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总览/微软/财报分析/FY2027Q1/逐字稿

FY2027Q1 电话会逐字稿

2026-10-28 来源:谷歌财经 / Quartr 96 段 · 11 位发言人 52 段被报告引用FY2027Q1 季度页 →电话会深度解析 →
译文 96/96 段 · 引用以英文原文为准

发言人

点击某位发言人,只突出显示其发言;再次点击恢复
姓名职位机构段落
Amy HoodCFOMicrosoft30
Satya NadellaChairman and CEOMicrosoft29
Jonathan NeilsonVP of Investor RelationsMicrosoft14
Operator10
Brad RebackAnalystStifel3
Adam WoodAnalystMorgan Stanley2
Karl KeirsteadAnalystUBS2
Gabriela BorgesAnalystGoldman Sachs2
Tal LianiAnalystBank of America2
Mark MoerdlerAnalystBernstein Research1
Brent ThillAnalystJefferies1

● 公司管理层 / 主持人 ● 外部分析师

P00100:00
Operator
Greetings, and welcome to the Microsoft Fiscal Year 2027 first quarter earnings conference call. At this time, all participants are in a listen-only mode. A question and answer session will follow the formal presentation. If anyone should require operator assistance, please press star zero on your telephone keypad. As a reminder, this conference is being recorded. It is now my pleasure to introduce Jonathan Neilson, Vice President of Investor Relations.
大家好,欢迎参加微软 2027 财年第一季度财报电话会议。目前所有参会者均处于仅收听模式。正式陈述结束后将进入问答环节。如需接线员协助,请按电话键盘上的星号键加 0。提醒各位,本次会议正在录音。现在我很高兴向大家介绍投资者关系副总裁 Jonathan Neilson。
P00200:31
Jonathan NeilsonVP of Investor Relations
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 Brian DeFoe, Deputy General Counsel and Corporate Secretary. 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 when we provide Outlook commentary on today's call. 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.
下午好,感谢大家今天参加我们的会议。今天与我一同参会的有董事长兼首席执行官 Satya Nadella、首席财务官 Amy Hood、首席会计官 Alice Jolla,以及副总法律顾问兼公司秘书 Brian DeFoe。在微软投资者关系网站上,您可以找到我们的财报新闻稿和财务摘要演示文稿,这些材料旨在补充我们今天电话会议上的准备发言,并提供公认会计准则(GAAP)与非公认会计准则(non-GAAP)财务指标之间差异的调节表。当我们今天在电话会议上提供展望评论时,更详细的展望幻灯片将在微软投资者关系网站上公布。在本次电话会议上,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替代或优于按照 GAAP 编制的财务业绩指标。
P00301:29
They are included as additional clarifying items to aid investors in further understanding the company's first quarter performance, in addition to the impact these items and events have on the financial results. All growth comparisons we make on the call today relate 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 business 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. We will post our prepared remarks to our website immediately following the call until the complete transcript is available. 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.
纳入这些指标是作为额外的说明项目,以帮助投资者进一步理解公司第一季度的业绩表现,以及这些项目和事件对财务业绩的影响。除非另有说明,我们今天在电话会议上所做的所有增长比较均与去年同期相比。在可获得的情况下,我们还将提供按固定汇率计算的增长率,作为评估我们基础业务表现的框架,以剔除汇率波动的影响。当按固定汇率计算的增长率与报告增长率相同时,我们将仅提及该增长率。电话会议一结束,我们就会将准备好的发言稿发布到我们的网站上,直至完整逐字稿准备就绪。今天的电话会议正在进行网络直播和录音。如果您提出问题,该问题将被包含在我们的直播传输、逐字稿以及录音的任何未来使用中。
P00402:28
You can replay the call and view the transcript on the Microsoft Investor Relations website. 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 statements. With that, I'll turn the call over to Satya.
您可以在微软投资者关系网站上回听本次电话会议并查看逐字稿。在本次电话会议期间,我们将作出前瞻性陈述,这些陈述是对未来事件的预测、推算或其他陈述。这些陈述基于当前的预期和假设,受各种风险和不确定性的影响。由于今天的财报新闻稿、本次电话会议期间发表的评论,以及我们的 10-K 表格、10-Q 表格和向美国证券交易委员会提交的其他报告和文件中的风险因素部分所讨论的因素,实际结果可能存在重大差异。我们不承担更新任何前瞻性陈述的义务。下面,我将把电话交给 Satya。
P00503:16
Satya NadellaChairman and CEO
Thank you very much, Jonathan. It was a fast start to our fiscal year. Microsoft Cloud revenue surpassed $63 billion, with growth accelerating to 30% year-over-year. We are focused on three things: designing AI to empower people, ensuring every organization has sovereignty over its own learning, and building trust with controls that ensure agent safety and security. Now let's talk about how we are making progress on those goals as we build the new tech stack, starting with Copilot. We announced our biggest update to Copilot to date this quarter, bringing together chat, co-work, autopilot, and code into one unified experience. It's one product experience across commercial and consumer and comes with all of Office built in. We think of Copilot as the new OS for work. Customers are increasingly turning to Copilot to get real work done. Automated tasks has nearly doubled since July.
非常感谢,Jonathan。我们的新财年取得了开门红。Microsoft Cloud 营收突破 630 亿美元,同比增速加快至 30%。我们专注于三件事:设计赋能于人的人工智能(AI)、确保每个组织对自身的学习拥有主权,以及通过确保智能体安全和安保的控制措施来建立信任。现在让我们谈谈在构建全新技术栈的过程中,我们在实现这些目标方面所取得的进展,首先从 Copilot 开始。本季度我们发布了迄今为止对 Copilot 最大规模的更新,将聊天、协同办公(co-work)、自动驾驶(autopilot)和代码整合为一体化的统一体验。这是横跨企业客户与个人消费者的统一产品体验,并内置了全部 Office 功能。我们将 Copilot 视为工作的新操作系统(OS)。客户正越来越多地借助 Copilot 来完成实际工作。自 7 月以来,自动化任务量已接近翻倍。
P00604:12
Daily users are up nearly 50% quarter-over-quarter and over 5X year-over-year. User satisfaction improved nearly 20% quarter-over-quarter to another all-time high, and 90% of Copilot queries use auto mode, which dynamically routes tasks across models optimizing for quality, speed, and cost. These improvements are translating into larger purchases. The number of customers with more than 50,000 Copilot seats increased over 8X year-over-year, including Capgemini, HCLTech, Hitachi Group, Truist Financial, and U.K. Revenue and Customs Department. Just last week, Volkswagen announced plans to deploy Copilot to more than 330,000 employees, one of the largest deployments to date in Europe. We're also seeing strong momentum with E7, which brings together Copilot, E5, Entra, and Agent 365. Thousands of customers in every industry have purchased the suite to date, including Amadeus, BlackRock, Fiserv, New South Wales Health Department, and ZEISS.
日活跃用户环比增长近 50%,同比增长超过 5 倍。用户满意度环比提升近 20%,再创历史新高;90% 的 Copilot 查询使用自动模式(auto mode),该模式可在不同模型之间动态路由任务,从而针对质量、速度和成本进行优化。这些改进正在转化为更大规模的采购。拥有超过 50,000 个 Copilot 席位的客户数量同比增长超过 8 倍,其中包括 Capgemini、HCLTech、Hitachi Group、Truist Financial 以及英国税务海关总署(U.K. Revenue and Customs Department)。就在上周,Volkswagen 宣布计划向超过 330,000 名员工部署 Copilot,这是迄今为止欧洲规模最大的部署之一。我们还看到 E7 展现出强劲势头,它将 Copilot、E5、Entra 和 Agent 365 整合在一起。迄今为止,各行各业已有数千家客户购买了该套件,包括 Amadeus、BlackRock、Fiserv、新南威尔士州卫生部(New South Wales Health Department)和 ZEISS。
P00705:20
Our business model is expanding from per-seat subscriptions to include consumption, expanding our TAM and ARPU. The subscription brings increasingly capable everyday intelligence to every user. Typically, IT funds this, consolidating frontier advances for everyone across the organization. As agents take on higher-value work, consumption opens up business-funded demand, with spending tied directly to the value these agents deliver. The number of Copilot customers actively consuming credits through usage-based billing grew over 75% over the quarter. When it comes to software development, all major coding agents have shown up to work on GitHub. Agent-generated PRs have increased 6X over the past six months, and agents now open more than a third of all PRs on the platform. We are very hard at work on reliability as agentic activity on GitHub soars.
我们的商业模式正在从按席位订阅扩展到包含按量消耗,从而扩大我们的潜在市场规模(TAM)和每用户平均收入(ARPU)。订阅模式为每位用户带来能力不断提升的日常智能。通常由 IT 部门为此提供资金,将前沿技术进展整合后普及给组织内的每一个人。随着智能体承担更高价值的工作,按量消耗模式打开了由业务部门出资的需求,支出与这些智能体所交付的价值直接挂钩。本季度通过按使用量计费积极消耗额度的 Copilot 客户数量环比增长超过 75%。在软件开发领域,所有主流编程智能体都已经来到 GitHub 上工作。过去 6 个月里,由智能体生成的拉取请求(PR)增加了 6 倍,目前智能体发起的 PR 已占平台全部 PR 的 1/3 以上。随着 GitHub 上的智能体活动激增,我们正全力以赴保障平台可靠性。
P00806:19
At GitHub Universe this morning, we shared how we are expanding capacity and rebuilding the core Git architecture for the agentic wave. Also at Universe, we announced broad availability of Copilot Fusion, which is all about bringing multi-model orchestration to software development. It delivers frontier-level quality up to 40% faster and at up to 77% lower cost. Credit consumption from agentic features on GitHub has more than doubled since usage-based billing went into effect, and we are also helping developers secure their code and turn AI-generated code into high-quality software. GitHub Advanced Security revenue increased over 50% year-over-year as customers use its AI capabilities to scan entire repos and fix vulnerabilities in real time.
在今天上午的 GitHub Universe 大会上,我们分享了我们如何扩展容量并针对智能体浪潮重构核心 Git 架构。同样在 Universe 大会上,我们宣布全面推出 Copilot Fusion,其核心是将多模型编排引入软件开发。它能够以最高快 40% 的速度和最高低 77% 的成本交付前沿水准的质量。自按使用量计费生效以来,GitHub 上来自智能体功能的额度消耗已翻了一番以上;同时我们也在帮助开发者保护代码安全,并将 AI 生成的代码转化为高质量软件。GitHub Advanced Security 营收同比增长超过 50%,客户利用其 AI 能力扫描整个代码库并实时修复漏洞。
P00907:06
In the business application space, we are extending this vision of Copilot as the new OS for work, bringing the business logic and capabilities of Dynamics 365 directly into Copilot and helping every organization stand up their own infinite SaaS factory. This quarter, we introduced 13 new Copilot skills across Dynamics 365, which enables customers to access CRM and ERP capabilities directly in the flow of work. In recruiting, more than 10 million LinkedIn members use our LinkedIn AI-powered job search daily, and 25,000 customers are using our agentic hiring solutions. Recruiters using Hiring Assistant are finding interview-quality applicants 33% faster while reviewing 83% fewer profiles to find qualified match. In healthcare, we automated 30 million patient encounters this quarter, up 70% year-over-year, helping clinicians spend less time on administrative work and more time with patients.
在商业应用领域,我们正在延续将 Copilot 打造为工作新操作系统的愿景,把 Dynamics 365 的业务逻辑和功能直接引入 Copilot,帮助每个组织建立属于自己的无限 SaaS 工厂。本季度,我们在 Dynamics 365 中推出了 13 项新的 Copilot 技能,使客户能够在工作流程中直接调用 CRM 和 ERP 功能。在招聘领域,每天有超过 1,000 万名 LinkedIn 会员使用我们由 AI 驱动的 LinkedIn 求职搜索,并有 25,000 家客户正在使用我们的智能体招聘解决方案。使用 Hiring Assistant 的招聘人员找到符合面试质量的求职者的速度加快了 33%,同时为找到合格匹配人选而需要审阅的简历数量减少了 83%。在医疗健康领域,本季度我们自动化处理了 3,000 万次患者问诊记录,同比增长 70%,帮助临床医生减少行政事务时间,将更多时间留给患者。
P01008:07
10 providers, including Advocate Health, Mass General Brigham, Mercy, Intermountain Healthcare, and others, have used our solutions to document over one million encounters each since the beginning of the calendar year. In science, our FDE teams are working with customers to use Discovery to accelerate scientific progress. A great example is Saint-Gobain, which used Discovery to accelerate the development of low-carbon construction materials. Underneath our first-party agentic experience is a common platform. It starts with Foundry, which is becoming an increasingly important driver of our growth. Foundry helps organizations build learning loops grounded in their business context and deploy agents safely at scale. We now have over 120,000 Foundry customers, with revenue more than tripling year-over-year. Foundry's model choice and feature set, coupled with its deep integration across our stack, is driving differentiation. Azure OpenAI directly benefited in the last quarter with big advances in OpenAI models.
自今年年初以来,包括 Advocate Health、Mass General Brigham、Mercy、Intermountain Healthcare 等在内的 10 家医疗机构已各自使用我们的解决方案记录了超过 100 万次问诊。在科学领域,我们的前线部署工程师(FDE)团队正与客户合作,利用 Discovery 加速科学进展。Saint-Gobain 就是一个很好的例子,该公司利用 Discovery 加速了低碳建筑材料的研发。在我们第一方智能体体验的底层是一个通用平台。它始于 Foundry,Foundry 正成为推动我们增长的越来越重要的引擎。Foundry 帮助组织建立扎根于自身业务语境的学习闭环,并安全地大规模部署智能体。我们目前拥有超过 120,000 家 Foundry 客户,营收同比增长超过 2 倍(即增长至原来的 3 倍以上)。Foundry 的模型选择和功能集,加上它与我们整个技术栈的深度集成,正在推动差异化优势。上季度随着 OpenAI 模型取得重大进展,Azure OpenAI 直接从中受益。
P01109:13
When you couple this with our model choice built into Foundry, customers are able to build solutions optimizing across quality, cost, and performance. In fact, the number of customers building agentic solutions with multiple models increased 5X year-over-year, and revenue from open source models on Foundry increased 10X. We also continue to make rapid progress with our first-party models. Our goal is to advance the cost to outcome frontier, which means delivering capabilities comparable to leading models within three to six months of their release at a fraction of the training cost, thereby allowing us to transfer those cost benefits to customers. You see this in our products today. MAI Cyber now powers over 40% of the scans in our agentic MDASH code scanner at 18% lower cost per scan.
当将其与 Foundry 内置的模型选择相结合时,客户就能够构建在质量、成本和性能之间实现优化的解决方案。事实上,使用多模型构建智能体解决方案的客户数量同比增长了 5 倍,而 Foundry 上开源模型的营收增长了 10 倍。我们在自研第一方模型方面也继续取得快速进展。我们的目标是推进“成本-效果”前沿,这意味着在领先模型发布后的 3 到 6 个月内,以极小一部分的训练成本交付与之相当的能力,从而让我们能够将这些成本效益传递给客户。今天在我们的产品中就能看到这一点。MAI Cyber 目前驱动了我们智能体 MDASH 代码扫描器中超过 40% 的扫描任务,每次扫描成本降低了 18%。
P01210:01
MAI Transcribe is the most accurate and cheapest transcription model in the world, supporting Dragon Copilot's multilingual workflow. MAI Code Flash has three million users in GitHub Copilot last month alone, helping developers get more out of their AI credits. Microsoft-Decision-1 is our new model for structured decision-making, outperforming both LLMs and other decision models in latency and quality. Over 4,000 customers, including Atos Group, Equinor, and RBI, have already used it in the first month since its release. We recently completed pre-training MAI Base 2, which outperforms other open weight models we tested with four to 12 times greater training compute efficiency. This base model will be used in the upcoming MAI models across thinking, code, and cyber. Beyond models, we are making the harness behind our own Copilot experience available to customers in Foundry.
MAI Transcribe 是全球最准确且最便宜的语音转录模型,为 Dragon Copilot 的多语言工作流提供支持。仅上个月,MAI Code Flash 在 GitHub Copilot 中就拥有 300 万用户,帮助开发者充分利用其 AI 额度。Microsoft-Decision-1 是我们用于结构化决策的新模型,在延迟和质量上均优于大语言模型(LLM)及其他决策模型。在该模型发布后的第一个月内,包括 Atos Group、Equinor 和 RBI 在内的超过 4,000 家客户就已经投入使用。我们最近完成了 MAI Base 2 的预训练,其表现优于我们测试过的其他开源权重模型,训练算力效率高出 4 到 12 倍。该基础模型将用于即将推出的涵盖推理思考(thinking)、代码和网络安全领域的 MAI 模型。除了模型之外,我们还将支撑自身 Copilot 体验的底层运行框架(harness)在 Foundry 中向客户开放。
P01310:58
It gives customers a Microsoft-managed way to build agents that reason, use tools, complete complex, long-running work while preserving their choice of model. Another critical layer is data. We now have 44,000 paid Fabric customers, up more than 50% year-over-year. We are bringing Foundry and Fabric closer together so you can build your own agents right next to data. Over 19,000 customers now use Foundry and Fabric as enterprises connect and operate agents over real-time operational, analytical, and unstructured data. Customers are also rapidly deploying our AI-optimized databases, including PostgreSQL, SQL DB, Hyperscale, Cosmos DB, to give agents fast, secure access to the data and context they need. PostgreSQL growth accelerated for the fourth consecutive quarter, and the number of PostgreSQL customers also using Foundry accelerated to 90% year-over-year.
它为客户提供了一种由微软托管的方式,用于构建能够推理、使用工具、完成复杂且长周期工作的智能体,同时保留他们的模型选择权。另一个关键层是数据。我们目前拥有 44,000 家付费 Fabric 客户,同比增长超过 50%。我们正在拉近 Foundry 与 Fabric 的距离,以便客户能够紧挨着数据构建自己的智能体。随着企业连接并在实时运营数据、分析数据和非结构化数据之上运行智能体,目前已有超过 19,000 家客户同时使用 Foundry 和 Fabric。客户还在快速部署我们针对 AI 优化的数据库,包括 PostgreSQL、SQL DB、Hyperscale、Cosmos DB,为智能体提供快速、安全的数据和上下文访问。PostgreSQL 增速连续第四个季度加快,同时使用 Foundry 的 PostgreSQL 客户数量同比增速加快至 90%。
P01411:59
We also have one of the most important databases for any enterprise, which is the knowledge underneath Microsoft 365, spanning people, their relationships, documents, emails, meetings, chats, projects, and other artifacts. Work IQ makes this context available to every agentic workload. With Microsoft IQ, we are bringing together Work IQ, Fabric IQ, and Foundry IQ as a unified context for agentic systems. Nearly 60,000 customers are accessing context across Microsoft IQ, up 25% quarter-over-quarter. As enterprises deploy more agents, they also need to govern them at scale. With Agent 365, we provide a platform for AI observability, enabling customers to manage, secure, and optimize the performance and cost of their agents. Over 50 million agents are now in the registry, up over 30% quarter-over-quarter. Finally, as agents gain greater access to enterprise data and systems, security becomes even more critical.
我们还拥有对任何企业客户而言都最重要的数据库之一,那就是 Microsoft 365 底层的知识库,涵盖人员、人际关系、文档、电子邮件、会议、聊天、项目及其他工作成果。Work IQ 使这一上下文能够供每一个智能体工作负载调用。借助 Microsoft IQ,我们将 Work IQ、Fabric IQ 和 Foundry IQ 整合为面向智能体系统的统一上下文。目前有近 60,000 家客户正在跨 Microsoft IQ 调用上下文,环比增长 25%。随着企业部署越来越多的智能体,他们还需要对智能体进行大规模治理。通过 Agent 365,我们提供了一个 AI 可观测性平台,使客户能够管理、保护并优化其智能体的性能与成本。目前注册表中的智能体数量已超过 5,000 万个,环比增长超过 30%。最后,随着智能体获得对企业数据和系统更大的访问权限,安全变得愈发关键。
P01513:05
Our approach is to separate intelligence from authority, enforcing identity, permissions, monitoring, and containment outside the model itself. Last week, we expanded Perception with new capabilities to help customers secure and contain agentic insiders, including expanded agent discovery across local and cloud environments, dynamic permissions that enforce least privileged access for each task, and continuous risk assessment. We also introduced teams of guardian agents that continuously monitor agent activity to help prevent unsafe actions before they occur. We are seeing encouraging feedback on Perception overall from preview customers, including KPMG, Nationwide Building Society, Northern Trust, Celonis. More broadly, we are helping customers secure and govern AI use across the enterprise. Customers have used Microsoft Purview to audit over 7.6 billion agent activities to date, up 5x quarter-over-quarter. Underlying everything I have talked about so far is our infrastructure.
我们的方法是将智能与权限分离,在模型外部强制执行身份认证、权限管理、监控和隔离控制。上周,我们扩展了 Perception 的新功能,帮助客户保护和隔离内部智能体风险,包括跨本地和云环境的扩展智能体发现、针对每项任务强制执行最小权限访问的动态权限管理,以及持续风险评估。我们还推出了守护智能体(guardian agents)团队,持续监控智能体活动,在发生不安全行为之前予以阻止。我们从预览版客户那里收到了对 Perception 总体上令人鼓舞的反馈,这些客户包括 KPMG、Nationwide Building Society、Northern Trust、Celonis。更广泛地说,我们正在帮助客户保护和治理整个企业范围内的 AI 使用。迄今为止,客户已使用 Microsoft Purview 审计了超过 76 亿次智能体活动,环比增长 5 倍。支撑我到目前为止所谈到的一切的,是我们的基础设施。
P01614:12
We are building against a growing book of business with a fungible fleet that allows us to dynamically allocate capacity to the highest value opportunities across compute, data, Foundry, and Copilot. Accelerating demand led to us adding 24 new data centers across five continents this quarter. We are bringing capacity online faster, reducing dock-to-live times by about 20% quarter-over-quarter for new GB300s in our biggest regions, which make up the majority of the GPU deployments. At the same time, we continue to get more from the infrastructure we already have by optimizing across the data center design, silicon systems, software, and models. For example, we increased the throughput for Copilot workloads by over 50% quarter-over-quarter. We continue to scale our fleet with the latest innovations from NVIDIA, AMD, alongside our own Maia systems.
我们正依托不断增长的订单簿进行建设,打造可灵活调配(fungible)的算力集群,使我们能够跨算力、数据、Foundry 和 Copilot 将算力容量动态分配给最高价值的机会。不断加速的需求促使我们在本季度横跨五大洲新增了 24 座数据中心。我们正在加快产能上线速度,在我们最大的区域中,占 GPU 部署大多数的新款 GB300 从到货卸货到通电上线(dock-to-live)的时间环比缩短了约 20%。与此同时,我们通过跨数据中心设计、芯片系统、软件和模型的全方位优化,继续从现有基础设施中挖掘更多潜力。例如,我们将 Copilot 工作负载的吞吐量环比提升了 50% 以上。我们继续采用来自 NVIDIA、AMD 的最新创新产品以及我们自研的 Maia 系统来扩展我们的算力集群。
P01715:09
We have docked our first NVIDIA Vera Rubin GPUs and are very excited about it. Maia 200 is already delivering up to 1.7 times more tokens per watt across the AI experiences in Teams and Copilot, and Maia 300 will drive further gains, delivering 40% more tokens per watt compared to the leading GPU-based systems. Our growth extends beyond GPUs. We continue to see strong adoption of our cloud-native Cobalt CPUs, improving price performance for general purpose cloud workloads. All-up Azure growth was broad-based across both enterprises and small and medium business segments and spanning both core cloud services and AI infrastructure. Finally, let me turn to Devices and Consumer. In Windows, we are executing on our vision to bring hybrid intelligence to every desk and every home, making every PC a secure agent box.
我们已经接收了首批 NVIDIA Vera Rubin GPU,并对此感到非常振奋。在 Teams 和 Copilot 的各项 AI 体验中,Maia 200 的每瓦 token 产出已提升最高达 1.7 倍;而 Maia 300 将带来进一步提升,与领先的基于 GPU 的系统相比,每瓦 token 产出将高出 40%。我们的增长不仅局限于 GPU。我们继续看到云原生 Cobalt CPU 获得强劲采用,提升了通用云工作负载的性价比。整体而言,Azure 的增长在大中型企业客户和中小企业(SMB)客户中均广泛展开,并涵盖核心云服务与 AI 基础设施。最后,让我谈谈设备与消费业务(Devices and Consumer)。在 Windows 领域,我们正在执行将混合智能带到每一张办公桌和每一个家庭的愿景,让每一台 PC 都成为安全的智能体终端(agent box)。
P01816:04
As more capable models run locally, we see an opportunity to make it more intelligence effectively unmetered. We are working with the broader hardware ecosystem to bring these capabilities to a new generation of PCs across AMD's Ryzen AI 400 Series, Intel Core Ultra Series 3, Qualcomm Snapdragon X2 Series. Earlier this month, we also announced new PCs powered by NVIDIA's RTX Spark and DGX Station for Windows. With these new devices, you can run last year's Frontier models on your laptop and last quarter's model at your desk. We are bringing together Windows and Agent 365 so agents can work with secure boundaries on device. We introduced Microsoft Execution Containers, a policy-driven execution layer that governs and contains agents across Windows and other platforms integrated with Agent 365 for governance and observability.
随着能力更强的模型在本地运行,我们看到了让更多智能实际上实现不限量使用(unmetered)的机会。我们正与更广泛的硬件生态系统合作,将这些能力引入涵盖 AMD Ryzen AI 400 系列、Intel Core Ultra Series 3、Qualcomm Snapdragon X2 系列的新一代 PC。本月早些时候,我们还发布了搭载 NVIDIA RTX Spark 和面向 Windows 的 DGX Station 的新款 PC。借助这些新设备,您可以在笔记本电脑上运行去年的前沿模型,在台式机上运行上季度的模型。我们正在将 Windows 与 Agent 365 结合起来,使智能体能够在设备端的安全边界内工作。我们推出了 Microsoft Execution Containers(MXC),这是一个策略驱动的执行层,与 Agent 365 集成以实现治理和可观测性,跨 Windows 和其他平台对智能体进行治理和隔离。
P01917:00
Agents like OpenAI Codex, Anthropic Claude Code, Meta Muse are adopting MXC, and customers like Meta are starting to deploy it across their enterprise environments. In search and advertising, Bing and Edge once again took share. In LinkedIn, engagement continues to deepen across our more than 1.4 billion members, with time spent viewing content in the feed up 15% year-over-year. Finally, in gaming, we remain focused on building great games and reaching players wherever they choose to play across console, PC, mobile, and cloud. Minecraft delivered a record quarter, reaching all-time highs in both engagement and revenue, while World of Warcraft had its largest beta in franchise history.
诸如 OpenAI Codex、Anthropic Claude Code、Meta Muse 等智能体正在采用 MXC,而像 Meta 这样的客户也开始在其企业环境中进行部署。在搜索和广告业务方面,Bing 和 Edge 再次提升了市场份额。在 LinkedIn 方面,我们超过 14 亿会员的互动度持续加深,信息流内容浏览时长同比增长 15%。最后在游戏业务方面,我们依然专注于打造优秀的游戏,并在主机、PC、移动端和云端等玩家选择游玩的任何地方触达他们。《我的世界》(Minecraft)创下了季度纪录,互动度和营收双双达到历史最高水平,而《魔兽世界》(World of Warcraft)则迎来了该系列历史上规模最大的测试版(beta)。
P02017:46
We enter the holiday season with one of our strongest first and third-party lineups in years, including Modern Warfare 4, which launched last week to the best reviews for a Call of Duty game in more than a decade, and Grand Theft Auto 6, which is coming to Xbox next month. In closing, based on the demand we see, the strength of our products, and the efficiency we are driving across the stack, I've never been more confident in the long-term returns for our investments. With that, let me turn it over to Amy.
我们正带着多年来最强大的第一方和第三方游戏阵容之一进入假日季,其中包括上周发售并获得十多年来《使命召唤》(Call of Duty)系列最佳评测的《现代战争 4》(Modern Warfare 4),以及将于下个月登陆 Xbox 的《侠盗猎车手 6》(Grand Theft Auto 6)。最后总结一下,基于我们所看到的需求、我们产品的实力,以及我们在整个技术栈中推动的效率提升,我对我们投资的长期回报比以往任何时候都更有信心。下面,我把电话交给 Amy。
P02118:14
Amy HoodCFO
Thank you, Satya, and good afternoon everyone. Our results exceeded expectations across revenue, operating income, and earnings per share, driven by strong demand across the Microsoft Cloud. This quarter, revenue was $92.3 billion, up 19%. Gross margin dollars increased 17%, and gross margin percentage was 68%. Operating income increased 21% and 22% in constant currency. Earnings per share was $4.89, an increase of 18% and 19% in constant currency when adjusted for the impact per our investment in OpenAI. FX was roughly in line with guidance. Operating expenses increased 6%, driven by continued investments in R&D compute capacity and talent. Operating margins increased slightly year-over-year to 50%, driven by strong revenue growth, platform efficiency gains, and focused investments across our portfolio, partially offset by sales mix shift to Azure.
谢谢你,Satya,大家下午好。在 Microsoft Cloud 强劲需求的推动下,我们本季度的营收、营业利润和每股收益均超出预期。本季度营收为 923 亿美元,增长 19%。毛利额增长 17%,毛利率为 68%。营业利润增长 21%,按固定汇率计算增长 22%。剔除我们对 OpenAI 投资的影响后,每股收益为 4.89 美元,增长 18%,按固定汇率计算增长 19%。汇率影响与指引基本一致。营业费用增长 6%,主要由对研发算力容量和人才的持续投入所推动。营业利润率同比微升至 50%,得益于强劲的营收增长、平台效率提升以及我们在整个业务组合中的聚焦投入,但被销售结构向 Azure 倾斜所部分抵消。
P02219:12
When adjusted for the impact for our investments in OpenAI, other income and expense was negative $234 million, slightly lower than expected. Capital expenditures were $45.2 billion, as some 3P capacity deliveries we expected in Q1 were delayed. Roughly three quarters of our CapEx was for short-lived assets, primarily CPUs and GPUs, including higher memory and storage costs, as we continue to invest in the infrastructure required for our customers to build and scale AI applications. The remaining spend was for long-lived assets. This quarter, finance leases were $7.4 billion. As a reminder, we recognize the full principal value of finance leases in CapEx at the time of lease commencement. Cash paid for PP&E was $39.4 billion. Cash flow from operations was $58 billion, up 29%, driven by strong cloud billings and collections. Free cash flow was $18.6 billion, reflecting higher capital expenditures.
剔除我们对 OpenAI 投资的影响后,其他收入和支出为负 2.34 亿美元,略低于预期。资本开支为 452 亿美元,因为我们原预计在第一季度交付的部分第三方(3P)算力容量出现了延迟。我们的资本开支中约有 3/4 用于短周期资产,主要是 CPU 和 GPU(包括更高的内存和存储成本),以继续投资于客户构建和扩展 AI 应用所需的基础设施。其余支出用于长周期资产。本季度融资租赁为 74 亿美元。提醒大家,我们在租赁开始时将融资租赁的全部本金价值计入资本开支。购建不动产、厂房及设备(PP&E)支付的现金为 394 亿美元。经营活动产生的现金流为 580 亿美元,增长 29%,由强劲的云业务账单和回款推动。自由现金流为 186 亿美元,反映了较高的资本开支。
被引用:↩ 基本面档案 · 主要风险 · 算力投多了,需求跟不上 ×2↩ 基本面档案 · 主要风险 · 零部件涨价与第三方算力交付延迟↩ 基本面档案 · 管理层与资本配置↩ FY2027Q1 季度复盘 · 结论摘要↩ FY2027Q1 季度复盘 · 业绩与指引↩ FY2027Q1 季度复盘 · 财务拆解 · 资本开支、回报与现金流↩ FY2027Q1 季度复盘 · 当季异动 ×2↩ FY2027Q1 季度复盘 · 长期趋势异常↩ FY2027Q1 季度复盘 · 电话会要点 · 风险与逆风↩ FY2027Q1 季度复盘 · 叙事 vs 报表 ×2↩ FY2027Q1 电话会解析 · 核心判断↩ FY2027Q1 电话会解析 · 管理层发言解析 · Amy Hood|CFO↩ FY2027Q1 电话会解析 · 措辞与语气信号↩ 指引与语气 · 指引演变 · 资本开支与自由现金流↩ 指引与语气 · 指引可信度↩ 云三强一年砸 6,000 亿建算力:用同一把尺子量,谁的投入回本最快? · 多方原话交锋与验真标尺 · 对质二:自研芯片能省多少?——结论:省钱的说法都来自卖方或自用方,可核对的只有亚马逊的“客户省了 20 亿美元”↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 底层逻辑与关键账本 · 表二:上游芯片(AVGO/NVDA)交叉对账、单吉瓦(GW)算力物理经济账与 2027 折旧/净现金底牌↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 核心争议拆解 · 争议一:联立上游博通/英伟达账本与滞后本金,谁的真实算力增量 ROIC 最高?——结论:谷歌(31.5%)靠半价 TPU 夺冠,亚马逊(27.1%)居次,微软(18.2%)垫底↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 多方原话交锋与验真标尺 · 对质二:自研芯片能不能扛住硬件涨价与折旧?——结论:博通实锤“定制 XPU 成本不到 GPU 一半”,谷歌与亚马逊享自研红利,微软硬扛存储与 GPU 涨价↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 外部一手资料与产业链引用记录
P02320:09
Finally, we returned $10.2 billion to shareholders through dividends and share repurchases. Now to our segment results, reported under the updated segment structure announced in September. Revenue from Agents and Infra was $76.8 billion and grew 25%, reflecting strength across the connected layers of our platform. Commercial bookings decreased 12% and 11% in constant currency, driven by the impact from large Azure commitments in the prior year, partially offset by healthy growth in our commercial sales motions, including a large Azure commitment this quarter. Commercial remaining performance obligation grew 73% to $677 billion, with a smaller sequential decline relative to historical seasonality due to the large Azure commitment this quarter. Our RPO has a weighted average duration of 2.3 years, and roughly 30% will be recognized in revenue in the next 12 months, up 29% year-over-year. The remaining portion, recognized beyond the next 12 months, increased 98%.
最后,我们通过股息和股票回购向股东返还了 102 亿美元。现在来看按我们在 9 月份宣布的更新后分部架构报告的分部业绩。智能体与基础设施(Agents and Infra)分部营收为 768 亿美元,增长 25%,反映了我们平台各个互联层级的强劲表现。商业新签订单减少 12%,按固定汇率计算减少 11%,主因去年同期有大额 Azure 承诺订单的高基数影响,但被我们商业销售活动的健康增长(包括本季度签署的一项大额 Azure 承诺订单)所部分抵消。商业剩余履约义务(RPO)增长 73%,达到 6,770 亿美元;由于本季度签署了大额 Azure 承诺订单,其环比回落幅度小于历史季节性水平。我们的 RPO 加权平均期限为 2.3 年,其中约 30% 将在未来 12 个月内确认为营收,该部分同比增长 29%。将在未来 12 个月之后确认的剩余部分增长了 98%。
被引用:↩ 基本面档案 · 投资要点↩ 基本面档案 · 主要风险 · 折旧年限延长与分部重组掩盖成本压力↩ 基本面档案 · 主要风险 · 在手订单高度集中在 OpenAI↩ 基本面档案 · 商业模式与收入结构↩ 基本面档案 · 财务画像↩ FY2027Q1 季度复盘 · 结论摘要 ×2↩ FY2027Q1 季度复盘 · 财务拆解 · 前瞻指标 ×2↩ FY2027Q1 季度复盘 · 财务拆解 · 资本开支、回报与现金流↩ FY2027Q1 季度复盘 · 分部表现↩ FY2027Q1 季度复盘 · 电话会要点 · 业绩要点↩ FY2027Q1 季度复盘 · 管理层口径变化↩ FY2027Q1 季度复盘 · 对投资逻辑的影响↩ 估值 · 结论与需要跟踪的信号↩ FY2027Q1 电话会解析 · 管理层发言解析 · Amy Hood|CFO↩ FY2027Q1 电话会解析 · 措辞与语气信号↩ FY2027Q1 电话会解析 · 对投资判断的含义↩ 指引与语气 · 语气变化↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 核心争议拆解 · 争议二:剥离 OpenAI 与 Anthropic 关联长单后,1.83 万亿 RPO 谁的成色最硬?——结论:亚马逊 81% 原生企业云最稳,谷歌借甲骨文/黑石外溢,微软遭 OpenAI 自研芯片反噬↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 多方原话交锋与验真标尺 · 未来 2–4 个季度检验上述推演模型的四大定量标尺↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 外部一手资料与产业链引用记录
P02421:13
Now to Microsoft Cloud. Revenue was $63.9 billion, and growth accelerated to 30% and 31% in constant currency, with sequential dollars added nearly doubling year-over-year, reflecting strong demand across Azure and M365 Commercial Cloud. Azure revenue was ahead of expectations and increased 48%, even with the 3P capacity delays noted earlier, driven by Foundry and improved CPU monetization. Foundry revenue more than tripled year-over-year, with upside driven by efficiency gains across our GPU fleet that allowed us to allocate additional capacity to customers, as well as higher revenue per token that we benefited from in the quarter. Across our CPU fleet, engineering work enabled us to identify and monetize underutilized capacity this quarter, helping us serve more of the growing demand with our existing capacity.
现在来看 Microsoft Cloud。营收为 639 亿美元,增速加快至 30%,按固定汇率计算增长 31%,环比新增美元营收接近去年同期的 2 倍,反映了 Azure 和 M365 商业云的强劲需求。尽管存在前面提到的第三方(3P)算力容量交付延迟,Azure 营收依然超出预期,增长 48%,主要由 Foundry 和 CPU 变现能力改善所推动。Foundry 营收同比增长超过 2 倍(即增长至原来的 3 倍以上),其超预期表现得益于我们 GPU 集群的效率提升(使我们能够向客户分配更多算力容量),以及我们在本季度受益于更高的每 token 营收。在我们的 CPU 集群中,工程优化工作使我们能够在本季度识别并变现未充分利用的容量,帮助我们用现有容量满足了更多不断增长的需求。
被引用:↩ 基本面档案 · 投资要点↩ 基本面档案 · 主要风险 · 在手订单高度集中在 OpenAI↩ FY2027Q1 季度复盘 · 结论摘要 ×2↩ FY2027Q1 季度复盘 · 当季异动 ×3↩ FY2027Q1 季度复盘 · 分部表现↩ FY2027Q1 季度复盘 · 电话会要点 · 业绩要点↩ FY2027Q1 季度复盘 · 电话会要点 · 分部与业务动态↩ FY2027Q1 季度复盘 · 对投资逻辑的影响↩ 估值 · 方法选择↩ 估值 · 两阶段 DCF↩ FY2027Q1 电话会解析 · 核心判断 ×2↩ FY2027Q1 电话会解析 · 管理层发言解析 · Amy Hood|CFO ×2↩ FY2027Q1 电话会解析 · 措辞与语气信号↩ FY2027Q1 电话会解析 · 对投资判断的含义↩ 指引与语气 · 核心结论↩ 指引与语气 · 指引演变 · Azure 增速与新报告分部指引↩ 指引与语气 · 语气变化↩ 指引与语气 · 指引可信度↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 底层逻辑与关键账本 · 表二:上游芯片(AVGO/NVDA)交叉对账、单吉瓦(GW)算力物理经济账与 2027 折旧/净现金底牌↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 核心争议拆解 · 争议一:联立上游博通/英伟达账本与滞后本金,谁的真实算力增量 ROIC 最高?——结论:谷歌(31.5%)靠半价 TPU 夺冠,亚马逊(27.1%)居次,微软(18.2%)垫底↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 核心争议拆解 · 争议三:物理电力(GW)瓶颈与 2027 折旧瀑布——新增 210 亿折旧砸表,谁最抗跌?——结论:亚马逊 960MW 核电现成且折旧仅增 26.4%,谷歌迎 Q4 阵痛,微软遭 3P 延期并买断 6 万员工↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 多方原话交锋与验真标尺 · 对质一:算力到底有没有过剩?——结论:上下游五家掌门人同台证实“土地与电力(LPS)”才是唯一瓶颈,亚马逊自建现成核电最顺,谷歌与微软受困机房断档
P02522:08
The timing of engineering efficiencies like these, as well as 3P GPU lease deliveries, our own capacity build-outs, and ARPU changes from model mix can create quarterly variability in the year-over-year growth rate. Microsoft 365 Commercial Cloud revenue increased 18% and 19% in constant currency when adjusted for the prior year comparable that benefited from one point of in-period revenue recognition. On a reported basis, revenue growth was 17% and 18% in constant currency. Results were ahead of expectations, driven by stronger GitHub Copilot adoption and usage, partially offset by weaker sales execution in our Microsoft 365 E3 and standalone SKUs. We continue to evolve our sales motions to balance those more traditional SKU per seat rhythms with the newer premium E7, Microsoft 365 Copilot, and usage-based productivity offerings. Year-over-year growth was driven by both ARPU and seats.
诸如这类工程效率提升的时间节点,以及第三方 GPU 租赁交付、我们自身算力容量建设,还有模型组合变化带来的每用户平均收入(ARPU)变动,都可能造成同比增速出现季度波动。剔除去年同期受益于 1 个百分点的当期收入确认因素后,Microsoft 365 商业云营收增长 18%,按固定汇率计算增长 19%。按报告口径计算,营收增长 17%,按固定汇率计算增长 18%。业绩超出预期,主要由更强劲的 GitHub Copilot 采用率和使用量推动,但被我们在 Microsoft 365 E3 及独立 SKU 上的销售执行走弱所部分抵消。我们正继续演进销售运作模式,以平衡传统按席位销售 SKU 的节奏与较新的高端 E7、Microsoft 365 Copilot 及按使用量计费的生产力产品。同比增长由 ARPU 和席位增长共同驱动。
P02623:06
ARPU growth was led by our premium seat-based offerings, including Microsoft 365 Copilot, E5, and E7, which has already reached millions of paid seats, with additional contribution from usage-based offerings, primarily GitHub Copilot. Copilot revenue growth accelerated quarter-over-quarter with continued adoption across Microsoft 365, GitHub, and security. Paid Microsoft 365 commercial seats grew 5%, with some impact from the weaker sales execution noted earlier. Growth was driven by install-based expansion across all customer segments, though primarily in our SMB and frontline worker offerings. Microsoft 365 Consumer Cloud revenue increased 17% and 16% in constant currency, down sequentially as we begin to lap the benefit from the price increase in the prior year.
ARPU 增长主要由我们按席位计费的高端产品引领,包括 Microsoft 365 Copilot、E5 以及付费席位已达数百万个的 E7,此外按使用量计费的产品(主要是 GitHub Copilot)也做出了额外贡献。随着 Microsoft 365、GitHub 和安全产品领域的采用率持续提升,Copilot 营收增速实现环比加快。付费 Microsoft 365 商业席位增长 5%,在一定程度上受到了前面提到的销售执行走弱的影响。增长主要来自各个客户群体的装机量扩张,但主要集中在我们的中小企业(SMB)和一线员工产品。Microsoft 365 个人消费云营收增长 17%,按固定汇率计算增长 16%,增速环比回落,原因是我们开始进入去年同期提价红利的高基数期。
P02723:55
Productivity and server licensing revenue decreased 3% and 2% in constant currency, primarily driven by a decrease in transactional purchasing as we lap the benefit from product launches in the prior year, partially offset by a greater mix of contracts that carry higher in-period revenue recognition. Industry Solutions cloud revenue increased 10%, with growth in Dynamics 365 and LinkedIn Talent Solutions, though booking trends continued to moderate. In Frontier and Support Services, revenue increased 4% and 5% in constant currency, driven by support. Microsoft Cloud gross margin percentage declined year over year to 66%, driven by sales mix shift to Azure, partially offset by product-level margin improvements primarily in Azure. For this segment, gross margin dollars increased 20% and 21% in constant currency. Operating expenses increased 10%, driven by the R&D investments noted earlier.
生产力及服务器许可(Productivity and server licensing)营收下降 3%,按固定汇率计算下降 2%,主要是由于我们进入去年同期产品发布红利的高基数期,导致交易型采购减少,但被当期收入确认比例较高的合同占比提升所部分抵消。行业解决方案云(Industry Solutions cloud)营收增长 10%,Dynamics 365 和 LinkedIn 人才解决方案实现增长,不过新签订单趋势继续放缓。前沿及支持服务(Frontier and Support Services)营收增长 4%,按固定汇率计算增长 5%,主要由支持服务推动。Microsoft Cloud 毛利率同比下降至 66%,主因销售结构向 Azure 倾斜,但被产品层面的利润率改善(主要在 Azure)所部分抵消。该分部毛利额增长 20%,按固定汇率计算增长 21%。营业费用增长 10%,由前面提到的研发投入所驱动。
P02824:50
Operating income grew 24% and 25% in constant currency, and operating margins decreased slightly year over year to 53%, as strong revenue growth, platform efficiency gains, and focused investments across our portfolio were more than offset by sales mix shift to Azure. Now to Devices and Consumer. Revenue was $15.5 billion and declined 3%. Search and advertising revenue ex TAC increased 12% and was ahead of expectations, driven by higher volume and rate across LinkedIn, Edge, and Bing. Xbox revenue decreased 2%, and Xbox content and services revenue decreased 2% and 1% in constant currency, driven by declines in third-party content and Xbox Game Pass, partially offset by growth in first-party content. Windows OEM and Devices revenue decreased 22%.
营业利润增长 24%,按固定汇率计算增长 25%,营业利润率同比微降至 53%,因为强劲的营收增长、平台效率提升以及我们在整个业务组合中的聚焦投入,被销售结构向 Azure 倾斜的影响所抵消并超出。现在来看设备与消费业务(Devices and Consumer)。营收为 155 亿美元,下降 3%。剔除流量获取成本(TAC)后的搜索和广告营收增长 12%,超出预期,主要由 LinkedIn、Edge 和 Bing 的流量及费率提升所推动。Xbox 营收下降 2%,Xbox 内容和服务营收下降 2%,按固定汇率计算下降 1%,主因第三方内容和 Xbox Game Pass 收入下滑,但被第一方内容的增长所部分抵消。Windows OEM 和设备营收下降 22%。
P02925:42
Windows OEM revenue was below expectations and decreased 27% and 28% in constant currency, driven by the Windows 10 end of support demand in the prior year, inventory drawdowns by OEM and channel partners, and weaker PC market demand. Inventory levels remain elevated. Segment gross margin dollars were relatively unchanged year over year, and operating expenses decreased 3%, driven by Xbox, partially offset by the continued investments in R&D noted earlier. Operating income increased 2% and 3% in constant currency, and operating margins increased year over year to 35%, driven by lower amortization of intangible assets from the Activision acquisition, partially offset by the impact from a lower mix of Windows OEM revenue. Now, moving to the outlook for our second quarter, which, unless specifically noted otherwise, is on a U.S. dollar basis.
Windows OEM 营收低于预期,下降 27%,按固定汇率计算下降 28%,主要受去年同期 Windows 10 停止支持带来的抢装需求高基数、OEM 及渠道合作伙伴去库存,以及 PC 市场需求疲软的影响。库存水平依然偏高。分部毛利额同比基本持平,营业费用下降 3%,主要由 Xbox 费用减少所带动,但被前面提到的持续研发投入所部分抵消。营业利润增长 2%,按固定汇率计算增长 3%,营业利润率同比上升至 35%,主要得益于收购 Activision 产生的无形资产摊销减少,但被 Windows OEM 营收占比下降的影响所部分抵消。现在谈谈我们对第二季度的展望,除非另有明确说明,以下均以美元口径为基础。
P03026:35
Based on current rates, we expect FX to have no meaningful impact on total revenue, COGS, or operating expense growth, or on revenue growth in either segment. Starting with segment guidance. We expect revenue from Agents and Infra of $80.1 billion to $80.7 billion, or growth of 24% to 25%. In commercial bookings, we expect healthy growth in our commercial sales motions, though results will be impacted by the significant Azure commitments signed in the prior year. Timing related to significant Azure commitments like these will result in material volatility in bookings, making quarterly growth rates less indicative of underlying sales execution. In Azure, we expect revenue growth of 49% to 50% in constant currency, with continued efficiency gains across our CPU and GPU fleet, helping to offset some 3P GPU as-a-service contracts that have been delayed to H2. Customer demand continues to exceed available supply.
基于当前汇率,我们预计汇率对总营收、营业成本(COGS)或营业费用增速,以及对任一分部的营收增速均不会产生实质性影响。首先来看分部指引。我们预计智能体与基础设施(Agents and Infra)分部营收为 801 亿至 807 亿美元,即增长 24% 至 25%。在商业新签订单方面,我们预计商业销售活动将保持健康增长,但业绩将受到去年同期签署的大额 Azure 承诺订单高基数的影响。与这类大额 Azure 承诺订单相关的时间节点会导致新签订单出现较大波动,使得季度增长率难以准确反映底层销售执行情况。在 Azure 方面,我们预计按固定汇率计算的营收增速为 49% 至 50%,我们 CPU 和 GPU 集群的持续效率提升将有助于抵消部分推迟到下半年(H2)交付的第三方(3P)GPU 即服务(GPU as-a-service)合同影响。客户需求继续超过可用供给。
被引用:↩ 基本面档案 · 投资要点↩ FY2027Q1 季度复盘 · 结论摘要↩ FY2027Q1 季度复盘 · 业绩与指引↩ FY2027Q1 季度复盘 · 电话会要点 · 指引与展望↩ FY2027Q1 季度复盘 · 电话会要点 · 风险与逆风↩ FY2027Q1 季度复盘 · 管理层口径变化↩ FY2027Q1 季度复盘 · 对投资逻辑的影响↩ 估值 · 两阶段 DCF↩ 估值 · 结论与需要跟踪的信号↩ FY2027Q1 电话会解析 · 核心判断↩ FY2027Q1 电话会解析 · 管理层发言解析 · Amy Hood|CFO ×2↩ FY2027Q1 电话会解析 · 措辞与语气信号 ×2↩ FY2027Q1 电话会解析 · 对投资判断的含义↩ 指引与语气 · 核心结论↩ 指引与语气 · 指引演变 · Azure 增速与新报告分部指引 ×2↩ 指引与语气 · 指引演变 · 算力供给约束与元器件涨价 ×2↩ 指引与语气 · 语气变化↩ 指引与语气 · 需要跟踪的信号↩ 云三强一年砸 6,000 亿建算力:用同一把尺子量,谁的投入回本最快? · 多方原话交锋与验真标尺 · 对质一:算力是不是过剩?——结论:三家都说供不应求,瓶颈在机房和电力,谷歌、微软已在为第三方算力付出代价↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 多方原话交锋与验真标尺 · 对质一:算力到底有没有过剩?——结论:上下游五家掌门人同台证实“土地与电力(LPS)”才是唯一瓶颈,亚马逊自建现成核电最顺,谷歌与微软受困机房断档
P03127:35
Looking beyond Q2, year-over-year growth will continue to reflect the timing and scale of engineering efficiencies delivered in the quarter and new capacity adds, as well as a strong prior-year comparable that included accelerating growth in the second half. In M365 Commercial Cloud, we expect growth of approximately 19% in constant currency, with FX expected to reduce reported growth by less than a point. We expect continued momentum across our premium per-seat offerings and usage-based offerings, along with some improvement in execution across E3 and our standalone SKUs. Growth will be driven primarily by ARPU, with additional contribution from seats, and we continue to expect revenue growth to accelerate through the year. M365 Consumer Cloud revenue should grow in the low teens, down sequentially as we lap the price impact noted earlier.
展望第二季度之后,同比增速将继续反映各季度交付的工程效率提升及新增算力容量的时间节点与规模,以及去年同期的高基数(去年下半年包含了加速增长)。在 M365 商业云方面,我们预计按固定汇率计算增长约 19%,汇率预计将使报告口径增速减少不到 1 个百分点。我们预计按席位计费的高端产品和按使用量计费的产品将继续保持良好势头,同时 E3 和独立 SKU 的销售执行也将有所改善。增长将主要由 ARPU 驱动,席位增长提供额外贡献,而且我们继续预计营收增速将在整个财年内逐步加快。M365 个人消费云营收预计将保持十几个百分点偏低区间(low teens)的增长,增速环比回落,原因是我们进入了前面提到的提价影响基数期。
P03228:24
Productivity and Server Licensing revenue should decline in the mid to high single digits, down sequentially due to a lower expected mix of contracts that carry higher in-period revenue recognition. Quarterly growth can vary materially based on contract mix, product launch timing, and other transactional purchasing trends. In Industry Solutions Cloud, we expect revenue growth to be in the mid to high single digits, with continued impact from the bookings trends noted earlier. In Frontier and Support Services, we expect revenue to grow in the low to mid single digits. Microsoft Cloud gross margin percentage should be roughly 65%, down year over year, as continued improvement in product-level margins is more than offset by sales mix shift to Azure. In Devices and Consumer, we expect revenue to be $15.9 billion to $16.4 billion.
生产力及服务器许可营收预计将出现中至高个位数百分比下滑,且环比回落,原因是预计当期收入确认比例较高的合同占比将下降。季度增长率可能因合同组合、产品发布时间节点及其他交易型采购趋势而出现显著波动。在行业解决方案云方面,我们预计营收增速将处于中至高个位数百分比区间,继续受到前面提到的新签订单趋势影响。在前沿及支持服务方面,我们预计营收将实现低至中个位数百分比增长。Microsoft Cloud 毛利率预计约为 65%,同比下降,因为产品层面的持续利润率改善被销售结构向 Azure 倾斜的影响所抵消并超出。在设备与消费业务分部,我们预计营收为 159 亿至 164 亿美元。
P03329:13
Search and advertising revenue ex TAC growth should be in the low double digits, driven by consistent trends in rate and volume, with overall search and advertising revenue expected to grow at a similar rate. In Xbox Content and Services, we expect revenue growth to be in the mid to high single digits up sequentially, driven by the timing of content launches across both third and first party. With content launch patterns through the year, we expect growth to be the strongest in the second quarter, with some deceleration in Q3 and further moderation in Q4. Hardware revenue in Q2 should decline year over year. Windows OEM and Devices revenue should decline in the mid-30s. Growth will continue to be impacted by elevated inventory levels, PC market demand, and a prior-year comparable that benefited from Windows 10 end of support.
剔除流量获取成本(TAC)后的搜索和广告营收增速预计将处于十几个百分点偏低区间(low double digits),受持续稳定的费率和流量趋势驱动,整体搜索和广告营收预计将以相近速率增长。在 Xbox 内容和服务方面,我们预计营收将实现中至高个位数百分比增长,并实现环比上升,主要受第三方和第一方游戏内容发布时间节点的推动。根据全年的内容发布节奏,我们预计第二季度的增速将最为强劲,第三季度将有所放缓,第四季度则进一步趋缓。第二季度硬件营收预计将同比下降。Windows OEM 和设备营收预计将下降 30% 多(mid-30s)。增长将继续受到偏高的库存水平、PC 市场需求以及去年同期受益于 Windows 10 停止支持的高基数影响。
P03429:59
As in prior quarters, the range of potential outcomes remains wider than normal. We expect these trends to continue through the rest of the fiscal year. Therefore, at a total company level, revenue should be between $96 billion and $97.1 billion, or growth of 18%-19%. We expect COGS of $32.7 billion to $32.9 billion, or growth of 26%-27%, and operating expense of $18.5 billion to $18.6 billion, or growth of 9%, driven by continued investment in R&D, compute capacity, and talent. Our cost guidance across both COGS and OpEx includes an estimate for the recently announced employee voluntary exit offer. Operating margins should be down slightly year over year.
与前几个季度一样,潜在结果的波动区间依然比正常水平更宽。我们预计这些趋势将在本财年剩余时间内持续。因此,在公司整体层面,营收预计将在 960 亿至 971 亿美元之间,即增长 18% 至 19%。我们预计营业成本(COGS)为 327 亿至 329 亿美元,即增长 26% 至 27%;营业费用为 185 亿至 186 亿美元,即增长 9%,主要由对研发、算力容量和人才的持续投入所驱动。我们对营业成本和营业费用的成本指引包含了一项针对近期宣布的员工自愿离职计划的估算费用。营业利润率预计将同比微降。
P03530:44
Excluding any impact from our investments in OpenAI, other income expense is expected to be roughly negative $300 million, as interest income will be more than offset by interest expense, which includes the interest payments related to data center finance leases. We expect our Q2 effective tax rate to be approximately 20%. Next, capital expenditures. In Q2, we expect CapEx spend will be over $50 billion. Therefore, for the calendar year, spend should be approximately $170 billion due to the 3P capacity delays noted earlier. In the second half of the fiscal year, we currently expect CapEx spend to accelerate primarily from CPUs, inclusive of higher memory and storage costs, and GPUs, as well as the 3P capacity deliveries that shifted to H2.
剔除我们对 OpenAI 投资的任何影响后,其他收入和支出预计约为负 3 亿美元,因为利息收入将被利息支出(包括与数据中心融资租赁相关的利息支付)所抵消并超出。我们预计第二季度有效税率约为 20%。接下来是资本开支。在第二季度,我们预计资本开支将超过 500 亿美元。因此,受前面提到的第三方(3P)算力容量交付延迟影响,整个日历年的资本开支预计约为 1,700 亿美元。在本财年下半年,我们目前预计资本开支将加速增长,主要来自 CPU(含更高的内存和存储成本)和 GPU,以及顺延至下半年(H2)交付的第三方算力容量。
被引用:↩ 基本面档案 · 主要风险 · 算力投多了,需求跟不上↩ 基本面档案 · 主要风险 · 零部件涨价与第三方算力交付延迟 ×2↩ FY2027Q1 季度复盘 · 业绩与指引↩ FY2027Q1 季度复盘 · 当季异动↩ FY2027Q1 季度复盘 · 长期趋势异常↩ FY2027Q1 季度复盘 · 电话会要点 · 指引与展望↩ FY2027Q1 季度复盘 · 电话会要点 · 风险与逆风↩ FY2027Q1 季度复盘 · 管理层口径变化↩ FY2027Q1 电话会解析 · 核心判断↩ FY2027Q1 电话会解析 · 管理层发言解析 · Amy Hood|CFO↩ FY2027Q1 电话会解析 · 措辞与语气信号↩ 指引与语气 · 核心结论↩ 指引与语气 · 指引演变 · 资本开支与自由现金流 ×3↩ 指引与语气 · 指引演变 · 算力供给约束与元器件涨价↩ 指引与语气 · 需要跟踪的信号↩ 云三强一年砸 6,000 亿建算力:用同一把尺子量,谁的投入回本最快? · 多方原话交锋与验真标尺 · 对质一:算力是不是过剩?——结论:三家都说供不应求,瓶颈在机房和电力,谷歌、微软已在为第三方算力付出代价↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 多方原话交锋与验真标尺 · 对质一:算力到底有没有过剩?——结论:上下游五家掌门人同台证实“土地与电力(LPS)”才是唯一瓶颈,亚马逊自建现成核电最顺,谷歌与微软受困机房断档
P03631:30
As we continue to improve the efficiencies of our infrastructure, each dollar of CapEx has the potential to support more revenue and higher returns over time. Given our strong business performance, we expect to continue to remain free cash flow positive in FY27. To complement cash generated by the business and preserve financial flexibility, we will access additional sources of funding when we believe it is attractive to do so. In closing, we are off to a strong start to FY27, with accelerated growth across the Microsoft Cloud. Product improvements, along with efficiency gains across our data center infrastructure and our first-party apps and agents, are increasing the value and improving the outcomes we deliver to our customers. Delivering that value to our customers positions us for durable long-term growth. With that, let's go to Q&A. Jonathan?
随着我们不断提升基础设施的效率,随着时间推移,每一美元的资本开支都有潜力支撑更多的营收并带来更高的回报。鉴于我们强劲的业务表现,我们预计在 2027 财年将继续保持自由现金流为正。为了补充业务产生的现金并保持财务灵活性,当我们认为具有吸引力时,我们将使用额外的融资渠道。最后总结一下,我们在 2027 财年取得了强劲开局,Microsoft Cloud 实现加速增长。产品改进,加上我们数据中心基础设施以及第一方应用和智能体的效率提升,正在增加我们向客户交付的价值并改善客户成果。向客户交付这一价值使我们处于实现持久长期增长的有利位置。下面,让我们进入问答环节。Jonathan?
被引用:↩ 基本面档案 · 管理层与资本配置↩ FY2027Q1 季度复盘 · 结论摘要↩ FY2027Q1 季度复盘 · 业绩与指引↩ FY2027Q1 季度复盘 · 长期趋势异常↩ FY2027Q1 季度复盘 · 电话会要点 · 指引与展望↩ FY2027Q1 季度复盘 · 管理层口径变化↩ FY2027Q1 季度复盘 · 叙事 vs 报表↩ FY2027Q1 季度复盘 · 对投资逻辑的影响↩ FY2027Q1 电话会解析 · 核心判断↩ FY2027Q1 电话会解析 · 管理层发言解析 · Amy Hood|CFO↩ FY2027Q1 电话会解析 · 措辞与语气信号↩ 指引与语气 · 核心结论↩ 指引与语气 · 指引演变 · 资本开支与自由现金流 ×2↩ 指引与语气 · 语气变化↩ 云三强一年砸 6,000 亿建算力:用同一把尺子量,谁的投入回本最快? · 核心争议拆解 · 争议二:谁的现金和资产负债表最扛得住?——结论:谷歌 > 微软 > 亚马逊↩ 云三强一年砸 6,000 亿建算力:用同一把尺子量,谁的投入回本最快? · 多方原话交锋与验真标尺 · 对质三:2027 年谁会踩刹车?——结论:三家都说 2027 年继续加码,资金来源从自有现金流转向借款↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 核心争议拆解 · 争议四:穿透自由现金流“两负一正”假象,谁的资产负债表真正缺钱?——结论:谷歌 +1,400 亿净现金最宽裕,微软闪电发债 250 亿,亚马逊净债 -589 亿最紧绷↩ 年砸 6,000 亿美金的算力豪赌:云三强烧穿自由现金流、集体举债,谁最先跑通真金白银的正循环? · 多方原话交锋与验真标尺 · 对质三:现金流承压下 2027 年谁最先踩刹车?——结论:三家 2027 年均不踩刹车,但微软次日发债 250 亿与上下游垫资担保揭示全产业链进入“信用杠杆扩张期”
P03732:21
Jonathan NeilsonVP of Investor Relations
Thanks, Amy. We will now move over to Q&A. Out of respect for others on the call, we request that participants please only ask one question. Operator, can you please repeat your instructions?
谢谢你,Amy。我们现在进入问答环节。出于对电话会议其他参会者的尊重,我们恳请每位参会者仅提 1 个问题。接线员,请重复一下提问操作说明好吗?
问答环节
P03832:35
Operator
Thank you. Ladies and gentlemen, if you would like to ask a question, please press star one on your telephone keypad, and a confirmation tone will indicate your line is in the question queue. You may press star two if you would like to remove your question from the queue. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys. One moment, please, as we poll for questions. Our first question comes from the line of Adam Wood with Morgan Stanley. Please proceed.
谢谢。女士们、先生们,如果您想提问,请按电话键盘上的星号键加 1,确认音将表明您的线路已进入提问队列。如果您想从队列中取消提问,可以按星号键加 2。使用免提设备的参会者在按星号键之前可能需要先拿起听筒。请稍候,我们正在收集提问。我们的第 1 个问题来自 Morgan Stanley 的 Adam Wood。请讲。
P03933:13
Adam WoodAnalyst, Morgan Stanley
Hi. Thanks very much. Alongside lower-than-expected CapEx and those better cloud growth volumes sequentially, can I ask, as incremental AI capacity comes online, what do you see as likely to be the more important driver of returns over the next few years, improving utilization and unit costs within Azure, or your ability to monetize more layers of each workload across Fabric, Foundry, and Copilot?
嗨,非常感谢。在资本开支低于预期以及云业务增长量环比表现更好的同时,我想请问,随着新增 AI 算力容量陆续上线,您认为未来几年推动投资回报的更重要驱动力会是什么:是提升 Azure 内部的利用率和单位成本,还是你们跨 Fabric、Foundry 和 Copilot 对每个工作负载的更多层级进行变现的能力?
P04033:42
Satya NadellaChairman and CEO
Thanks for the question, Adam. I would say all of the above. I think the way we are coming at this is we have one pool, and we want to get the pool to be as efficient and fungible, right? That is sort of the place where if I think about all of the physics of how we are building out the data centers, all of the operational rigor with which we can bring up the capacity, and then of course, how do we run the workloads that are optimized on that infrastructure. Once you do that, then it is just a function of how we allocate it by looking at the demand signal. Even there, even in our new segment reporting, I think you kind of see it, which is Copilot stateful database underneath it is Work IQ.
谢谢你的提问,Adam。我会说以上全部都是。我认为我们看待这个问题的方式是,我们拥有一个统一的算力池,我们希望让这个池子尽可能高效且可灵活调配(fungible),对吧?如果我思考我们建设数据中心的所有物理机制、我们拉升算力容量的所有运营严谨性,然后当然还有我们如何在这个基础设施上运行经过优化的工作负载,这就是核心所在。一旦做到了这一点,接下来就只是通过观察需求信号来决定如何分配算力容量的问题。甚至在我们的新分部报告中,我想你也能看到这一点:Copilot 底层的有状态数据库是 Work IQ。
P04134:44
That gets used in Foundry, which is where people will build, let's say, a multi-agent system for supply chain that spans both unstructured and structured. Of course, it uses a Postgres database in Azure. Then, by the way, all the agentic work is registered in the Agent 365, and Perception manages the security of it, right? To us at least, we look at all of this as the same infrastructure. Of course, we report to you in a variety of different products. Your core question of where is the margin going to come from, where the leverage is going to come from, it's going to come from every one of them, and it compounds when we work them across.
它被用于 Foundry 中,人们会在 Foundry 里构建比如横跨非结构化和结构化数据的供应链多智能体系统。当然,它会使用 Azure 中的 Postgres 数据库。顺便说一句,所有智能体工作都会在 Agent 365 中注册,并由 Perception 管理其安全性,对吧?至少对我们而言,我们将所有这些视为同一个基础设施。当然,我们在向大家报告时会拆分为各种不同的产品。至于你核心关心的问题——利润率将来自哪里、经营杠杆将来自哪里——它将来自上述每一个环节,而且当我们将它们跨层协同运作时,会产生复利效应。
P04235:37
Amy HoodCFO
Adam, I'm sorry if we missed the front half of your question. I think we at least caught the back half.
Adam,很抱歉我们刚才如果漏听了你问题的前半部分。我想我们至少听清了后半部分。
P04335:43
Satya NadellaChairman and CEO
That's great.
太好了。
P04435:44
Jonathan NeilsonVP of Investor Relations
Thanks, Adam.
谢谢,Adam。
P04535:44
Adam WoodAnalyst, Morgan Stanley
Yeah, absolutely. That's very helpful. Thank you.
是的,完全没问题。非常有帮助,谢谢。
P04635:47
Jonathan NeilsonVP of Investor Relations
Operator, next question, please.
接线员,请接下一个问题。
P04735:51
Operator
The next question comes from the line of Karl Keirstead with UBS. Please proceed.
下一个问题来自 UBS 的 Karl Keirstead。请讲。
P04835:57
Karl KeirsteadAnalyst, UBS
Okay. Thank you. Amy and Satya, I am wondering if you could unpack what I thought was one of the key metrics from this call, and that is the guidance for Azure growth of 49% to 50% constant currency in December. I can imagine there is a number of variables, the capacity you are putting out, the allocation to third-party customers, probably OpenAI's strength, but perhaps you could comment a little bit on what some of the key drivers are, given how good that number seems, at least to me. Thank you.
好的,谢谢。Amy 和 Satya,我想请你们拆解一下我认为本次电话会议最关键的指标之一,那就是 12 月所在季度 Azure 按固定汇率计算增长 49% 至 50% 的指引。我能想到其中存在许多变量,比如你们投产的算力容量、向第三方客户的分配,可能还有 OpenAI 的强劲表现,但考虑到这个数字至少在我看来是如此亮眼,也许你们可以谈谈其中一些核心驱动因素是什么。谢谢。
P04936:29
Amy HoodCFO
Thanks, Karl, for the question. Maybe I will start by talking a little bit about Q1, and I think that will help to think through Q2 and even going forward. It is not unrelated, really, to Adam's question at some level as well.
谢谢你的提问,Karl。也许我先谈谈第一季度的情况,我认为这有助于思考第二季度乃至未来的表现。从某种程度上说,这也与 Adam 的问题密切相关。
P05036:45
In Q1, I would say the engineering teams have really delivered very, very good work in terms of improving efficiency at the platform layer. That is not just a statement around the efficiency of GPUs. It is a statement around the efficiency of every layer, how the app utilizes the platform, and how Foundry utilizes the platform, as well as the Azure platform itself. Those efficiencies, they are sort of ground out every week, and you have good ideas, a lot work, some don't, and you stay at it. So they are not maybe as predictable in terms of how much impact we will get in quarter. Q1, they did a very good job, and you saw some of that result in us being able to put more allocation into Foundry in the quarter. That is a great thing because as I said in the call, we still have demand that exceeds supply.
在第一季度,我想说工程团队在提升平台层效率方面确实完成了非常出色的工作。这不仅仅是指 GPU 的效率,而是指每一个层级的效率——应用如何利用平台、Foundry 如何利用平台,以及 Azure 平台本身的效率。这些效率提升是每周一点一滴打磨出来的,你会有很多好点子,很多奏效了,有些没奏效,但你一直坚持去做。因此,就单季度能产生多大影响而言,它们可能没那么容易精确预测。第一季度团队做得非常好,你也看到其中一部分成果体现为我们能够在本季度向 Foundry 分配更多算力容量。这是一件好事,正如我在电话会议中所说,我们的需求依然超过供给。
P05137:48
So where we can have our engineering teams deliver those efficiencies, we do really try to put it into Foundry when we can because it is so important, as Satya talked about, into how customers broadly are building what I would call against a new stack. Secondly, and you mentioned it, token pricing will create a little bit of variability. We had higher token pricing than we expected in the quarter. With some high-quality models that we are able to take advantage of and see good margins on do benefit us in the quarter. That did happen in Q1. I think also in that number in Q1 was the efficiencies I talked about applied not just to our GPU fleet, but I think people sort of underestimated when the example Satya gave for Adam's question, that is a GPU, CPU, storage, memory workload. It takes all of the pieces.
因此,只要我们的工程团队能够实现这些效率提升,在条件允许时我们就确实会尽量将其投入到 Foundry 中,因为正如 Satya 所谈到的,Foundry 对于广大客户如何基于我称之为“新堆栈”进行构建至关重要。其次,正如你提到的,token 定价会带来一点波动。本季度我们的 token 定价高于预期。凭借我们能够利用并获得良好利润率的一些高质量模型,我们在本季度确实从中受益了。这在第一季度确实发生了。我认为第一季度的那个数字里还包含了我刚才谈到的效率提升——它不仅适用于我们的 GPU 集群,而且我认为大家有些低估了 Satya 在回答 Adam 问题时举的那个例子:那是一个涵盖 GPU、CPU、存储、内存的综合工作负载,需要所有组件协同配合。
P05238:50
Our ability to also create additional capacity within our existing fleet gave us some room to be able to convert that actually pretty quickly as well in Q1. So in Q2, we have got those efficiency gains, which is great, and those will continue into Q2. We need to find some more, which we are counting on, enable to get to that guidance that I gave because I have faith in the team's work in Q1 continuing into Q2. But we also need that work to be able to help us a little bit because we had some supply we were counting on Q2 move out into H2. I think, and to your point, there is also some unknown on some token pricing through the quarter. That stuff can change.
我们在现有集群内部挖掘出额外算力容量的能力,也给了我们一些空间,使我们能够在第一季度相当快地将其转化为收入。到了第二季度,我们已经拥有了这些效率提升成果,这非常好,而且这些成果将延续到第二季度。我们还需要挖掘更多效率,这也是我们正在倚仗的,以达成我给出的那份指引,因为我有信心团队在第一季度的工作将延续到第二季度。但我们也确实需要这项工作来帮我们一把,因为我们原指望在第二季度上线的一部分供给推迟到了下半年(H2)。此外,正如你所说,整个季度中某些 token 的定价也存在一些未知数,这些因素是会变化的。
P05339:38
I feel good in terms of the efficiency gains that we saw when we are able, and when I am able to see those and put them in, I feel good about guiding to that. But as other things are less predictable, I hope that is helpful on the levers, Karl.
对于我们已经看到的效率提升,当我能够看到这些成果并将其纳入测算时,我对据此给出指引感到很有把握。但鉴于其他因素较难预测,希望以上对驱动因素的拆解对你有帮助,Karl。
P05439:55
Karl KeirsteadAnalyst, UBS
Yeah, it is. Thanks, Amy.
是的,很有帮助。谢谢你,Amy。
P05539:58
Jonathan NeilsonVP of Investor Relations
Thanks, Karl. Operator, next question, please.
谢谢,Karl。接线员,请接下一个问题。
P05640:03
Operator
The next question comes from the line of Mark Moerdler with Bernstein Research. Please proceed.
下一个问题来自 Bernstein Research 的 Mark Moerdler。请讲。
P05740:09
Mark MoerdlerAnalyst, Bernstein Research
Thank you very much for taking my question. Congratulations on the solid quarter and the solid guidance. It is really nice to see how well you guys are executing. I would like to get a sense on the drivers of the AI strength in Azure being from enterprise versus digitally native in general, or AI native. With inferencing starting to ramp and Microsoft the go-to for enterprises, how should we think, Amy, about the mix of enterprise customer workloads within overall workloads at this point? Satya, with the strong growth of the Azure AI platform offering, can you give us color on what is driving that? Is it, again, enterprise? Is it digitally native? Obviously, it is a mix of both, but any color that shows the ramp of that enterprise, I think, would be valuable.
非常感谢接受我的提问。祝贺你们取得了稳健的季度业绩并给出了稳健的指引。看到你们如此出色的执行力令人非常欣喜。我想了解一下,目前推动 Azure 中 AI 强劲表现的驱动力究竟更多来自传统企业客户,还是总体上的数字原生企业或 AI 原生企业?随着推理需求开始放量,而微软又是企业客户的首选平台,Amy,在这个时间点上,我们应该如何看待企业客户工作负载在整体工作负载中的占比结构?Satya,鉴于 Azure AI 平台产品的高速增长,您能否为我们进一步拆解背后的驱动力?究竟更多是企业客户还是数字原生企业?显然这是两者的结合,但任何能够展示企业客户放量态势的细节都将非常有价值。
P05841:01
Satya NadellaChairman and CEO
Yeah. Thanks for the question, Mark. Maybe I will start, and Amy, you can add to it. I was even in Europe just last week, and it was great to see the quality of the agentic systems that are just broadly getting deployed. When Unilever deploys what is their automated order taking and trade coupon dispute management stuff, all as a fully agentic touchless system. Rolls-Royce deploys a system to really manage all of their maintenance of whatever their jet engines with 30,000 parts are pretty complex supply chain, both planning, execution, inventory management system, all built on Foundry agentic systems. RBI, which is an Austrian bank, showed me 20 plus business processes end to end. They were talking about whether it is in for credit or what have you, how they are able to now do that so much more optimally.
好的,谢谢你的提问,Mark。也许我先来回答,然后 Amy 可以补充。就在上周我还去了欧洲,看到正在广泛部署的智能体系统所展现出的高质量,令人非常振奋。比如 Unilever 部署了自动化订单接收和贸易优惠券纠纷管理系统,全部作为完全无接触的智能体系统运行。Rolls-Royce 部署了一套系统来全面管理其喷气发动机(包含 30,000 个零部件)的维护工作,这是一个相当复杂的供应链规划、执行和库存管理系统,全部基于 Foundry 智能体系统构建。奥地利银行 RBI 向我展示了 20 多个端到端业务流程,他们谈到了无论是在信贷审批还是其他业务中,他们现在如何能够以更优化的方式完成这些工作。
P05942:13
So the breadth, the quality, their ability. Oh, by the way, the multi-model nature of it. They start with a frontier model. Many of them are, in fact, the Unilever one, they just dropped an MAI model trained using our traces. So even the degree of sophistication of what I think of as model optimization, workload optimization, token optimization, was just great to see. So the breadth is starting. Finally, it does feel like the enterprise workloads. They feel like to me, like the database applications enterprises built in the past that I grew up with are happening now when it comes to AI. In fact, if anything, some of the- The shiny object stuff is waning, which is it is not about the next big thing. They are really more about, "Wow, can I build a system? Can I own the weights? Can I manage my costs?
所以无论是广度、质量,还是他们的能力——顺便提一句,还有它的多模型特性。他们通常从前沿模型起步;其中许多客户,实际上就像 Unilever 这个案例,他们刚刚利用我们的运行轨迹(traces)训练并部署了一个 MAI 模型。因此,在我称之为模型优化、工作负载优化、token 优化的成熟度方面,能看到这样的进展实在令人振奋。所以广度正在铺开。终于,我确实感觉企业客户工作负载正在全面启动。这让我觉得,就像我成长过程中亲历的企业在过去构建数据库应用一样,同样的事情如今正在 AI 领域发生。事实上,如果要说有什么变化的话,那就是一些追逐“花哨噱头”(shiny object)的现象正在消退,大家不再只是谈论下一个宏大概念,而是真正关心:“哇,我能构建一个系统吗?我能拥有模型权重吗?我能管住我的成本吗?
P06043:11
Can I have reliability? What about security?" So in that sense, the enterprise breadth motion is starting. But like everything else, the enterprise stuff is not like a quarter-over-quarter. It is a decade-long thing, and that is what I have been waiting for, as opposed to four customers who buy a lot of capacity from you, and you can show a few quarters of growth, and that is not a business as far as I am concerned. So I want the breadth. We are well-positioned on the breadth. We have large customers who want to buy from us, and we are open for business with it. As long as the pricing is right, we may sell them some. If not, we will be patient about building the breadth business.
我能获得可靠性吗?安全性怎么保障?”从这个意义上讲,企业客户的广度扩展正在启动。但就像其他所有企业级业务一样,企业客户市场不是按季度剧烈跳动的,而是一场长达 10 年的征程,而这正是我一直在等待的——相比之下,仅仅靠 4 家大客户向你购买大笔算力容量,虽然能让你展现出几个季度的增长,但在我看来那算不上一门真正的生意。所以我追求的是广度。我们在广度上处于非常有利的位置。当然也有大客户希望向我们采购,我们对这类业务也敞开大门;只要定价合理,我们可能会卖给他们一些。但如果定价不合适,我们会耐心地建设具有广度的业务。
P06144:00
Jonathan NeilsonVP of Investor Relations
Thanks, Mark. Operator, next question, please.
谢谢,Mark。接线员,请接下一个问题。
P06244:05
Operator
The next question comes from the line of Gabriela Borges with Goldman Sachs. Please proceed.
下一个问题来自 Goldman Sachs 的 Gabriela Borges。请讲。
P06344:12
Gabriela BorgesAnalyst, Goldman Sachs
Hi. Good evening. Thank you. Satya, I want to stay on this topic of breadth because you had a comment in the prepared remarks talking about how MAI can now be comparable to leading models within 3 to 6 months of their release. At the same time, you have OpenAI at 11% of revenue in the quarter. Maybe just take a step back and give us your latest thinking on how you think token mix and token value is going to evolve between the frontier MAI, and maybe what some of your more sophisticated enterprise customers are doing from a proprietary AI strategy standpoint. Thank you.
嗨,晚上好,谢谢。Satya,我想继续探讨关于“广度”的这个话题,因为您在准备好的发言中提到,MAI 现在可以在领先模型发布后的 3 到 6 个月内达到与之相当的水平。与此同时,本季度 OpenAI 占到了你们营收的 11%。能否请您退后一步,谈谈您对于前沿模型、MAI 之间的 token 组合和 token 价值将如何演变的最新思考,以及您旗下一些更为成熟的企业客户在专有 AI 战略方面正在采取哪些做法?谢谢。
P06444:48
Satya NadellaChairman and CEO
Yeah. I would say you should think of three things perhaps as in the toolbox for any workload. The first is a new model drops, and it has some great performance, and you can eval-max on whatever that matters to you, i.e., the outcome that matters to you by using it. People should use it. We saw that with some of the OpenAI models in the last quarter. They were fantastic models, and we are obviously very thrilled about the progress OpenAI has made with Astra and also what is to come. I thought we saw some good demand on that. The next thing people do is, "Hey, can I actually put multiple of the frontier models?" Because these have very different prices.
好的。我认为对于任何工作负载而言,你都可以把工具箱里的工具看作包含三个层面。第一,当一个新模型发布时,它具有非常出色的性能,你可以通过使用它在任何你所看重的指标(即对你重要的业务成果)上把评测效果拉满(eval-max)。大家应该去用它。我们在上个季度看到的一些 OpenAI 模型就是如此。它们是非常棒的模型,我们对 OpenAI 在 Astra 上取得的进展以及接下来的新成果显然感到非常振奋。我认为我们在这方面看到了很好的需求。人们接下来会做的第二件事是:“嘿,我能不能实际上把多个前沿模型组合起来使用?”因为这些模型的价格差异很大。
P06545:34
In fact, this morning, Artificial Analysis had what I think is the real benchmark, which is the coding agents using our Fusion, and I think we were number 2 or number 3 there, which is awesome to see. Which is you can now get frontier performance 45% faster, 75% cheaper. Who would want to not take that? If you are a coding agent user, you want, in fact, Anthropic and OpenAI, by the way, to compete for your workload, not like once a quarter, but for every task. That to me is what the value of these routers and Auto, Fusion stuff routing does, and we are very excited about it. Then the last thing is another important one. A lot of customers are saying, "Hey, look, take the Unilever one." It is their system.
事实上,今天上午 Artificial Analysis 发布了一项我认为真正有意义的基准测试,测试的是使用我们 Fusion 的编程智能体,我想我们在那里排在第 2 或第 3 名,看到这个结果太棒了。这意味着你现在可以以快 45% 的速度、低 75% 的成本获得前沿水准的性能。谁会不想用这样的方案呢?如果你是一名编程智能体用户,你实际上会希望 Anthropic 和 OpenAI 来竞争你的工作负载,而且不是每个季度竞争一次,而是针对每一项具体任务展开竞争。在我看来,这就是这些路由器(routers)以及 Auto、Fusion 路由功能的核心价值所在,我们对此感到非常兴奋。然后最后一件事也是非常重要的一点。许多客户正在说:“嘿,看看 Unilever 的例子。”那是他们自己的系统。
P06646:29
They will ultimately take even the traces after having done even a bunch with frontier models, and they just want to train their own model. So it can be open weights or, in this case, it was MAI model. So I think all of that needs to be as options that are available. Then depending on pricing, depending on the need of the customer, they will exercise it. There is a temporality to it. It is never like, "Oh, I start one place and that is where I stop." It is like, "I may start at the frontier. I may go to an open weight. I may go to an MAI model. I may go back to the frontier for the next drop for a few months, come out." That is how I think how dynamic these workloads are.
在使用前沿模型做了大量工作之后,他们最终甚至会提取那些运行轨迹(traces),然后只想要训练属于他们自己的模型。这可以是开源权重模型,或者在 Unilever 这个案例中是 MAI 模型。因此我认为,所有这些都需要作为可选项提供给客户。然后根据定价、根据客户的具体需求,他们会行使这一选择权。这里面存在一种时间动态性(temporality)。它绝不是“哦,我从一个地方起步,然后就永远停在那里”。实际情况是:“我可能会从前沿模型起步,可能会转向开源权重模型,可能会转向 MAI 模型,然后再为了下一代新模型回到前沿模型用上几个月,之后再切换出来。”我认为这就是这些工作负载如此动态演进的方式。
P06747:13
That is where when we think about Foundry or when we think about Fabric or when we think about Copilot and GitHub Copilot, we really want to build a model system that delivers customers value continuously versus them being stuck in any one thing.
因此,当我们思考 Foundry、思考 Fabric,或者思考 Copilot 和 GitHub Copilot 时,我们真正想要构建的是一个能够持续为客户交付价值的模型系统,而不是把他们困在某一个单一选择里。
P06847:34
Gabriela BorgesAnalyst, Goldman Sachs
Thank you for the call.
感谢您的解答。
P06947:34
Jonathan NeilsonVP of Investor Relations
Thanks, Gabriela. Operator, next question, please.
谢谢,Gabriela。接线员,请接下一个问题。
P07047:40
Operator
The next question comes from the line of Brent Thill with Jefferies. Please proceed.
下一个问题来自 Jefferies 的 Brent Thill。请讲。
P07147:46
Brent ThillAnalyst, Jefferies
Thanks. Amy, good to see as you are approaching 50%. You have another line item approaching 50%, and that is your operating margin. I think many ask, how can you sustain this level of growth with a 50 on the top and a 50 on the bottom? Maybe you can discuss the operational improvements you continue to put forward to maintain that high level on the bottom line.
谢谢。Amy,很高兴看到在云增速接近 50% 的同时,你们还有另一个指标也接近 50%,那就是你们的营业利润率。我想很多人都在问,在顶线(营收增速)达到 50、底线(营业利润率)也达到 50 的情况下,你们如何能够维持这样的增长水平?能否请您谈谈,为了在利润端维持如此高的水平,你们正在持续推进哪些运营改进?
P07248:13
Amy HoodCFO
Thanks, Brent. Let me first say the best solution here is revenue growth. I would say I tend to start and focus there, even though I think many people seem to think I start at the bottom of the P&L and work up. The right answer is you always start at the top of the P&L and work down. What we have been focused on, and I think really it is almost inherent in all of the commentary, is we change segments because we are changing how we deliver products and services to customers. We are changing it because we are delivering new and different products with a lot of value in them, and those products are far more integrated than they were before. I think when you see that revenue accelerate at the top line, of course, it does.
谢谢,Brent。首先我想说,这里最好的解决方案就是营收增长。尽管似乎很多人认为我是从利润表(P&L)的最底端开始往上倒推,但我往往是从最顶端(营收)开始并聚焦于此。正确的答案永远是从利润表的顶端开始往下做。我们一直专注的事情——而且我认为这几乎贯穿着我们今天所有的评论——就是我们之所以调整分部架构,是因为我们正在改变向客户交付产品和服务的方式。我们之所以做出改变,是因为我们正在交付蕴含巨大价值的全新且不同的产品,而且这些产品的集成度比以往高得多。我认为,当你看到顶线营收加速增长时,它自然就会起到推动作用。
P07349:03
In a pretty healthy way contribute to positive margin and positive margin dollars, which I think I need people to also focus on. The second piece is this real focus on efficiency. Because efficiency, when we say the word, I think people believe it is cost-related. The outcome is cost-related, but the real benefit of efficiency is stability, it is security, it is reliability, it is that it delivers the highest quality unit at the lowest possible cost. So it is operational excellence. So I think when you think about you can deliver product excellence, which is what we are really focused on, I think we did a very good job on product quality in the past quarter, which I think teams should be proud of in lots of places.
它会以相当健康的方式贡献正的利润率和正的利润额(margin dollars),我认为大家也同样需要关注利润额的增长。第二块是对效率的真正聚焦。因为当我们提到“效率”这个词时,我想大家往往认为它只跟成本有关。其结果确实与成本相关,但效率带来的真正好处是稳定性、安全性、可靠性,是能够以尽可能低的成本交付最高质量的单元产出。所以它的本质是卓越运营(operational excellence)。因此我认为,当你思考如何交付卓越产品(这也是我们真正聚焦的核心)时,我认为过去一个季度我们在产品质量方面做得非常出色,各个领域的团队都应当为此感到自豪。
P07449:53
I think then you have this sort of operational focus on improvement, and then it is a real focus, in terms of operating expense, to make sure it is going toward building the new thing or providing security and quality. I think we have made, I think, a very active choice to be really focused on those two things, especially in this environment, and how important it is. I think when you do those things and you happen to be in a good market with breadth and breadth in customers and a global business, we have seen a good result. This quarter in particular, when you are delivering a lot of efficiency gains in a quarter and you can deliver revenue growth without spending additional costs, you of course see a benefit, which we did.
在此基础上,再加上这种对持续改进的运营聚焦,然后在营业费用方面保持真正的专注,确保资金投向构建新产品或者提供安全性和质量保障。我认为我们做出了一个非常主动的选择,即高度聚焦于这两件事,尤其是在当前环境下,这两点至关重要。当你做好了这些事情,同时又恰好身处一个具有客户广度和全球化业务的良好市场中,我们就看到了很好的结果。特别是在本季度,当你在单季度内实现了大量效率提升,并且能够在不增加额外成本支出的情况下实现营收增长时,你自然会看到利润率受益,而我们本季度确实做到了这一点。
P07550:43
But I feel good about what is behind that number, which is, I think, a focus on the right levers.
但我对这个数字背后的支撑因素感到很满意,那就是我认为我们聚焦在了正确的杠杆上。
P07650:52
Jonathan NeilsonVP of Investor Relations
Thanks, Brent Thill. Operator, next question, please.
谢谢,Brent Thill。接线员,请接下一个问题。
P07751:27
Brad RebackAnalyst, Stifel
Hello?
喂?
P07851:29
Jonathan NeilsonVP of Investor Relations
We are. Hi.
我们在听。你好。
P07951:32
Operator
Sorry about that.
刚才很抱歉。
P08051:32
Apologies for the delay. Our next question comes from the line of Brad Reback with Stifel.
抱歉耽搁了。我们的下一个问题来自 Stifel 的 Brad Reback。
P08151:39
Brad RebackAnalyst, Stifel
Great. Sorry about that. I did not hear my name. On M365 consumption, when you all shifted GitHub from a per-seat model to a consumption model, it unlocked a ton of revenue growth for you all. As you think about the tools in place now on the consumption side for the core M365 customer, do you think the unlock is as fast and without sales effort, or is it going to take a fair amount of effort to get those meters spinning? Thanks.
太好了,刚才很抱歉,我没听到叫我的名字。关于 M365 的按量消耗模式,当你们把 GitHub 从按席位模式转向按量消耗模式时,为你们释放了巨大的营收增长。当你们思考目前针对核心 M365 客户在按量消耗端所部署的工具时,你们认为这种增长释放也会一样快且无需太多销售投入,还是说需要付出相当大的销售努力才能让这些计费表快速转动起来?谢谢。
P08252:14
Satya NadellaChairman and CEO
Yeah, thanks for the question. On the coding side, it will be faster just because I think people are used to paying on this pay-as-you-go as the general market, and how it works. If anything, hopefully some of the things that we announced even at GitHub Universe today with Fusion are a more attractive way, right? Because if you think about it, right, you buy a bunch of credits and you want to use those credits most efficiently. That is the promise of GitHub Copilot Fusion. So we are very optimistic about making progress on that. When it comes to Copilot itself, right, we are trying to make sure that we in some sense are driving more and more value into the subscription with every model drop and essentially consolidating the frontier gains for broad deployment.
好的,谢谢你的提问。在编程领域,速度确实会更快,原因很简单,我认为大家已经习惯了按需付费(pay-as-you-go),这是该领域的普遍市场习惯和运作方式。甚至可以说,希望我们今天在 GitHub Universe 大会上随 Fusion 一起发布的一些功能会提供一种更具吸引力的方式,对吧?因为如果你仔细想一想,你购买了一批额度(credits),你自然希望最高效地使用这些额度。这就是 GitHub Copilot Fusion 的承诺。因此我们对在这方面取得进展非常乐观。而说到 Copilot 本身,我们正努力确保随着每一次模型升级,将越来越多的价值注入到订阅服务中,实质上是将前沿技术成果整合起来以实现广泛部署。
P08353:12
In many instances, as my remarks said, IT funds this, right? That is the thing that you want to have standard issue across the board. At the same time, you have your pay-as-you-go or consumption meters for places where you need it. So both of those options are open, and I think that is why the fact, with Copilot, Amy referenced, which is we are trying to make sure that customers understand both options, they are able to use the two options in the optimal way that benefits them. We do not want them to overbuy one thing and then feel like they are tokenmaxxing because that does not serve anybody's purpose. We want to make sure that they understand the value of the subscription, and how it is a continually improving value. It is not even static. At the same time, you can exercise this consumption meter.
在很多情况下,正如我在发言中所说,这笔费用是由 IT 部门出资的,对吧?这是企业希望在整个组织内统一配备的标准配置。与此同时,在有需要的场景下,客户也可以使用按需付费或按量消耗的计费表。因此这两种选择都是开放的,我认为这也正是 Amy 刚才提到关于 Copilot 的一点:我们正努力确保客户同时理解这两种选择,并能够以最有利于自身的方式优化组合使用这两种模式。我们不希望他们过度购买某一种模式,然后觉得自己是在盲目刷 token(tokenmaxxing),因为那对任何人都没有好处。我们希望确保他们理解订阅服务的价值,并明白这是一个持续提升的价值,甚至不是静态不变的。与此同时,你也可以启用这个按量消耗计费表。
P08454:08
So that is a little bit of the degree of sophistication in both in our sales motions, even in customers understanding that is, I think, coming together. We feel very good about the progress, but a lot more to do.
所以无论是在我们的销售运作模式上,还是在客户对这一机制的理解上,这都体现出了一定程度的精细化演进,我认为这两方面正在逐步磨合成型。我们对目前的进展感到非常满意,但还有很多工作要做。
P08554:20
Amy HoodCFO
I think I would say it is also why we have made the investment into the Frontier Co. here, coupled with changes in our sales motion, which I talked a little bit about. We need both of those things, to make sure customers are. Because what I think Satya Nadella is saying, we want them to utilize both the Copilot license to its fullest and understand when the consumption meter is delivering value to them. The investment in the FDE organization or the Frontier Co. as well as new motions within our modern work and Microsoft 365 sales teams, are both meant to do that. I think to Satya Nadella's point, it will be a slower move. I also still think we are still seeing encouraging signs, and I am still positive about that.
我想补充一点,这也正是我们投资建立 Frontier Co. 并配合调整销售运作模式的原因,刚才我也稍微提到了一点。我们需要双管齐下,以确保客户能够充分受益。因为正如 Satya Nadella 所说,我们希望客户既能充分利用 Copilot 席位许可,又能明白按量消耗计费表在什么时候能为他们创造价值。对前线部署工程师(FDE)组织(即 Frontier Co.)的投资,以及我们在现代办公(Modern Work)和 Microsoft 365 销售团队内部推行的新销售动作,都是为了实现这一目标。我同意 Satya Nadella 的观点,这会是一个相对渐进的过程。但我依然认为我们已经看到了令人鼓舞的迹象,我对此依然持积极态度。
P08655:16
Brad RebackAnalyst, Stifel
Thank you.
谢谢。
P08755:18
Jonathan NeilsonVP of Investor Relations
Thanks, Brad. Operator, we have time for one last question.
谢谢,Brad。接线员,我们还有时间回答最后 1 个问题。
P08855:24
Operator
The next question will come from the line of Tal Liani with Bank of America. Please proceed.
下一个问题将来自 Bank of America 的 Tal Liani。请讲。
P08955:32
Tal LianiAnalyst, Bank of America
Hey. Just clarification on something you just said. Did you disclose the Copilot numbers this quarter? My question is more about the capital commitment or the capital strategy. You said in the prepared remarks that you will approach raising capital if need be in the future. Can you discuss your strategy around it, between debt and equity and other sources? How do you intend to raise capital if need be? Thanks.
嘿,我想先澄清一下你们刚才提到的一件事:你们本季度披露 Copilot 的具体数据了吗?我的主要问题是关于资本承诺或资本战略。您在准备好的发言中提到,未来如有需要,你们将考虑筹集资金。您能否谈谈你们围绕这一点的战略,在债务、股权和其他渠道之间如何考量?如果有需要,你们打算如何筹集资金?谢谢。
P09056:00
Amy HoodCFO
Great. I will take that. I think what I said is if it is attractive and makes sense. We are lucky. We have a lot of flexibility in terms of our capacity to raise financing. I have talked about this before. There is a form of financing called leasing, and we have been using that one as a vehicle. We are fortunate to have access in the debt markets, given where our ratings are, and we have not yet, I would say, tapped that. Of course, there are other options. I think the way I see it is we are feeling good that we are free cash flow positive. We feel good that the return on every dollar of CapEx we are spending, we are confident in that. Therefore, we feel like we have lots of options to be able to tap the financing markets when they make sense and they are attractive.
好的,这个问题我来回答。我想我刚才的原话是“当这样做具有吸引力且合乎逻辑时”。我们很幸运,在筹集融资的能力方面拥有很大的灵活性。我以前也谈到过这一点:有一种融资形式叫做租赁(leasing),我们一直在将其作为一种融资工具使用。鉴于我们的信用评级水平,我们很幸运能够便利地进入债务市场,而且我想说我们目前尚未真正动用那块空间。当然,还有其他各种选择。在我看来,我们对保持自由现金流为正感到很满意,我们对所支出的每一美元资本开支的回报都充满信心。因此,我们认为自己拥有很多选择,可以在合乎逻辑且具有吸引力的时候利用融资市场。
P09257:05
Tal LianiAnalyst, Bank of America
Thank you.
谢谢。
P09357:05
Jonathan NeilsonVP of Investor Relations
Thanks, Tal. 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 all of you soon.
谢谢,Tal。今天财报电话会议的问答环节到此结束。感谢大家今天的参与,期待很快与各位再次交流。
P09457:14
Amy HoodCFO
Thank you.
谢谢大家。
P09557:15
Jonathan NeilsonVP of Investor Relations
Cheers.
再见。
P09657:19
Operator
Thank you. This concludes today's conference. You may disconnect your lines at this time, and we thank you for your participation.
谢谢。今天的会议到此结束。您现在可以挂断电话,感谢您的参与。