workloads, OpenAI inferencing, powering our Copilots.
在云服务与令牌工厂方面，长期竞争力的关键在于构建能够支持新型大规模工作负载的基础设施。我们正针对这些工作负载所具有的异构性与分布式特性来打造基础设施，确保其精准匹配所有客户（包括长尾客户）在地理区域和细分市场层面的具体需求。我们优化的核心指标是“每瓦特每美元所产生的令牌数”，其实现路径在于通过硅基系统与软件提升资源利用率、降低总体拥有成本（TCO）。一个典型例证是：我们在最高流量的工作负载之一——为 Copilot 提供支持的 OpenAI 推理任务中，成功将吞吐量提升了 50%。

And another example was the unlocking of new capabilities and efficiencies for our Fairwater data centers. In this instance, we connected both Atlanta and Wisconsin site through an AI WAN to build a first of its kind AI super factory. Fairwater's 2-storey design and liquid cooling allow us to run higher GPU densities and thereby improve both performance and latencies for high-scale training. All up, we added nearly 1 gigawatt of total capacity this quarter alone.
另一个例子是 Fairwater 数据中心新能力与效率的释放。在此案例中，我们通过 AI 广域网（AI WAN）将亚特兰大与威斯康星州两地站点互联，建成了业界首个 AI 超级工厂。Fairwater 采用两层式建筑结构并配备液冷系统，使其能够部署更高密度的 GPU，从而显著提升大规模训练任务的性能表现并降低延迟。仅本季度，我们就新增了近 1 吉瓦（GW）的总容量。

At the silicon layer, we have NVIDIA and AMD and our own Maia chips, delivering the best all up fleet performance, cost and supply across multiple generations of hardware. Earlier this week, we brought online our Maia 200 accelerator. Maia 200 delivers 10-plus petaFLOPS at FP4 precision with over 30% improved TCO compared to the latest generation hardware in our fleet. We will be scaling this starting with inferencing and synthetic data gen for our Superintelligence Team as well as doing inferencing for Copilot and Foundry.
在芯片层面，我们拥有英伟达（NVIDIA）、超威半导体（AMD）以及自研的 Maia 芯片，从而在多代硬件中全面实现最佳的整体机群性能、成本效益与供应能力。本周早些时候，我们已正式上线 Maia 200 加速器。Maia 200 在 FP4 精度下可提供超过 10 petaFLOPS 的算力，相较当前机群中最新型号的硬件，总体拥有成本（TCO）降低逾 30%。我们将率先在“超级智能团队”（Superintelligence Team）的推理任务和合成数据生成任务中规模化部署该芯片，同时也将用于 Copilot 及 Foundry 产品的推理任务。

And given AI workloads are not just about AI accelerators, but also consume large amounts of compute, we are pleased with the progress we are making on the CPU side as well. Cobalt 200 is another big leap forward, delivering over 50% higher performance compared to our first custom build processor for cloud-native workloads. Sovereignty is increasingly top of mind for customers, and we are expanding our solutions and global footprint to match. We announced DC investments in 7 countries this quarter alone, supporting local data residency needs. And we offer the most comprehensive set of sovereignty solutions across public, private and national partner cloud, so customers can choose the right approach for each workload with the local control they require.
鉴于 AI 工作负载不仅依赖 AI 加速器，还需消耗大量计算资源，我们在 CPU 领域取得的进展同样令人欣喜。Cobalt 200 是又一重大突破，其性能相较我们首款面向云原生工作负载的自研处理器提升了逾 50%。数据主权正日益成为客户关注的首要议题，为此，我们正持续拓展相关解决方案及全球布局以满足客户需求。仅本季度，我们就宣布了在 7 个国家投资建设数据中心，以支持本地数据驻留需求。此外，我们在公有云、私有云及国家合作伙伴云三大领域，提供了业界最全面的数据主权解决方案，使客户能够根据每类工作负载的具体要求，灵活选择最适合的方式，并实现所需的本地化管控。

Next, I want to talk about the agent platform. Like in every platform shift, all software is being rewritten. A new app platform is being born. You can think of agents as the new apps and to build, deploy and manage agents, customers will need a model catalog, tuning services, harness for orchestration, services for context engineering, AI safety, management, observability and security. It starts with having broad model choice. Our customers expect to use multiple models as part of any workload that they can fine tune and optimize based on cost, latency and performance requirements. And we offer the broadest selection of models of any hyperscaler. This quarter, we added support for GPT-5.2 as well as Claude 4.5. Already over 1,500 customers have used both Anthropic and OpenAI models on Foundry. We are seeing increasing demand for region-specific models, including Mistral and Cohere as more customers look for sovereign AI choices, and we continue to invest in our first-party models, which are optimized to address the highest value customer scenarios such as productivity, coding and security.
接下来，我想谈谈智能体平台。正如每一次平台变革一样，所有软件都在被重新编写，一个全新的应用平台正在诞生。您可以将智能体视作新一代应用程序；而要构建、部署和管理智能体，客户需要模型目录、调优服务、编排框架、上下文工程服务、AI 安全服务、管理服务、可观测性服务及安全服务。这一切始于提供广泛的模型选择。我们的客户期望在任何工作负载中都能灵活选用多种模型，并根据成本、延迟和性能要求进行微调与优化。我们是所有超大规模云服务商中提供模型种类最全的厂商。本季度，我们新增了对 GPT-5.2 及 Claude 4.5 的支持。目前已有超过 1500 家客户在 Foundry 平台上同时使用 Anthropic 与 OpenAI 的模型。随着越来越多客户寻求具备主权属性的人工智能解决方案，市场对区域性专属模型（如 Mistral 与 Cohere）的需求持续攀升。与此同时，我们持续加大自有模型的研发投入——这些第一方模型专为高价值客户场景（例如办公提效、编程开发与网络安全）进行了深度优化。

As part of Foundry, we also give customers the ability to customize and fine-tune models. Increasingly, customers want to be able to capture the tacit knowledge they possess inside of model weights as their core IP. This is probably the most important sovereign consideration for firms as AI diffuses more broadly across our GDP and every firm needs to protect their enterprise value. For agents to be effective, they need to be grounded in enterprise data and knowledge, that means connecting their agents to systems of record and operational data, analytical data as well as semi-structured and unstructured productivity and communications data. And this is what we are doing with our unified IQ layer, spanning Fabric, Foundry and data powering Microsoft 365.
作为“铸造厂”（Foundry）的一部分，我们还为客户提供定制和微调模型的能力。越来越多的客户希望将自身所掌握的隐性知识嵌入模型权重中，将其作为核心知识产权加以保护。随着人工智能更广泛地渗透至整个 GDP 领域，这可能是企业最为核心的主权考量——每一家企业都需要保护自身的商业价值。要使智能体（agents）真正有效，就必须以企业数据与知识为根基，这意味着需将智能体连接至权威系统（systems of record）、运营数据、分析数据，以及半结构化和非结构化的生产力与通信数据。这正是我们通过统一的 IQ 层所实现的目标，该层贯通 Fabric、Foundry 以及驱动 Microsoft 365 的数据平台。

（编注：核心数据隐私的问题，记得亚马逊好像也提过）

In the world of context engineering, Foundry knowledge and Fabric are gaining momentum. Foundry knowledge delivers better context with automated source routing an advanced agentic retrieval while respecting user permissions. And Fabric brings together end-to-end operational real-time and analytical data. 2 years since it became broadly available, Fabric's annual revenue run rate is now over $2 billion with over 31,000 customers, and it continues to be the fastest-growing analytics platform on the market with revenue up 60% year-over-year. All of the number of customers spending $1 million plus per quarter on Foundry grew nearly 80%, driven by strong growth in every industry. And over 250 customers are on track to process over 1 trillion tokens on Foundry this year. There are many great examples of customers using all of this capability on Foundry to build their own agentic systems. Alaska Airlines is creating natural language flight search. BMW is speeding up design cycles, Land O'Lakes is enabling precision farming for co-op members, and SymphonyAI is addressing bottlenecks in the CPG industry. And of course, Foundry remains a powerful on-ramp for the entire cloud. The vast majority of Foundry customers use additional Azure solutions like developer services, app services, databases as they scale.
在上下文工程领域，Foundry 知识库与 Fabric 正在加速发展。Foundry 知识库通过自动化源路由与先进的智能体检索技术，在严格遵守用户权限的前提下，提供更优质的上下文支持；而 Fabric 则实现了端到端的运营、实时及分析数据融合。自全面上市两年来，Fabric 年度经常性收入（ARR）已突破 20 亿美元，客户数量超过 31,000 家，持续成为市场上增速最快的分析平台，年同比收入增长达 60%。季度支出超 100 万美元的 Foundry 客户数量增长近 80%，各行业均展现出强劲增长势头；此外，已有逾 250 家客户预计今年将在 Foundry 上处理超 1 万亿个 token。众多客户正充分利用 Foundry 的全部能力，构建自有智能体系统，案例丰富：阿拉斯加航空正在打造基于自然语言的航班搜索功能；宝马正加快产品设计周期；Land O’Lakes（兰德奥莱克）正为其合作社成员赋能精准农业；SymphonyAI（交响人工智能）则致力于解决日用消费品（CPG）行业的瓶颈问题。当然，Foundry 依然是通往整个云生态的强大入口。 绝大多数代工厂（Foundry）客户在业务扩展过程中，还会采用其他 Azure 解决方案，例如开发者服务、应用服务和数据库等。

Beyond Fabric and Foundry, we are also addressing agent building by knowledge workers with Copilot Studio and Agent Builder. Over 80% of the Fortune 500 have active agents built using these low-code/no-code tools. As agents proliferate, every customer will need new ways to deploy, manage and protect them. We believe this creates a major new category and significant growth opportunity for us. This quarter, we introduced Agent 365, which makes it easy for organizations to extend their existing governance, identity, security and management to agents. That means the same controls they already use across Microsoft 365 and Azure, now extend to agents they build and deploy on our cloud or any other cloud. And partners like Adobe, Databricks, Genspark, Glean, NVIDIA, SAP, ServiceNow and Workday are already integrating Agent 365. We are the first provider to offer this type of agent control plane across clouds.
除 Fabric 和 Foundry 外，我们还通过 Copilot Studio 和 Agent Builder 支持知识型员工构建智能体（agent）。《财富》500 强企业中，超过 80% 已使用这些低代码/无代码工具构建并部署了活跃的智能体。随着智能体数量激增，所有客户都将需要全新的方式来部署、管理和保护这些智能体。我们认为，这将催生一个全新的重要产品类别，并为我们带来显著的增长机遇。本季度，我们正式推出 Agent 365，使企业能够轻松将其现有的治理、身份认证、安全及管理能力延伸至智能体层面。这意味着客户当前在 Microsoft 365 和 Azure 上所采用的全部管控策略，如今均可无缝覆盖其在我们的云平台或任何其他云平台上构建与部署的智能体。目前，Adobe、Databricks、Genspark、Glean、NVIDIA、SAP、ServiceNow 和 Workday 等合作伙伴已开始集成 Agent 365。我们是首家提供跨云智能体管控平面（agent control plane）的厂商。

Now let's turn to the high-value agentic experiences we are building. AI experiences are intent-driven and are beginning to work at task scope. We are entering an age of macro delegation and micro steering across domains. Intelligence using multiple models is built into multiple form factors. You see this in chat, in new agent inbox, apps, coworkers, scaffoldings, agent workflows embedded in applications and IDs that are used every day or even in our command line with file system access and skills. That's the approach we are taking with our first-party family of copilot spanning key domains.
现在，让我们转向我们正在构建的高价值智能体体验。AI 体验以用户意图为核心驱动，目前已开始在任务层面发挥作用。我们正步入一个“宏观委托、微观引导”的时代，这种模式横跨各个领域。基于多个模型的智能能力已融入多种形态的产品中：从聊天界面、全新的智能体收件箱，到各类应用、同事协作工具、脚手架式辅助系统、嵌入应用程序中的智能体工作流，乃至日常使用的身份认证系统（IDs），甚至包括支持文件系统访问和各类技能的命令行工具。这正是我们面向关键领域的第一方 Copilot 产品家族所采用的发展路径。

In consumer, for example, Copilot experiences span chat, news, feed, search, creation, browsing, shopping and integrations into the operating system, and it's gaining momentum. Daily users of our Copilot app increased nearly 3x year-over-year. And with Copilot checkout, we have partnered with PayPal, Shopify and Stripe, so customers can make purchases directly within the app. With Microsoft 365 Copilot, we are focused on organization-wide productivity.
以消费者领域为例，Copilot 体验已覆盖聊天、新闻、信息流、搜索、内容创作、网页浏览、购物以及操作系统级集成等多个场景，并持续加速普及。我们的 Copilot 应用日活跃用户数同比增长近 3 倍。此外，借助 Copilot 结账功能，我们已与 PayPal、Shopify 及 Stripe 达成合作，使用户可直接在应用内完成购买。而在 Microsoft 365 Copilot 方面，我们的重点则聚焦于提升组织整体的工作效率。

Work IQ takes the data underneath Microsoft 365 and creates the most valuable stateful agent for every organization. It delivers powerful reasoning capabilities over people, their roles, their artifacts, their communications and their history and memory all within an organization security boundary. Microsoft 365 Copilot's accuracy and latency powered by Work IQ is unmatched, delivering faster and more accurate work grounded results than competition, and we have seen our biggest quarter-over-quarter improvement in response quality to date. This has driven record usage intensity with average number of conversations per user doubling year-over-year. Microsoft 365 Copilot also is becoming true daily habit with daily active users increasing 10x year-over-year.
Work IQ 深度挖掘 Microsoft 365 底层数据，为每一家组织打造最具价值的有状态智能体（stateful agent）。它在组织安全边界内，对人员、其岗位职责、产出文档、沟通记录以及历史与记忆等要素，提供强大的推理能力。依托 Work IQ 技术赋能，Microsoft 365 Copilot 的准确率与响应延迟表现业界领先，所生成的工作成果比竞争对手更快速、更精准；截至目前，我们在响应质量方面的季度环比提升幅度创历史新高。这一突破显著推动了用户活跃度：人均对话次数同比增长达两倍。同时，Microsoft 365 Copilot 正日益成为用户的日常必备工具，日活跃用户数同比增长达十倍。

We're also seeing strong momentum with researcher agent, which supports both OpenAI and Claude, as well as agent mode in Excel, PowerPoint and Word. All up, it was a record quarter for Microsoft 365 Copilot seat adds, up over 160% year-over-year. We saw accelerating seat growth quarter-over-quarter and now have 15 million paid Microsoft 365 Copilot seats and multiples more enterprise chat users.
我们还观察到研究型智能体（researcher agent）展现出强劲发展势头——该智能体同时支持 OpenAI 与 Claude 模型；此外，Excel、PowerPoint 和 Word 中的智能体模式（agent mode）也广受好评。综合来看，本季度 Microsoft 365 Copilot 的席位新增量再创纪录，同比增长逾 160%；席位数量的季度环比增速持续加快，目前已拥有 1500 万付费席位，并服务数倍于此规模的企业级聊天用户。

And we are seeing larger commercial deployments. The number of customers with over 35,000 seats tripled year-over-year. Fiserv, ING, NASA, University of Kentucky, University of Manchester, U.S. Department of Interior and Westpac, all purchased over 35,000 seats. Publicis alone purchased over 95,000 seats for nearly all its employees. We are also taking share in Dynamics 365 with built-in agents across the entire suite. A great example of this is how Visa is turning customer conversations data into knowledge articles with our customer knowledge management agent and dynamics. And how Sandvik is using our sales qualification agent to automate lead qualification across tens and thousands of potential customers.
我们正看到更大规模的商业部署。拥有超过 35,000 个席位的客户数量同比增长了三倍。Fiserv、荷兰国际集团（ING）、美国国家航空航天局（NASA）、肯塔基大学、曼彻斯特大学、美国内政部以及西太平洋银行（Westpac）均采购了超过 35,000 个席位。其中，阳狮集团（Publicis）一家就为其几乎全部员工采购了逾 95,000 个席位。同时，我们正在凭借内置于整个 Dynamics 365 套件中的智能代理，持续扩大市场份额。一个典型范例是：Visa 正借助我们的客户知识管理智能代理与 Dynamics，将客户对话数据转化为知识文章；而山特维克（Sandvik）则利用我们的销售资质评估智能代理，在数以万计的潜在客户中实现线索资质评估的自动化。

In coding, we are seeing strong growth across all paid GitHub Copilot. Copilot Pro Plus subs for individual devs increased 77% quarter-over-quarter, and all up now, we have 4.7 million paid Copilot subscribers, up 75% year-over-year. Siemens, for example, is going all in on GitHub adopting the full platform to increase developer productivity after a successful Copilot rollout to 30,000-plus developers. GitHub Agent HQ is the organizing layer for all coding agents like Anthropic, OpenAI, Google, Cognition and xAI in the context of customers GitHub repos. With Copilot CLI and VS Code, we offer developers the full spectrum of form factors and models they need for AI-first coding workflows.
在编程领域，我们看到所有付费版 GitHub Copilot 均呈现强劲增长。面向个人开发者的 Copilot Pro Plus 订阅用户数量环比增长 77%，目前付费 Copilot 订阅用户总数已达 470 万，同比增长 75%。例如，西门子公司已全面采用 GitHub 平台，以提升开发者生产力——此前，Copilot 已成功部署至其超过 3 万名开发者团队。GitHub Agent HQ 是面向客户 GitHub 代码仓库的统一编排层，可整合 Anthropic、OpenAI、Google、Cognition 和 xAI 等各类编程智能体。借助 Copilot CLI 和 VS Code，我们为开发者提供覆盖全形态终端与全模型谱系的 AI 优先编程工作流支持。

And when you add Work IQ as a skill or an MCP to our developer workflow, it's a game changer, surfacing more context like e-mails, meetings, docs, projects, messages and more. You can simply ask the agent to plan and execute changes to your code base based on an update to a spec-in Sharepoint or using the transcript of your last engineering and design meeting in Teams.
当您将 Work IQ 作为一项技能或 MCP（模型控制协议）集成至我们的开发者工作流中时，这将带来颠覆性变革——它能自动呈现更多上下文信息，例如电子邮件、会议记录、文档、项目信息、消息等。您只需向智能体发出指令，即可基于 SharePoint 中更新的需求文档，或 Teams 中最近一次工程与设计会议的会议纪要，自动规划并执行代码库的相应变更。

And we're going beyond that with GitHub Copilot STK. Developers can now embed the same run time behind Copilot CLI, multi-model, multistep planning tools, MCP integration, Ops streaming directly into their applications. In security, we added a dozen new and updated security Copilot agents across Defender, Entra, Intune, and Purview. For example, Icertis, the SOC team used Security Copilot agent to reduce manual triage time by 75%, which is a real game changer in an industry facing a severe talent shortage.
我们还通过 GitHub Copilot STK 进一步拓展了这一能力。开发者如今可将 Copilot CLI 背后的同一运行时——支持多模型、多步骤规划的工具、MCP 集成及运维流式处理——直接嵌入其应用程序中。在安全领域，我们已在 Defender、Entra、Intune 和 Purview 中新增并更新了十余种安全 Copilot 智能体。例如，Icertis 公司的 SOC 团队借助安全 Copilot 智能体，将人工初步分类（triage）耗时减少了 75%，这在当前面临严重人才短缺的安全行业堪称真正的变革性突破。

To make it easier for security teams to onboard, we are rolling out security copilot to all our E5 customers and our security solutions are also becoming essential to manage organization's AI deployments. 24 billion Copilot interactions were audited by Purview this quarter, up 9x year-over-year.
为便于安全团队快速上手，我们正向所有 E5 客户全面推送安全 Copilot；同时，我们的安全解决方案也日益成为企业管理和规范 AI 部署不可或缺的一环。本季度，Purview 审计的 Copilot 交互次数达 240 亿次，同比增长 9 倍。

Finally, I want to talk about 2 additional high-impact agenetic experiences. First, in health care, Dragon Copilot is the leader in its category, helping over 100,000 medical providers automate their workflows. Mount Sinai Health is now moving to a system-wide Dragon Copilot deployment for providers after a successful trial with its primary care physicians. All up, we helped document 21 million patient encounters this quarter, up 3x year-over-year.
最后，我想谈谈另外两项具有重大影响的智能体应用体验。首先，在医疗健康领域，“龙”助手（Dragon Copilot）是其细分领域的领导者，已帮助超过 10 万名医疗从业者实现工作流程自动化。西奈山医疗系统（Mount Sinai Health）在对其全科医生成功开展试点后，现已启动面向全体医护人员的“龙”助手系统级部署。本季度，我们共协助记录了 2,100 万次患者就诊事件，同比增长达 3 倍。

And second, when it comes to science and engineering, companies like Unilever in consumer goods and Synopsys in EDA are using Microsoft Discovery to orchestrate specialized agents for R&D end-to-end. They're able to reason over scientific literature and internal knowledge, formulate hypotheses, spin up simulations and continuously iterate to drive new discoveries.
其次，在科学研究与工程领域，消费品行业的联合利华（Unilever）和电子设计自动化（EDA）领域的新思科技（Synopsys）等企业正采用微软发现平台（Microsoft Discovery），端到端编排专业智能体以支持研发工作。这些企业能够基于科学文献及内部知识进行推理、提出假设、启动仿真，并持续迭代优化，从而推动新发现不断涌现。

Beyond AI, we continue to invest in all our core franchises and meet the needs of our customers and partners, and we are seeing strong progress. For example, when it comes to cloud migrations, our new SQL server has over 2x the IaaS adoption of the previous version. In Security, we now have 1.6 million security customers, including over 1 million who use 4 or more of our workloads. Windows reached a big milestone, 1 billion Windows 11 users up over 45% year-over-year. And we had share gains this quarter across Windows, Edge and Bing, double-digit member growth in LinkedIn with 30% growth in paid video ads.
除人工智能外，我们持续投资于所有核心业务，并积极满足客户与合作伙伴的需求，目前已取得显著进展。例如，在云迁移方面，我们全新推出的 SQL Server 在基础设施即服务（IaaS）领域的采用率较上一版本提升逾两倍；在安全领域，我们的安全客户总数已达 160 万，其中超 100 万客户同时使用我们四项或以上的安全工作负载；Windows 亦迎来重要里程碑——Windows 11 用户数突破 10 亿，同比增长逾 45%；本季度，我们在 Windows、Edge 及 Bing 的市场份额均实现增长；LinkedIn 会员数实现两位数增长，付费视频广告收入同比增长 30%。

And in gaming, we are committed to delivering great games across Xbox, PC, Cloud and every other device, and we saw record PC players in paid streaming hours on Xbox.
在游戏领域，我们致力于为 Xbox、PC、云平台及所有其他设备提供卓越的游戏体验；本季度，Xbox 平台付费流媒体游戏时长所覆盖的 PC 玩家数量创下历史新高。

In closing, we feel very good about how we are delivering for customers today and building the full stack to capture the opportunity ahead.
总而言之，我们对当前为客户提供的价值深感满意，同时也正全力构建端到端技术栈，以充分把握未来机遇。

With that, let me turn it over to Amy to walk through our financial results and outlook, and I look forward to rejoining for your questions.
接下来，请 Amy 为大家详细解读我们的财务业绩与展望。随后我将再次加入，回答各位的提问。

Amy Hood
艾米·胡德
Executive VP & CFO
执行副总裁兼首席财务官（CFO）

Thank you, Satya, and good afternoon, everyone. With growing demand for our offerings and focused execution by our sales teams, we again exceeded expectations across revenue, operating income and earnings per share, while investing to fuel long-term growth. This quarter, revenue was $81.3 billion, up 17% and 15% in constant currency. Gross margin dollars increased 16% and 14% in constant currency, while operating income increased 21% and 19% in constant currency.
谢谢萨提亚，大家下午好。得益于我们各项产品需求持续增长，以及销售团队专注高效的执行，我们在本季度的营收、营业利润和每股收益方面再次超出预期，同时我们也在加大投入，以推动长期增长。本季度营收达 813 亿美元，同比增长 17%，按固定汇率计算增长 15%。毛利额同比增长 16%，按固定汇率计算增长 14%；营业利润同比增长 21%，按固定汇率计算增长 19%。

Earnings per share was $4.14, an increase of 24% and 21% in constant currency when adjusted for the impact from our investment in OpenAI. And FX increased reported results slightly less than expected, particularly in Intelligent Cloud revenue. Company gross margin percentage was 68%, down slightly year-over-year, primarily driven by continued investments in AI infrastructure and growing AI product usage that was partially offset by ongoing efficiency gains, particularly in Azure and M365 Commercial Cloud as well as sales mix shift to higher-margin businesses.
每股收益为 4.14 美元，若剔除对 OpenAI 投资的影响进行调整，则同比增长 24%，按固定汇率计算增长 21%。汇率变动对报告业绩的正面影响略低于预期，尤其体现在智能云业务营收方面。公司整体毛利率为 68%，同比略有下降，主要原因在于持续加大对人工智能基础设施的投资，以及人工智能相关产品使用量不断攀升；尽管 Azure 与 Microsoft 365 商业云等业务持续提升运营效率，并且产品销售结构进一步向高利润率业务倾斜，部分抵消了上述影响，但整体毛利率仍小幅承压。

Operating expenses increased 5% and 4% in constant currency, driven by R&D investments in compute capacity and AI talent as well as impairment charges in our gaming business. Operating margins increased year-over-year to 47%, ahead of expectations. As a reminder, we still account for investment in OpenAI under the equity method. And as a result of OpenAI's recapitalization, we now record gains or losses based on our share of the change in their net assets on their balance sheet as opposed to our share of their operating profit or losses from their income statement. Therefore, we recorded a gain which drove other income and expense to $10 billion in our GAAP results.
运营费用以固定汇率计算分别增长了 5%和 4%，主要受计算能力及人工智能人才研发投入，以及游戏业务减值损失的影响。营业利润率同比上升至 47%，超出预期。需要提醒的是，我们目前仍按权益法核算对 OpenAI 的投资。由于 OpenAI 进行了资本重组，我们现根据其资产负债表上净资产变动中归属于我们的份额，而非其利润表中经营利润或亏损中归属于我们的份额，来确认相关利得或损失。因此，我们在美国通用会计准则（GAAP）财务报表中确认了一笔利得，使得其他收入与费用项目达到 100 亿美元。

When adjusted for the OpenAI impact, other income and expense was slightly negative and lower than expected driven by net losses on investments. Capital expenditures were $37.5 billion, and this quarter, roughly 2/3 of our CapEx was on short-lived assets, primarily GPUs and CPUs. Our customer demand continues to exceed our supply. Therefore, we must balance the need to have our incoming supply better meet growing Azure demand with expanding first-party AI usage across services like M365 Copilot and GitHub Copilot, increasing allocations to R&D teams to accelerate product innovation and continued replacement of end-of-life server and networking equipment.
剔除 OpenAI 相关影响后，其他收入与支出略微为负，且低于预期，主要受投资净亏损拖累。资本支出为 375 亿美元，本季度约三分之二的资本支出用于短期资产，主要包括 GPU 和 CPU。客户需求持续超过供应能力。因此，我们必须在以下几方面取得平衡：一方面，需提升 incoming 供应能力，以更好满足 Azure 日益增长的需求；另一方面，要扩大第一方 AI 应用（如 Microsoft 365 Copilot 和 GitHub Copilot）的资源分配，增加对研发团队的投入以加速产品创新，并持续推进服务器及网络设备的更新换代（替换已到生命周期终点的设备）。

The remaining spend was for long-lived assets that will support monetization for the next 15 years and beyond. This quarter, total finance leases were $6.7 billion, and were primarily for large data center sites. And cash paid for PP&E was $29.9 billion. Cash flow from operations was $35.8 billion, up 60%, driven by strong Cloud billings and collections. And free cash flow was $5.9 billion and decreased sequentially, reflecting the higher cash capital expenditures from a lower mix of finance leases. And finally, we returned $12.7 billion to shareholders through dividend and share repurchases, an increase of 32% year-over-year.
剩余支出用于购置长期资产，这些资产将支持未来 15 年及更长时间的货币化运营。本季度，融资租赁总额为 67 亿美元，主要投向大型数据中心园区；购建固定资产、无形资产和其他长期资产所支付的现金为 299 亿美元。经营活动产生的现金流量为 358 亿美元，同比增长 60%，主要得益于云业务强劲的账单开立与回款表现。自由现金流为 59 亿美元，环比下降，反映出当期现金资本性支出增加，同时融资性租赁占比有所降低。最后，公司通过派发股息和股票回购方式向股东返还资金 127 亿美元，同比增长 32%。

Now to our commercial results. Commercial bookings increased 230% and 228% in constant currency, driven by the previously announced large Azure commitment from OpenAI that reflects multiyear demand needs as well as the previously announced Anthropic commitment from November and healthy growth across our core annuity sales motions.
接下来是商业业务业绩。按固定汇率计算，商业预订额增长 230%和 228%，主要受此前宣布的 OpenAI 对 Azure 的大额多年期承诺驱动——该承诺反映了其多年期需求；此外，也受益于去年 11 月宣布的 Anthropic 相关承诺，以及公司核心年金型销售模式的稳健增长。

Commercial remaining performance obligation, which continues to be reported net of reserves increased to $625 billion, and was up 110% year-over-year with a weighted average duration of approximately 2.5 years. Roughly 25% will be recognized in revenue in the next 12 months, up 39% year-over-year. The remaining portion recognized beyond the next 12 months increased 156%. Approximately 45% of our commercial RPO balance is from OpenAI. The significant remaining balance grew 28% and reflects ongoing broad customer demand across the portfolio.
商业剩余履约义务（Commercial Remaining Performance Obligation，RPO）持续以扣除准备金后的净额列示，目前已增至 6250 亿美元，同比增长 110%，加权平均履约周期约为 2.5 年。其中约 25%预计将在未来 12 个月内确认为收入，较去年同期增长 39%；剩余部分（即 12 个月之后确认的收入）同比增长 156%。我们商业 RPO 余额中约 45%来自 OpenAI。这一显著的剩余余额同比增长 28%，反映出客户对整个投资组合持续强劲的广泛需求。

Microsoft Cloud revenue was $51.5 billion and grew 26% and 24% in constant currency. Microsoft Cloud gross margin percentage was slightly better than expected at 67%, and down year-over-year due to continued investments in AI that were partially offset by ongoing efficiency gains noted earlier.
微软云（Microsoft Cloud）营收达 515 亿美元，按固定汇率计算同比增长 26%和 24%。微软云毛利率为 67%，略高于预期，但同比下降，主要由于持续加大人工智能领域的投入；此前提到的运营效率提升在一定程度上抵消了这部分投入的影响。

Now to our segment results. Revenue from Productivity and Business Processes was $34.1 billion and grew 16% and 14% in constant currency. M365 Commercial cloud revenue increased 17% and 14% in constant currency with consistent execution in the core business and increasing contribution from strong copilot results. ARPU growth was again led by E5 and M365 Copilot, and paid M365 commercial seats grew 6% year-over-year to over 450 million with installed base expansion across all customer segments, though primarily in our small and medium business and frontline worker offerings.
接下来是各业务部门的业绩情况。生产力与商业流程部门的营收为 341 亿美元，按固定汇率计算同比增长 16%，环比增长 14%。M365 商业云营收按固定汇率计算同比增长 17%，环比增长 14%，核心业务持续稳健执行，同时 Copilot 相关成果表现强劲，贡献不断提升。每用户平均收入（ARPU）增长继续由 E5 版和 M365 Copilot 引领；付费 M365 商业用户席位同比增长 6%，总数突破 4.5 亿，安装基础在所有客户群体中均实现扩展，其中尤以中小企业及一线员工产品线增长最为显著。

M365 Commercial products revenue increased 13% and 10% in constant currency, ahead of expectations due to higher-than-expected Office 2024 transactional purchasing. M365 consumer cloud revenue increased 29% and 27% in constant currency, again driven by ARPU growth. M365 consumer subscriptions grew 6%. LinkedIn revenue increased 11% and 10% in constant currency driven by Marketing Solutions.
M365 商业产品营收按固定汇率计算同比增长 13%，环比增长 10%，超出预期，主要得益于 Office 2024 交易型采购量高于预期。M365 个人消费者云营收按固定汇率计算同比增长 29%，环比增长 27%，再次由 ARPU 增长驱动；M365 个人消费者订阅用户数增长 6%。领英（LinkedIn）营收按固定汇率计算同比增长 11%，环比增长 10%，主要由营销解决方案（Marketing Solutions）业务带动。

Dynamics 365 revenue increased 19% and 17% in constant currency with continued growth across all workloads. Segment gross margin dollars increased 17% and 15% in constant currency, and gross margin percentage increased, again driven by efficiency gains at M365 Commercial Cloud that were partially offset by continued investments in AI, including the impact of growing copilot usage.
Dynamics 365 营收同比增长 19%，按固定汇率计算增长 17%，所有工作负载均持续增长。该业务部门的毛利额同比增长 17%，按固定汇率计算增长 15%；毛利率同比提升，主要得益于 Microsoft 365 商业云（M365 Commercial Cloud）运营效率的提高，但部分被公司在人工智能（AI）领域的持续投入所抵消，其中包括 Copilot 使用量不断增长所带来的影响。

Operating expenses increased 6% and 5% in constant currency, and operating income increased 22% and 19% in constant currency. Operating margins increased year-over-year to 60%, driven by improved operating leverage as well as the higher gross margins noted earlier.
运营费用同比增长 6%，按固定汇率计算增长 5%；营业利润同比增长 22%，按固定汇率计算增长 19%。营业利润率同比提升至 60%，这主要得益于运营杠杆效应增强，以及前述更高的毛利率。

Next, the Intelligent Cloud segment. Revenue was $32.9 billion and grew 29% and 28% in constant currency. In Azure and Other Cloud services, revenue grew 39% and 38% in constant currency, slightly ahead of expectations with ongoing efficiency gains across our fungible fleet, enabling us to reallocate some capacity to Azure that was monetized in the quarter.
接下来是智能云（Intelligent Cloud）业务部门。该部门营收达 329 亿美元，同比增长 29%，按固定汇率计算增长 28%。其中，Azure 及其他云服务营收同比增长 39%，按固定汇率计算增长 38%，略高于预期；这得益于我们通用型服务器集群（fungible fleet）持续提升的运营效率，使我们得以将部分算力重新分配至 Azure，并在本季度实现货币化。

As mentioned earlier, we continue to see strong demand across workloads, customer segments and geographic regions, and demand continues to exceed available supply. In our on-premises server business, revenue increased 2% and 1% in constant currency, ahead of expectations, driven by demand for our hybrid solutions, including a benefit from the launch of SQL Server 2025, as well as higher transactional purchasing ahead of memory price increases. Segment gross margin dollars increased 20% and 19% in constant currency. Gross margin percentage decreased year-over-year, driven by continued investments in AI and sales mix shift to Azure, partially offset by efficiency gains in Azure.
如前所述，我们继续看到各类工作负载、客户群体及地理区域均呈现强劲需求，且需求持续超过现有供应能力。在本地服务器业务中，营收按固定汇率计算分别增长 2%和 1%，超出预期，这主要得益于客户对混合解决方案的强劲需求，包括 SQL Server 2025 发布带来的积极影响，以及内存价格上涨前交易型采购量的提升。该业务板块的毛利额按固定汇率计算分别增长 20%和 19%。毛利率百分比同比有所下降，主要原因是公司持续加大对人工智能（AI）领域的投入，以及销售结构向 Azure 倾斜；部分被 Azure 运营效率提升所抵消。

Operating expenses increased 3% and 2% in constant currency, and operating income grew 28% and 27% in constant currency. Operating margins were 42%, down slightly year-over-year as increased investments in AI were mostly offset by improved operating leverage.
运营费用按固定汇率计算分别增长 3%和 2%，营业利润按固定汇率计算分别增长 28%和 27%。营业利润率约为 42%，同比略有下降，主要由于 AI 领域投入增加，但大部分被运营杠杆效应提升所抵消。

Now to More Personal Computing. Revenue was $14.3 billion and declined 3%. Windows OEM and devices revenue increased 1%, and was relatively unchanged in constant currency. Windows OEM grew 5% with strong execution as well as a continued benefit from Windows 10 end of support. Results were ahead of expectations as inventory levels remained elevated with increased purchasing ahead of memory price increases.
接下来是“更加个性化的计算”业务板块。该板块营收为 143 亿美元，同比下降 3%。其中，Windows OEM（原始设备制造商）及设备业务营收增长 1%，以不变汇率计算则基本持平。Windows OEM 业务增长 5%，主要得益于出色的执行能力，以及 Windows 10 终止支持所带来的持续利好。由于内存价格上涨预期推动采购提前增加，渠道库存水平维持高位，实际业绩超出预期。

Search and news advertising revenue ex TAC increased 10% and 9% in constant currency, slightly below expectations, driven by some execution challenges. As expected, the sequential growth rate moderated as the benefit from third-party partnerships normalized.
搜索与新闻广告营收（扣除流量获取成本 TAC 后）增长 10%，以不变汇率计算增长 9%，略低于预期，主要受部分执行层面挑战影响。如预期所示，环比增速有所放缓，原因是第三方合作伙伴关系带来的增量收益趋于正常化。

And in Gaming. Revenue decreased 9% and 10% in constant currency. Xbox content and services revenue decreased 5% and 6% in constant currency, and was below expectations driven by first-party content with impact across the platform. Segment gross margin dollars increased 2% and 1% in constant currency, and gross margin percentage increased year-over-year, driven by sales mix shift to higher-margin businesses.
游戏业务方面，营收下降 9%，以不变汇率计算下降 10%。Xbox 内容与服务营收下降 5%，以不变汇率计算下降 6%，低于预期，主要受第一方游戏内容表现疲软影响，且该影响波及整个平台。本业务板块毛利额增长 2%，以不变汇率计算增长 1%；毛利率同比上升，主要得益于产品结构向更高毛利业务倾斜。

Operating expenses increased 6% and 5% in constant currency, driven by the impairment charges in our gaming business noted earlier, as well as R&D investments in compute capacity and AI talent. Operating income decreased 3% and 4% in constant currency, and operating margins were relatively unchanged year-over-year at 27% as higher operating expenses were mostly offset by higher gross margins.
运营费用以固定汇率计算分别增长了 6%和 5%，主要受前述游戏业务减值损失，以及在计算能力和人工智能人才方面的研发投入增加所驱动。以固定汇率计算，营业利润分别下降了 3%和 4%，营业利润率同比基本持平，为 27%，原因是更高的运营费用大部分被更高的毛利率所抵消。

Now moving to our Q3 outlook, which unless specifically noted otherwise, is on a U.S. dollar basis. Based on current rates, we expect FX to increase total revenue growth by 3 points. Within the segments, we expect FX to increase revenue growth by 4 points in Productivity and Business Processes, and 2 points in Intelligent Cloud and More Personal Computing. We expect FX to increase COGS and operating expense growth by 2 points. As a reminder, this impact is due to the exchange rates a year ago.
接下来是第三季度业绩展望（除非另有特别说明，否则所有数据均以美元计）。基于当前汇率，我们预计外汇因素将使总收入增长率提升 3 个百分点。分业务板块来看，我们预计外汇因素将使“生产力与业务流程”板块的收入增长率提升 4 个百分点，“智能云”与“更多个人计算”板块的收入增长率各提升 2 个百分点。我们预计外汇因素将使销售成本及运营费用的增长率均提升 2 个百分点。需要提醒的是，该影响源于一年前的汇率水平。

Starting with the total company. We expect revenue of USD 80.65 billion to USD 81.75 billion or growth of 15% to 17%, with continued strong growth across our commercial businesses, partially offset by our consumer businesses. We expect COGS of USD 26.65 billion to USD 26.85 billion or growth of 22% to 23%, and operating expense of USD 17.8 billion to USD 17.9 billion or growth of 10% to 11%, driven by continued investment in R&D, AI compute capacity and talent against a low prior year comparable. Operating margins should be down slightly year-over-year.
首先来看公司整体业绩。我们预计营收为 806.5 亿至 817.5 亿美元，同比增长 15%至 17%，其中商用业务持续强劲增长，部分被消费类业务拖累。我们预计销售成本为 266.5 亿至 268.5 亿美元，同比增长 22%至 23%；运营支出为 178 亿至 179 亿美元，同比增长 10%至 11%，主要源于在研发、人工智能算力基础设施及人才方面的持续投入——这一增幅受上年同期基数较低影响。营业利润率预计将同比小幅下降。

Excluding any impact from our investments in OpenAI, other income and expense is expected to be roughly $700 million, driven by a fair market gain in our equity portfolio and interest income, partially offset by interest expense, which includes the interest payments related to data center finance leases. And we expect our adjusted Q3 effective tax rate to be approximately 19%.
若剔除对 OpenAI 投资的影响，其他收入与支出预计约为 7 亿美元，主要来自权益投资组合的公允价值收益及利息收入，部分被利息支出抵消；该利息支出包括数据中心融资租赁相关的利息付款。我们预计调整后的第三季度有效税率为约 19%。

Next, we expect capital expenditures to decrease on a sequential basis due to the normal variability from cloud infrastructure build-outs and the timing of delivery of finance leases. As we work to close the gap between demand and supply, we expect the mix of short-lived assets to remain similar to Q2.
接下来，由于云基础设施建设投入的正常波动以及融资租赁交付时间的影响，我们预计资本支出将环比下降。在努力弥合供需缺口的过程中，我们预计短期资产的构成将与第二财季保持相似。

Now our commercial business. In commercial bookings, we expect healthy growth in the core business on a growing expiry base when adjusted for the OpenAI contracts in the prior year. As a reminder, the significant OpenAI contracts signed in Q2 represents multiyear demand needs from them, which will result in some quarterly volatility in both bookings and RPO growth rates going forward. Microsoft Cloud gross margin percentage to be roughly 65%, down year-over-year, driven by continued investments in AI.
现在来看我们的商业业务。在商业预订方面，若剔除上一年度 OpenAI 合同的影响，我们预计核心业务将在不断扩大的到期基数基础上实现稳健增长。需要提醒的是，第二财季签署的重大 OpenAI 合同代表了其多年期的需求，这将导致未来几个季度的预订额及剩余履约义务（RPO）增长率出现一定的季度性波动。微软云毛利率预计约为 65%，同比下降，主要原因是持续加大对人工智能领域的投入。

Now to segment guidance. In Productivity and Business Processes, we expect revenue of USD 34.25 billion to USD 34.55 billion or growth of 14% to 15%. In M365 Commercial Cloud, we expect revenue growth to be between 13% and 14% in constant currency with continued stability and year-over-year growth rates on a large and expanding base. Accelerating Copilot momentum and ongoing E5 adoption will again drive ARPU growth. M365 commercial products revenue should decline in the low single digits, down sequentially, assuming office 2024 transactional purchasing trends normalize.
接下来是分部业绩指引。在“生产力与业务流程”板块，预计营收为 342.5 亿至 345.5 亿美元，同比增长 14%至 15%。在 M365 商业云板块，以不变汇率计，预计营收增长率为 13%至 14%，在庞大且持续扩张的基数上保持稳定，并实现同比正增长。Copilot 势头持续加速及 E5 版本持续采用，将再次推动每用户平均收入（ARPU）增长。假设 Office 2024 的交易型采购趋势回归常态，M365 商业产品营收预计将出现低个位数的环比下降。

As a reminder, M365 commercial products include components that can be variable due to in-period revenue recognition dynamics. M365 consumer cloud revenue growth should be in the mid- to high 20% range, driven by growth in ARPU as well as continued subscription volume. For LinkedIn, we expect revenue growth to be in the low double digits. And in Dynamics 365, we expect revenue growth to be in the high teens with continued growth across all workloads.
需要提醒的是，M365 商业产品包含若干组成部分，其收入可能因当期收入确认机制而产生波动。M365 个人云业务营收增长率预计处于 20%中高位区间，主要受 ARPU 提升及订阅用户数量持续增长驱动。LinkedIn 方面，预计营收增长率为低两位数；Dynamics 365 方面，预计营收增长率处于高 teens（即 17%–19%）区间，且所有工作负载均将持续增长。

For Intelligent Cloud, we expect revenue of USD 34.1 billion to USD 34.4 billion or growth of 27% to 29%. In Azure, we expect Q3 revenue growth to be between 37% and 38% in constant currency against a prior year comparable that included significantly accelerating growth rates in both Q3 and Q4. As mentioned earlier, demand continues to exceed supply, and we will need to continue to balance the incoming supply we can allocate here against other priorities.
智能云业务方面，我们预计营收为 341 亿至 344 亿美元，同比增长 27%至 29%。在 Azure 业务方面，按不变汇率计算，我们预计第三季度营收同比增长 37%至 38%，而去年同期的可比数据已包含第三、第四季度显著加速的增长率。如前所述，当前需求持续超过供应能力，因此我们需要继续权衡此处可分配的新增供应量与其他优先事项之间的关系。

As a reminder, there can be quarterly variability in year-on-year growth rates depending on the timing of capacity delivery and when it comes online as well as from in-period revenue recognition depending on the mix of contracts. In our on-premises server business, we expect revenue to decline in the low single digits as growth rates normalize following the launch of SQL Server 2025, though increased memory pricing could create additional volatility in transactional purchasing.
需要提醒的是，由于产能交付时间及上线时点存在差异，以及当期收入确认方式受合同结构影响，同比增速可能逐季度出现波动。在本地服务器业务方面，随着 SQL Server 2025 发布后增速逐步回归常态，我们预计营收将呈低个位数下降；不过内存价格上涨可能导致交易型采购出现额外的波动性。

In More Personal Computing, we expect revenue to be USD 12.3 billion to USD 12.8 billion. Windows OEM and devices revenue should decline in the low teens. Growth rates will be impacted as the benefit from Windows 10 end of support normalizes and as elevated inventory levels come down through the quarter. Therefore, Windows OEM revenue should decline roughly 10%.
在“更个性化计算”业务板块，我们预计营收为 123 亿至 128 亿美元。Windows OEM（原始设备制造商）及设备业务营收预计将同比下降一成多（低两位数）。受 Windows 10 终止支持带来的利好效应逐步消退，以及渠道库存水平在本季度持续回落的影响，Windows OEM 营收预计下降约 10%。

The range of potential outcomes remains wider than normal, in part due to the potential impact on the PC market from increased memory pricing. Search and News advertising ex TAC revenue growth should be in the high single digits. Even as we work to improve execution, we expect continued share gains across Bing and Edge with growth driven by volume, and we expect sequential growth moderation as the contribution from third-party partnerships continues to normalize.
潜在业绩结果的区间范围仍较正常情况更为宽泛，部分原因在于内存价格上涨可能对 PC 市场造成影响。搜索与新闻广告（不含流量获取成本 TAC）营收增速预计为高位个位数。尽管我们正持续提升运营执行效率，但预计必应（Bing）和 Edge 浏览器的市场份额仍将延续增长态势，主要由用户使用量带动；同时，随着第三方合作所带来的贡献进一步回归常态，环比增长势头预计将有所放缓。

And in Xbox content and services, we expect revenue to decline in the mid-single digits against a prior year comparable that benefited from strong content performance, partially offset by growth in Xbox Game Pass. And hardware revenue should decline year-over-year.
在 Xbox 内容与服务业务方面，由于上年同期基数受益于强劲的内容表现，本季度营收预计同比下降中个位数，其中 Xbox Game Pass 业务的增长将部分抵消该下滑。硬件营收则预计同比下滑。

Now some additional thoughts on the rest of the fiscal year and beyond. First, FX. Based on current rates, we expect FX to increase Q4 total revenue and COGS growth by less than 1 point with no impact to operating expense growth. Within the segments, we expect FX to increase revenue growth by roughly 1 point in Productivity and Business Processes and More Personal Computing, and less than 1 point in Intelligent Cloud.
接下来，就本财年剩余时间及以后的发展，再谈几点补充看法。首先，关于汇率（FX）影响：基于当前汇率水平，我们预计汇率因素将使第四财季的总收入和销售成本（COGS）增长率提升不到 1 个百分点，但对运营费用增长率不产生影响。分业务板块来看，我们预计汇率因素将使“生产力与商业流程”板块以及“更加个人化的计算”板块的收入增长率提升约 1 个百分点，而“智能云”板块的收入增长率则提升不到 1 个百分点。

With the strong work delivered in H1 to prioritize investment in key growth areas and the favorable impact from a higher mix of revenue in our Windows OEM and commercial on-prem businesses, we now expect FY '26 operating margins to be up slightly. We mentioned the potential impact on Windows OEM and on-premises server markets from increased memory pricing earlier. In addition, rising memory prices would impact capital expenditures, though the impact on Microsoft Cloud gross margins will build more gradually as these assets depreciate over 6 years.
得益于上半年在关键增长领域精准加大投资所取得的显著成效，叠加 Windows OEM 业务及商用本地部署业务收入占比提升所带来的积极影响，我们目前预计 2026 财年的运营利润率将略有上升。此前我们曾提及，内存价格上涨可能对 Windows OEM 市场及本地服务器市场造成一定影响。此外，内存价格上涨还将影响资本支出；不过，由于相关资产将在 6 年内逐步折旧，因此对微软云整体毛利率的影响将更为渐进。

In closing, we delivered strong top line growth in H1, and are investing across every layer of the stack to continue to deliver high-value solutions and tools to our customers. With that, let's go to Q&A, Jonathan.
最后总结一下：我们在上半年实现了强劲的营收增长，并正持续在技术栈的每一层加大投入，以继续为客户提供高价值的解决方案与工具。接下来，我们进入问答环节，有请乔纳森（Jonathan）。

Question-and-Answer Session
问答环节

Jonathan Neilson
乔纳森·尼尔森
Vice President of Investor Relations
投资者关系副总裁

Thanks, Amy. We'll now move over to Q&A. Out of respects for others on the call, we request that participants please only ask 1 question. Operator, can you please repeat your instructions?
谢谢，艾米。接下来我们将进入问答环节。为尊重电话会议中的其他参与者，我们恳请每位参会者仅提出一个问题。请问话务员能否再次说明相关操作指引？

Operator
操作员

[Operator Instructions] And our first question comes from the line of Keith Weiss with Morgan Stanley.
[话务员操作指引] 第一位提问者来自摩根士丹利的基思·韦斯。

Keith Weiss
基思·韦斯
Morgan Stanley, Research Division
摩根士丹利，研究部

I'm looking at Microsoft print where earnings is growing 24% year-on-year, which is a spectacular result. Great execution on your part, top line growing well, margins expanding. But I'm looking at after-hours trading and the stock is still down. And I think one of the core issues that is weighing on investors is CapEx is growing faster than we expected and maybe Azure is growing a little bit slower than we expected. And I think that fundamentally comes down to a concern on the ROI on this CapEx spend over time. So I was hoping you guys could help us fill in some of the blanks a little bit in terms of how should we think about capacity expansion and what that can yield in terms of Azure growth going forward. More to the point, how should we think about the ROI on this investment as it comes to fruition?
我正在查看微软的财报，其盈利同比增长 24%，这一成绩十分亮眼。贵公司在执行层面表现卓越，营收增长稳健，利润率持续扩大。但我在盘后交易中注意到，股价仍在下跌。我认为，令投资者担忧的核心问题之一在于：资本支出（CapEx）增速超出预期，而 Azure 业务的增长速度则略低于预期。归根结底，这本质上反映出市场对这笔资本支出长期投资回报率（ROI）的忧虑。因此，我希望各位能帮助我们进一步厘清一些关键问题：我们应如何理解当前的产能扩张策略？这种扩张未来将为 Azure 增长带来怎样的实际成效？更具体地说，随着这项投资逐步落地并产生回报，我们又该如何评估其投资回报率（ROI）？

Amy Hood
艾米·胡德
Executive VP & CFO
执行副总裁兼首席财务官（CFO）

Thanks, Keith. And let me start and Satya can add some broader comments, I'm sure. I think the first thing, I think you really asked a very direct correlation that I do think many investors are doing, which is between the CapEx spend and seeing an Azure revenue number. And we tried last quarter, and I think, again, this quarter to talk more specifically about all the places that the CapEx spend, especially the short-lived CapEx spend across CPU and GPU and where that will show up.
谢谢，基思。让我先来发言，萨提亚稍后肯定会补充一些更宏观的评论。首先，我想您提出了一个非常直接的关联问题，而我认为许多投资者也正在做同样的分析，即资本支出（CapEx）与 Azure 营收数据之间的关系。上一季度我们已尝试对此进行说明，而本季度我们再次努力更具体地阐述资本支出——尤其是 CPU 和 GPU 相关的短期资本支出——在哪些方面会产生影响。

Sometimes, I think it's probably better to think about the Azure guidance that we give as an allocated capacity guide about what we can deliver in Azure revenue. Because as we spend the capital and put GPUs specifically, it applies to CPUs, the GPUs more specifically, we're really making long-term decisions. And the first thing we're doing is solving for the increased usage in sales and the accelerating pace of M365 Copilot as well as GitHub Copilot, our first-party apps. Then we make sure we're investing in the long-term nature of R&D and product innovation. And much of the acceleration that I think you've seen from us and products over the past a bit is coming because we are allocating GPUs and capacity to many of the talented AI people we've been hiring over the past years.
有时，我认为将我们给出的 Azure 指导方针理解为一种“已分配容量指南”可能更为恰当，即它反映的是我们在 Azure 收入方面所能实现的交付能力。因为当我们投入资本、特别是部署 GPU（当然也包括 CPU，但更侧重于 GPU）时，实际上是在做出长期决策。我们首先要解决的是销售端使用量的增长，以及 Microsoft 365 Copilot 和 GitHub Copilot 等第一方应用加速普及所带来的需求；随后，我们确保持续投入于研发及产品创新的长期建设。过去一段时间以来，您所看到的我们及各产品线的诸多加速进展，很大程度上正源于我们将 GPU 资源与算力容量配置给了近年来持续引进的众多优秀 AI 人才。

Then, when you end up, is that, you end up with the remainder going towards serving the Azure capacity that continues to grow in terms of demand. And a way to think about it, because I think, I get asked this question sometimes, is if I had taken the GPUs that just came online in Q1 and Q2 in terms of GPUs and allocated them all to Azure, the KPI would have been over 40. And I think the most important thing to realize is that this is about investing in all the layers of the stack that benefit customers. And I think that's hopefully helpful in terms of thinking about capital growth, it shows in every piece, it shows in revenue growth across the business and shows as OpEx growth as we invest in our people.
随后，当您完成分配后，剩余部分将用于满足 Azure 不断增长的容量需求。对此，一种理解方式是——我有时会被问到这个问题——如果我把第一季度和第二季度新上线的所有 GPU 全部分配给 Azure，那么该关键绩效指标（KPI）将超过 40。我认为最重要的是要认识到，此举旨在投资于整个技术栈的各个层面，从而惠及客户。希望这种思路有助于大家理解资本投入的增长：它体现在业务的每个环节中，既反映在整体营收增长上，也体现为运营支出（OpEx）的增长——因为我们正在持续投资于人才队伍建设。

Satya Nadella
萨提亚·纳德拉
Chairman & CEO
董事长兼首席执行官

Yes, I think you -- Amy covered it. But basically, as an investor, I think when you think about our capital and you think about the GM profile of our portfolio, you should obviously think about Azure. But you should think about M365 Copilot and you should think about GitHub pilot, you should think about Dragon Copilot, Security Copilot. All of those have a GM profile and lifetime value. I mean if you think about it, acquiring an Azure customer is super important to us, but so is acquiring an M365 or a GitHub or a Dragon Copilot, which are all by the way incremental businesses and TAMs for us. And so we don't want to maximize just 1 business of ours, we want to be able to allocate capacity while we're sort of supply constrained in a way that allow us to essentially build the best LTV portfolio. That's on one side. And the other one that Amy mentioned is also R&D. I mean you got to think about compute is also R&D, and that's sort of the second element of it. And so we are using all of that, obviously, to optimize for the long term.
是的，我认为您——艾米已经讲过了。但基本上，作为投资者，当您思考我们的资本以及我们投资组合的毛利率（GM）特征时，显然应该考虑 Azure。同时，您也应该考虑 M365 Copilot、GitHub Copilot、Dragon Copilot 以及 Security Copilot。所有这些产品都具备自身的毛利率特征和客户终身价值（LTV）。也就是说，从我们的角度看，获取一位 Azure 客户固然至关重要，但获取一位 M365、GitHub 或 Dragon Copilot 客户同样重要——而这些业务本身也均为我们在增量层面拓展的新业务及可触达市场（TAM）。因此，我们并不希望仅仅最大化某一项业务，而是希望在当前算力供应受限的情况下，合理分配算力资源，从而构建出最优的客户终身价值（LTV）投资组合。这是第一方面。另一方面，正如艾米所提到的，还有研发投入（R&D）的问题。实际上，算力投入本身也属于研发范畴，这构成了第二方面考量。因此，我们显然正充分利用上述所有因素，以实现长期优化。

Operator
操作员

The next question comes from the line of Mark Moerdler with Bernstein Research.
下一个问题来自伯恩斯坦研究公司（Bernstein Research）的马克·莫尔德勒（Mark Moerdler）。

Mark Moerdler
马克·莫尔德勒
Bernstein Institutional Services LLC, Research Division
伯恩斯坦机构服务有限责任公司，研究部

Congrats on the quarter. One of the other questions we believe investors want to understand is how to think about your line of sight from hardware CapEx investment to revenue and margins. You capitalized servers over 6 years, but the average duration of your RPO is 2.5 years, up from 2 years last quarter. How do investors get comfortable that since this is a lot of this CapEx is AI-centric that you'll be able to capture sufficient revenue over the 6-year useful life of the hardware to deliver solid revenue and gross profit dollars growth, hopefully, one similar to the CPU revenue.
恭喜本季度的业绩表现。我们认为投资者还希望了解的另一个问题是：如何理解贵公司从硬件资本性支出（CapEx）投资到收入及利润率之间的路径与前景。贵公司将服务器资本化摊销期设定为 6 年，但目前合同负债（RPO）的平均期限为 2.5 年，较上季度的 2 年有所上升。鉴于当前大量资本性支出集中于 AI 相关领域，投资者如何确信贵公司能够在该等硬件 6 年的使用寿命内实现足够规模的收入，从而推动收入及毛利润金额实现稳健增长——理想情况下，其增长水平可与 CPU 业务收入相媲美？

Amy Hood
艾米·胡德
Executive VP & CFO
执行副总裁兼首席财务官（CFO）

Thanks, Mark. Let me start with at a high level and Satya can add as well. I think when you think about average duration, I think what you're getting to is -- and we need to remember, is it, average duration is a combination of a broad set of contract arrangements that we have. A lot of them around things like M365 or our BizApps portfolio, are shorter dated, right, 3-year contracts. And so they have, quite frankly, a short duration. The majority then that's remaining are Azure contracts are longer duration. And you saw that this quarter when we saw the extension of that duration from around 2 years to 2.5 years. And the way to think about that is the majority of the capital that we're spending today, and a lot of the GPUs that we're buying are already contracted for most of their useful life. And so a way to think about that is much of that risk that I think you're pointing to isn't there, because they're already sold for the entirety of their useful life. And so part of it exists because you have this shorter-dated RPO because of some of the M365 stuff. If you look at the Azure only, RPO is a little bit more extended. A lot of that is CPU basis. It's not just GPU. And on the GPU contracts that we've talked about, including for some of our largest customers, those are sold for the entire useful life of the GPU. And so there's not the risk to which I think you may be referring. Hopefully, that's helpful.
谢谢，马克。我先从宏观层面开始说明，萨提亚随后也会补充。关于平均合同期限，我想您关注的要点是——我们需要牢记，平均合同期限是我们各类合同安排的综合体现。其中许多合同，例如围绕 Microsoft 365（M365）或我们的商业应用（BizApps）投资组合所签订的合同，期限相对较短，通常为三年期合同，因此其合同期限实际上较短。剩余的主要部分则为 Azure 合同，期限更长；本季度我们已观察到该期限从约两年延长至两年半。理解这一点的关键在于：我们当前投入的大部分资本，以及大量采购的 GPU，其整个使用寿命期内的使用均已通过合同锁定。因此，您所指出的这部分风险实际上并不存在，因为这些资源在其整个生命周期内都已被预先售出。当然，部分风险之所以存在，是因为 M365 等业务带来了期限较短的未确认收入（RPO）。但若仅看 Azure 业务，其 RPO 的期限则相对更长，且其中很大一部分基于 CPU，而不仅限于 GPU。 关于我们此前讨论过的 GPU 合约，包括面向部分最大客户签署的合约，这些合约均按 GPU 的整个使用寿命进行销售。因此，并不存在您可能所指的风险。 希望如此，这很有帮助。

Satya Nadella
萨提亚·纳德拉
Chairman & CEO
董事长兼首席执行官

Yes. And just to -- one other thing I would add to it is, in addition to sort of what Amy mentioned, which is it's already contracted for the useful life is we do use software to continuously around even the latest models on the fleet that is aging, if you will. So that's sort of what gives us that duration. And so at the end of the day, we want to have -- that's why we even think about aging the fleet constantly, right? So it's not about buying a whole lot of gear 1 year. It's about each year, you write the Moore's Law, you add, you use software, and then you optimize across all of it.
是的。另外，我还想补充一点：除了艾米刚才提到的内容（即设备在其整个使用寿命内均已签订合约），我们还会持续利用软件对机队中日益老化的设备进行更新，包括部署最新的模型。这正是我们能够延长设备使用寿命的原因所在。因此，归根结底，我们始终关注机队的持续更新换代——这并非意味着某一年集中采购大量硬件，而是每年依据摩尔定律进行硬件升级、软件部署，并对整体系统进行优化。

Amy Hood
艾米·胡德（Amy Hood）
Executive VP & CFO
执行副总裁兼首席财务官（CFO）

And Mark, maybe to state this in case it's not obvious, is that as you go through the useful life, actually, you get more and more and more efficient at delivery. So where you've sold the entirety of its life, the margins actually improved with time. And so I think that may be a good reminder to people as we see that, obviously, in the CPU fleet all the time.
马克（Mark），为避免误解，我再明确说明一下：随着设备进入其使用寿命的不同阶段，其交付效率实际上会不断提升。也就是说，即便您已售出设备整个生命周期的服务，其利润率仍会随时间推移而逐步提高。这一点，在我们日常观察 CPU 机队时便十分明显，或许值得大家特别留意。

Operator
操作员

The next question comes from the line of Brent Thill with Jefferies.
下一个问题来自杰弗里斯公司（Jefferies）的布伦特·希尔（Brent Thill）。

Brent Thill
布伦特·希尔
Jefferies LLC, Research Division
杰富瑞有限责任公司，研究部

Amy, on 45% of the backlog being related to OpenAI. I'm just curious if you can comment, there's obviously concern about the durability. And I know maybe there's not much you can say on this, but I think everyone is concerned about the exposure. And if you could maybe talk through your perspective and what both you and Satya are seeing.
艾米，关于积压订单中 45%与 OpenAI 相关的问题，我很好奇您能否就此发表评论。显然，市场对此类订单的可持续性存在担忧。我知道您或许不便对此多做说明，但大家确实都关注着这一风险敞口。不知您能否分享一下您的看法，以及您和萨提亚目前所观察到的情况？

Amy Hood
艾米·胡德
Executive VP & CFO
执行副总裁兼首席财务官（CFO）

I think maybe I would have thought about the question quite differently, Brent. The first thing to focus on is the reason we talked about that number is because 55% or roughly $350 billion is related to the breadth of our portfolio, a breadth of customers across solutions, across Azure, across industries, across geographies. That is a significant RPO balance, larger than most peers, more diversified than most peers. And frankly, I think we have super high confidence in it.
布伦特，我想我可能会以截然不同的角度来思考这个问题。首先需要关注的是，我们之所以提及这一数字，是因为其余 55%（约合 3500 亿美元）的积压订单源自我们投资组合的广度——涵盖各类客户、Azure 平台上的各项解决方案、不同行业以及全球各地区。这一剩余履约义务（RPO）余额规模显著，不仅远超大多数同行，而且业务构成也比大多数同行更为多元化。坦率而言，我们对此具有极高的信心。

And when you think about that portion alone growing 28%, it's really impressive work on the breadth as well as the adoption curve that we're seeing, which is I think what I get asked most frequently, it's grown by customer segment, by industry and by geo. And so it's very consistent. And so then if you're asking about how do I feel about OpenAI and the contract and the health, listen, it's a great partnership. We continue to be their provider of scale. We're excited to do that. We sit under one of the most successful businesses built, and we continue to feel quite good about that. It's allowed us to remain a leader in terms of what we're building and being on the cutting edge of app innovation.
仅考虑该部分业务增长 28%，其在覆盖广度及采用率曲线上所展现出的强劲表现确实令人印象深刻。这也是我被问及最多的问题——该业务的增长遍及各客户细分市场、各行业以及各地区，表现极为一致。至于您询问我对 OpenAI 及其合同与业务健康状况的看法，坦白说，这是一段非常出色的合作关系。我们持续作为其规模化服务的提供商，对此我们深感振奋。我们正置身于有史以来最成功的企业之一旗下，对此我们始终充满信心。这一合作也使我们得以持续保持在应用创新前沿的领导地位。

Operator
操作员

The next question comes from the line of Karl Keirstead with UBS.
下一个问题来自瑞银（UBS）分析师卡尔·凯尔斯蒂德（Karl Keirstead）。

Karl Keirstead
卡尔·凯尔斯蒂德
UBS Investment Bank, Research Division
瑞银投资银行，研究部

Amy, regardless of how you allocate the capacity between first party and third party, can you comment qualitatively on the amount of capacity that's coming on. I think the 1 gigawatt added in the December quarter was extraordinary and hence that the capacity adds are accelerating. But I think a lot of investors have their eyes on Fairwater Atlanta, Fairwater Wisconsin, and would love some comments about the magnitude of the capacity adds regardless of how they're allocated in the coming quarters.
艾米，无论您如何在第一方与第三方之间分配产能，您能否从定性角度谈谈即将上线的产能规模？我认为，截至 12 月财季新增的 1 吉瓦产能非常可观，表明产能扩张正在加速。但许多投资者目前高度关注费尔沃特亚特兰大（Fairwater Atlanta）和费尔沃特威斯康星（Fairwater Wisconsin）项目，非常希望了解未来几个季度新增产能的具体规模，无论这些产能将如何在第一方与第三方之间进行分配。

Amy Hood
艾米·胡德
Executive VP & CFO
执行副总裁兼首席财务官（CFO）

Yes, Karl, I think we've said a couple of things. We're working as hard as we can to add capacity as quickly as we can. You've mentioned specific sites like Atlanta or Wisconsin, those are multiyear deliveries. So I wouldn't focus necessarily on specific locations. The real thing we've got to do, and we're working incredibly hard doing it, is adding capacity globally. A lot of that will be added in the United States, the 2 locations you've mentioned, but it also needs to be added across the globe to meet the customer demand that we're seeing and the increased usage. We'll continue to add both long-lived infrastructure. The way to think about that is we need to make sure we've got power and land and facilities available and we'll continue to put GPUs and CPUs in them when they're done as quickly as we can.
是的，卡尔，我想我们已经提到了几点。我们正竭尽全力以最快的速度增加产能。您提到的亚特兰大或威斯康星等具体地点，其交付周期长达数年，因此您未必需要特别关注具体位置。我们真正需要做、并且正在全力以赴推进的，是在全球范围内增加产能。其中很大一部分新增产能将位于美国，包括您提到的这两个地点，但与此同时，我们也必须在全球其他地区同步扩充产能，以满足当前客户不断增长的需求和使用量的持续攀升。我们将持续投入建设长期使用的基础设施——简而言之，就是确保电力供应、土地资源及配套设施及时到位；待设施建成后，我们将以最快速度部署 GPU 和 CPU。

And then finally, we'll try to make sure we can get as efficient as we possibly can on the pace at which we do that and how we operate them so that they can have the highest possible utility. And so I think it's not really about 2 places, Karl, I would definitely abstract away from that. Those are multiyear delivery time lines. But really, we just need to get it done every location where we're currently in a build or starting to do that. We're working as quickly as we can.
最后，我们将努力确保在执行该计划的过程中尽可能提高效率，并优化运营方式，以实现最高的利用率。因此，我认为这并不仅仅关乎两个地点，卡尔。我肯定会将这个问题抽象化处理。这些交付时间表都跨越多个年度。实际上，我们只需在当前正在建设或即将启动建设的每个地点尽快完成即可，而我们正全力以赴地推进。

Operator
操作员

The next question comes from the line of Mark Murphy with JPMorgan.
下一个问题来自摩根大通（JPMorgan）的马克·墨菲（Mark Murphy）。

Mark Murphy
马克·墨菲（Mark Murphy）
JPMorgan Chase & Co, Research Division
摩根大通公司，研究部

Satya, the performance achievements of the Maia 200 accelerator for inference, look quite remarkable, especially in comparison to TPUs and Trinium and Blackwell, which have just been around a lot longer. Could you put that accomplishment in perspective in terms of how much of a core competency you think silicon might become for Microsoft. And Amy, are there any ramifications worth mentioning there in terms of supporting your gross margin profile for inference costs going forward?
萨提亚（Satya），Maia 200 推理加速器所取得的性能成就非常出色，尤其与已问世更久的 TPU、Trinium 及 Blackwell 相比更是如此。您能否从战略角度谈谈，芯片设计未来可能在微软核心能力中占据怎样的地位？艾米（Amy），这一进展是否会对贵公司未来推理成本相关的毛利率产生值得关注的影响？

Satya Nadella
萨提亚·纳德拉
Chairman & CEO
董事长兼首席执行官

Yes, thanks for the question. So a couple of things. One is we've been at this in a variety of different forms for a long, long time in terms of building our own silicon. And so we're very, very thrilled about the progress with Maia 200, and -- especially when we think about running a GPT-5.2 and the performance we were able to get in the GEMS at FB4, just proof point that when you have a new workload, a new shape of a workload, you can start innovating end-to-end between the model and the silicon and the entire system. It's just not even about just the silicon, the way the networking works at rack scale that's optimized with memory for this particular workload.
是的，感谢您的提问。首先，我们在自研芯片领域已深耕多年，以多种形式持续推进。因此，我们对“迈阿密 200”（Maia 200）所取得的进展感到非常振奋——尤其是当我们考虑其运行 GPT-5.2 模型时，在 FB4 数据中心 GEMS 系统中所展现出的卓越性能，这正有力印证了一点：面对全新工作负载，或工作负载形态发生根本变化时，我们能够围绕模型、芯片及整个系统开展端到端协同创新。这绝不仅仅关乎芯片本身，还包括针对该特定工作负载，在机架级网络架构与内存配置方面所实现的深度优化。

And the other thing is we're obviously round-tripping and working very closely with own super intelligence team with all of our models, as you can imagine, whatever we build will be all optimized for Maia. So we feel great about it. And I think the way to think about all up is we're in such early innings. I mean, even just look at the amount of silicon innovation and systems innovation. Even since December, I think the new thing is everybody is talking about low latency inference, right? And so one of the things we want to make sure is we are not locked into any one thing. If anything, we have great partnership with NVIDIA, with AMD, they are innovating, we're innovating. We want a fleet at any given point in time to have access to the best TCO. And it's not a one-generation game. I think a lot of folks just talk about who's ahead. It's just remember, you have to be ahead for all time to come. And that means you really want to think about having a lot of innovation that happens out there to be in your fleet, so that your fleet is fundamentally advantaged at the TCO level. So that's kind of how I look at it, which is we are excited about Maia. We're excited about Cobalt. We're excited about our DPU, our NIC. So we have a lot of systems capability. That means we can vertically integrate. And because we can vertically integrate doesn't mean we just only vertically integrate. And so we want to be able to have the flexibility here, and that's what you see us do.
另一点是，正如您所料，我们显然正在与自有超级智能团队紧密协作，并围绕所有模型开展往返式开发工作；我们构建的任何产品都将针对 Maia 进行全面优化。因此，我们对此充满信心。 总体来看，我认为目前仍处于非常早期的发展阶段。仅以芯片和系统层面的创新为例：甚至自去年 12 月以来，业界新涌现的一大焦点就是低延迟推理，对吧？因此，我们希望确保自身不会被锁定在某一种技术路径上。事实上，我们与英伟达（NVIDIA）和超威半导体（AMD）均保持着卓越的合作关系——他们在持续创新，我们也在持续创新。我们希望在任一时间点，我们的算力集群都能随时接入具备最优总体拥有成本（TCO）的硬件方案。这绝非仅关乎单一代际的竞争。许多人只关注“谁眼下领先”，但请务必牢记：真正的挑战在于，必须长期保持领先。这意味着，您必须充分吸纳外部涌现的大量创新成果，并将其融入自身算力集群，从而在总体拥有成本（TCO）层面构筑根本性优势。 这便是我的整体看法：我们对 Maia 充满期待，同样也对 Cobalt 充满期待。 我们对自家的 DPU（数据处理单元）和 NIC（网络接口卡）感到非常兴奋。因此，我们在系统层面拥有强大的能力，这意味着我们可以实现垂直整合。但能够垂直整合，并不意味着我们只做垂直整合。我们希望在此领域保有充分的灵活性，而这正是你所看到我们正在做的。

Operator
操作员

The next question comes from the line of Brad Zelnick with Deutsche Bank.
下一个问题来自德意志银行的布拉德·泽尔尼克（Brad Zelnick）。

Brad Zelnick
布拉德·泽尔尼克（Brad Zelnick）
Deutsche Bank AG, Research Division
德意志银行股份有限公司，研究部

Satya, we heard a lot about Frontier transformations from Judson at Ignite, and we've seen customers realize breakthrough benefits when they adopt the Microsoft AI stack. Can you help frame for us the momentum in enterprises embarking on these journeys? And any expectation for how much their spend with Microsoft can expand in becoming frontier firms?
萨提亚（Satya），我们在 Ignite 大会上听贾德森（Judson）详细介绍了“前沿转型”（Frontier transformations）；我们也看到，客户在采用微软 AI 技术栈后，已切实获得突破性收益。您能否为我们梳理一下，目前企业开启此类转型之旅的整体进展与势头？此外，对于这些正迈向“前沿企业”（frontier firms）的客户，您预计他们未来在微软的支出规模将扩大到何种程度？

Satya Nadella
萨提亚·纳德拉
Chairman & CEO
董事长兼首席执行官

Yes. Thank you for that. So I think one of the things that we are seeing is the adoption across the 3 major suites of ours, right? So if you take M365, you take what's happening with security and you take GitHub. In fact, it's fascinating. I mean these 3 things had effectively compounding effects for our customers in the past, like something like Entra as an identity system, or Defender as the protection system, across all 3 was sort of super helpful.
是的，感谢您的提问。我认为我们目前看到的一个现象是，我们的三大产品套件正获得广泛采用，这三大套件分别是：Microsoft 365、安全产品线以及 GitHub。事实上，这一趋势非常引人注目。过去，这三大产品线对客户而言具有显著的协同增效作用——例如，Entra 作为统一身份认证系统，Defender 作为端到端防护体系，均可无缝覆盖全部三大平台，从而为客户带来极大价值。

But so what now you're seeing is something like Work IQ, right? So I mean just to give you a favor for it, the most important database underneath for any company that uses Microsoft today is the data underneath Microsoft 365. And the reason is because it has all those tacit information, right, who are your people, what are their relationships, what are their projects they're working on, what are their artifacts, their communications. So that's a super important asset for any business process, business workflow context.
而如今，您所看到的正是类似“Work IQ”这样的创新产品。不妨举个例子：对于当前使用微软产品的任何企业而言，其最核心的数据资产，恰恰就是 Microsoft 365 平台底层所沉淀的数据。原因在于，这些数据完整承载了大量隐性信息——例如企业员工是谁、彼此之间存在怎样的协作关系、正在推进哪些项目、产出过哪些工作成果、以及日常沟通交流的轨迹等。因此，在任何业务流程与工作流场景中，这些数据都已成为一项至关重要的战略资产。

In fact, the scenario I even had in my transcript around you can now take Work IQ as an MCP server and GitHub Repo and say, "Hey, please look at my design meetings for the last month in Teams and tell me if my repo reflects it." I mean that's a pretty high-level way to think about how, what is happening previously perhaps with our tools business and our GitHub business are suddenly now being transformative, right? That agent black plane is really transforming companies in some sense, right? That's, I think, the most magical thing, which is you deploy these things. And suddenly, the agents are helping you coordinate, bring more leverage to your enterprise.
事实上，我在会议记录中提到的场景是：你现在可以将 Work IQ 作为 MCP 服务器和 GitHub 仓库使用，并提出请求：“嘿，请查看我过去一个月在 Teams 中的设计会议内容，并告诉我我的代码仓库是否反映了这些会议成果。” 我的意思是，这是一种相当高层次的思考方式，用以理解此前或许仅限于我们工具业务和 GitHub 业务的功能，如今正迅速转变为具有变革性的影响，对吧？从某种意义上说，这种智能代理“黑箱”确实在真正改变企业，对吧？我认为，这最神奇之处在于：你部署了这些工具后，智能代理随即开始协助你协调工作，为你的企业带来更高的杠杆效应。

Then on top of it, of course, there is the transformation, which is what businesses are doing. How should we think about customer service. How should we think about marketing. How should we think about finance. How should we think about that and build our own agents. That's where all the services in Fabric and Foundry. And of course, GitHub tooling is helping them or even the low-code/no-code tools. I had some stats on how much that's being used. But one of the more exciting things for me is the new agents systems, M365 Copilot, GitHub Copilot, Security Copilot, all coming together to compound the benefits of all the data and all the deployment, I think, is probably the most transformative effect right now.
在此基础之上，当然还有企业正在进行的数字化转型：我们应如何思考客户服务？如何思考市场营销？如何思考财务管理？又该如何构建我们自己的智能代理？Fabric 和 Foundry 中的所有服务正是为此而生。当然，GitHub 的开发工具，甚至低代码/无代码工具，也在助力企业实现这一目标。我掌握了一些关于这些工具使用程度的统计数据。但对我而言，更令人振奋的是新一代智能代理系统——Microsoft 365 Copilot、GitHub Copilot 和 Security Copilot 正在协同整合，从而叠加放大所有数据与部署所带来的效益。我认为，这或许是当下最具变革性的影响。

Jonathan Neilson
乔纳森·尼尔森
Vice President of Investor Relations
投资者关系副总裁

Thanks, Brad. Operator, we have time for 1 last question.
谢谢布拉德。各位，操作员，我们还剩最后一个问题的时间。

Operator
操作员

And the last question will come from the line of Raimo Lenschow with Barclays.
最后一个问题来自巴克莱银行的雷莫·伦施（Raimo Lenschow）先生。

Raimo Lenschow
雷莫·伦施沃
Barclays Bank PLC, Research Division
巴克莱银行股份有限公司，研究部

The last few quarters we talked -- besides the GPU side, you talked about CPU as well on the Azure side and you had some operational changes at the beginning of January last year. Can you speak what you saw there? And maybe put it more on a bigger picture in terms of clients realizing that their move to the cloud is important if you want to deliver proper AI. So what are we seeing in terms of cloud transition?
过去几个季度，我们讨论过——除了 GPU 方面，您还提到了 Azure 平台的 CPU 情况，而且去年 1 月初您还进行了一些运营调整。您能否谈谈当时观察到的情况？此外，能否从更宏观的角度阐述一下：客户正逐渐意识到，若想真正实现人工智能（AI）能力，向云迁移至关重要。那么，目前我们在云迁移方面看到了哪些趋势？

Satya Nadella
萨提亚·纳德拉
Chairman & CEO
董事长兼首席执行官

I didn't quite...
我并未完全……

Jonathan Neilson
乔纳森·尼尔森
Vice President of Investor Relations
投资者关系副总裁

Sorry, Raimo, you were asking about the SMC CPU side? Or can you just repeat the question, please?
抱歉，雷莫，您刚才问的是 SMC 的 CPU 端情况吗？或者您能再重复一下问题吗？

Raimo Lenschow
雷莫·伦施
Barclays Bank PLC, Research Division
巴克莱银行股份有限公司，研究部

Yes. Sorry. So I was wondering about the CPU side of Azure because we had some operational changes there. And we also hear from the [ field a lot ] that people are realizing they need to be in the Cloud if you want to do proper AI and if that's kind of driving momentum.
是的，抱歉。我刚才想了解的是 Azure 在 CPU 端的情况，因为我们在该领域已进行了一些运营调整。此外，我们还从[一线市场]听到大量反馈：客户逐渐意识到，若要真正开展人工智能（AI）相关工作，就必须上云，而这似乎正在推动业务增长势头。

Satya Nadella
萨提亚·纳德拉
Chairman & CEO
董事长兼首席执行官

Yes. I think I get it. So first of all, I had mentioned in my remarks that when you think about AI workloads, you should think of AI workloads as just AI accelerator compute, right? Because in some sense, you take any agent, the agent will then spawn through tools used maybe a container, which runs obviously on compute. In fact, we have -- whenever we think about even building out of the fleet, we think of in ratios or even for a training job, by the way. An AI training job requires a bunch of compute and a bunch of storage very close to compute. So therefore -- and same thing in inferencing as well.
是的，我明白您的意思。首先，我在发言中提到过，当您考虑人工智能（AI）工作负载时，应将其视为纯粹的 AI 加速器计算，对吧？因为从某种意义上说，无论您采用何种智能体（agent），该智能体都会通过调用工具（例如容器）来执行任务，而这些工具显然运行在计算资源之上。事实上，我们——甚至在规划整个服务器集群的构建时——都会以特定比例来统筹考量；同样地，在训练任务中也是如此。一项 AI 训练任务需要大量计算资源，以及与这些计算资源物理位置非常接近的大量存储资源。因此，推理（inferencing）环节亦是如此。

So in inferencing with agent mode would require you to essentially provision a computer or computing resources to the agent. So not -- they don't need GPUs. They're running on GPUs, but they need computers, which are compute and storage. So that's what's happening even in the new world.
因此，在采用智能体模式进行推理时，本质上需要为该智能体配置一台计算机或相应的计算资源。也就是说——它们并不单纯依赖 GPU，尽管其运行确实依托于 GPU；它们真正需要的是兼具计算能力与存储能力的完整计算机系统。这正是当前新范式下正在发生的情况。

The other thing you mentioned is the Cloud migrations are still going on. In fact, 1 of the stats I had was SQL -- latest SQL server growing as an IaaS service in Azure. And so -- that's one of the reasons why we have to think about our commercial cloud and keep it balanced with the rest of our AI Cloud because when clients bring their workloads and build new workloads, they need all of these infrastructure elements in the region in which they are deploying.
您提到的另一件事是云迁移仍在持续进行中。事实上，我掌握的一项统计数据表明：最新版 SQL Server 作为 Azure 中的一项 IaaS 服务正持续增长。因此，这也是我们必须统筹考虑商业云战略，并使其与我们的 AI 云保持平衡的原因之一——因为当客户将其工作负载迁移上云或构建新工作负载时，他们需要在自身部署所在区域中拥有全部这些基础设施组件。

Jonathan Neilson
乔纳森·尼尔森（Jonathan Neilson）
Vice President of Investor Relations
投资者关系副总裁

That wraps up the Q&A portion of today's earnings call. Thank you for joining us today, and we look forward to speaking with you all soon.
今天财报电话会议的问答环节到此结束。感谢各位今天的参与，我们期待尽快再次与大家交流。

Satya Nadella
萨提亚·纳德拉（Satya Nadella）
Chairman & CEO
董事长兼首席执行官

Thank you all.
谢谢大家。

Amy Hood
艾米·胡德
Executive VP & CFO
执行副总裁兼首席财务官（CFO）

Thank you.
谢谢。

Operator
操作员

Thank you. This concludes today's conference. You may disconnect your lines at this time, and we thank you for your participation. Have a great night.
谢谢。本次会议到此结束。您现在可以挂断电话，感谢您的参与。祝您晚上愉快。