长达四页的内部信，OpenAI在打什么牌？

marsbitPublished on 2026-04-14Last updated on 2026-04-14

Abstract

OpenAI内部信揭示与Anthropic的竞争策略：双方收入口径差异导致Anthropic公布的300亿美元年化营收被OpenAI调整为220亿美元，核心分歧在于记账方式（毛额vs净额）。企业端市场差距迅速缩小，Anthropic在IT、金融等关键行业已反超OpenAI。算力方面，当前OpenAI领先35%，但远期规划存在四倍差距。OpenAI承认微软合作限制客户触达，转而与亚马逊达成500亿美元合作，而亚马逊同时押注两家公司，通过Bedrock平台分发双方模型，加剧竞争复杂性。

按 Anthropic 的账本,它的年化收入是 300 亿美元,按 OpenAI 的换算,同一批销售数字只值 220 亿美元。两个数字都没造假。这是 4 月 13 日被媒体曝光的那封四页内部信里,OpenAI 首席营收官德雷瑟(Denise Dresser)抛出的第一刀。

事情的起点是一封被 The Information 获取的员工备忘录。德雷瑟在信里同时做了三件事:赞美亚马逊新合作「需求大得惊人」,承认微软合作「限制了我们触达客户」,然后花了相当篇幅拆解 Anthropic 的收入数字。这封信流出的时间,恰好是 Anthropic 刚宣布突破 300 亿美元年化营收里程碑的一周后。

表面是公司内部沟通,实质是一场精心构建的信息战。要读懂它,从三个维度分别入手最为直接,收入口径、企业端竞争格局以及算力军备路线,再把它们放进同一张云合作结构图里看。

80 亿美元的会计差距从哪里来

Anthropic 报出 300 亿美元年化营收,OpenAI 说实际数字是 220 亿。差出来的 80 亿美元,是两家公司在收入记账口径上做出的截然不同的选择。

Anthropic 采用毛口径(Gross)记账:当一家企业通过 AWS 购买了 Claude 的使用额度,Anthropic 把这笔钱的全额计入顶线收入,再把支付给亚马逊的平台分成作为成本处理。OpenAI 反过来,它只记录从微软那里实际拿到手的净额,微软的分成不进顶线。

两种方式都符合美国通用会计准则(GAAP)。Anthropic 的逻辑是它在客户交易中是「主要交易方」(principal),云厂商只是分发管道。OpenAI 的逻辑则是它把微软视为「代理方」,入账只算实际到手的部分。分歧的根源不在于谁在造假,而在于谁更激进地主张自己在销售链条中的主导地位。

德雷瑟在备忘录里写道,Anthropic「使用了让收入数字看起来更大的记账方式」,包括将 AWS 和谷歌的分成额毛额全额计入顶线营收。这句话的潜台词不难理解,届时 Anthropic 向 SEC 递交 S-1 招股书,审计师将对这个口径做出裁定,届时可能需要做统一口径的调整披露。按同一口径换算,Anthropic 是 220 亿,OpenAI 是 240 亿,领先方换了位置。

需要说明的是,Anthropic 的收入增速本身已经是历史级别的。据 Bloomberg 和 Sacra 等媒体的数据,它的年化营收从 2025 年四季度末的约 90 亿美元增长到现在的 300 亿美元,不到五个月三倍多,而且这主要是客户真实采购驱动,不是账面口径调整能解释的。这场会计争议的核心不是 Anthropic 在缩水,而是 OpenAI 在用「口径」这把刀重新画边界。

企业端的追赶速度,比大多数人预想的快

Ramp 追踪平台上数千家企业的实际 AI 支出行为,是判断企业端真实选择的一手数据来源。

Ramp AI Index 4 月数据:Anthropic 在企业付费客户中的占比升至 30.6%,OpenAI 是 35.2%,差距从 2 月份的 11 个百分点缩窄到 4.6 个百分点。按照 Anthropic 过去两个月平均每月 +6.3 个百分点的增速(这本身已是该指标的单月最大增幅纪录),它将在大约两个月内在这一指标上反超 OpenAI。

更值得注意的是结构性信号。在三个高采购力行业,Anthropic 的领先已经成为事实,信息技术/软件(63% 对 54%)、金融服务(52% 对 46%)、专业服务(47% 对 44%)均超出 OpenAI。这三个行业恰好是企业 AI 预算最集中、采购决策最专业的领域。这意味着在 AI 购买链条里拥有最大话语权的那批公司,已经开始集体向 Anthropic 倾斜。

德雷瑟在备忘录里罕见地承认,Anthropic「在企业客户中拥有显著的领先优势」,理由是编程能力。这句话从 OpenAI 内部发出,分量与外部评价完全不同,这是一家公司在内部告诉自己的员工,对方在核心战场上赢了。她同时加了一个预警:「You do not want to be a single-product company in a platform war.」(「在平台战争中,你不会想成为一家单一产品公司。」)这是在提醒员工,Claude 在编程上的优势如果无法延伸到平台层,最终只是一张门票而不是一张船票。

算力差距:今天相近,2030 年四倍

算力容量是 AI 公司之间最难在短期内缩短的竞争维度,因为它的建设周期以年为单位,资金门槛以百亿为单位。

当前的数字看起来差距不大:OpenAI 约 1.9 吉瓦,Anthropic 约 1.4 吉瓦,相差约 35%。德雷瑟在备忘录中将 Anthropic 描述为「operating on a meaningfully smaller curve」,但这个说法在当前的容量对比上并不算夸张,差距是真实存在的,只是还没到决定性的程度。

真正的分叉在 2027 年之后。OpenAI 规划 2030 年达到 30 吉瓦算力,背靠的是与甲骨文签订的 300 亿美元五年云计算合同、整个 Stargate 基础设施项目,以及 1.4 万亿美元的总建设承诺。

Anthropic 的路径依赖是一笔博通(Broadcom)定制芯片协议,容量为 3.5 吉瓦,通过谷歌云部署,2027 年起生效,加上 AWS 已有的训练集群,2027 年底目标是 7-8 吉瓦。

即便 Anthropic 完全兑现 2027 年目标,它与 OpenAI 2030 年规划之间仍有四倍的差距。这条鸿沟在技术上不是无法弥补的,如果模型效率提升足以让每单位算力产生更多收益,Anthropic 可以在更少的算力上做出足够好的产品。

但它必须在 Claude 在企业端的势头继续保持的前提下,通过持续的订阅收入去支撑自己的算力采购成本:据 Sacra 估计,Anthropic 今年支付给云合作商的费用将约 19 亿美元,2027 年将升至约 64 亿美元。

亚马逊,同时押注两个竞争对手

这封备忘录里最耐人寻味的一句话,是德雷瑟对微软合作关系的直接定性,她写道这一合作「也限制了我们在企业所在的地方触达他们」。

OpenAI 转向亚马逊的动作已经非常清晰:据 CNBC 报道,今年 2 月,亚马逊宣布向 OpenAI 投资 500 亿美元,同时获得 OpenAI 企业 Agent 管理平台 Frontier 的独家第三方云分销资格。

这是从微软轨道向亚马逊轨道的主动切换,背后逻辑很直接,很多企业客户的 AI 基础设施已经建在 AWS 的 Bedrock 平台上,微软的排他条款让 OpenAI 很难在那里直接销售。

但亚马逊在这场竞争里的另一面也同样值得关注,它是 Anthropic 目前最大的云基础设施合作方和战略投资人,累计投资 80 亿美元,双方合作的 Project Rainier 集群部署了约 50 万枚 Trainium 2 芯片。亚马逊在整场 AI 竞赛里的总押注合计 580 亿美元,同时流向两个正在企业市场正面交战的对手。

这不是一家超大规模云厂商的多元押注,而是一个更精确的结构:亚马逊既是 Anthropic 的「战略盟友和最大金主」,又是 OpenAI 用来「取代微软」的新云基础。

当两家公司争夺同一批企业客户时,争夺的渠道恰好是亚马逊的 Bedrock 平台,这个平台同时分发着两家公司的模型。谁在 Bedrock 上的转化率更高,亚马逊都赚到了,但 OpenAI 和 Anthropic 彼此损失了。

在企业市场份额持续被蚕食、微软合作出现结构性裂痕的压力下,OpenAI 选择用一场精心计算的数字战来重建叙事,同时借助亚马逊重新布局分发管道。三组数字各自拆开,这场竞争比任何一方想让你看到的都要复杂。

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Agent S: The Future of Autonomous Interaction in Web3 Introduction In the ever-evolving landscape of Web3 and cryptocurrency, innovations are constantly redefining how individuals interact with digital platforms. One such pioneering project, Agent S, promises to revolutionise human-computer interaction through its open agentic framework. By paving the way for autonomous interactions, Agent S aims to simplify complex tasks, offering transformative applications in artificial intelligence (AI). This detailed exploration will delve into the project's intricacies, its unique features, and the implications for the cryptocurrency domain. What is Agent S? Agent S stands as a groundbreaking open agentic framework, specifically designed to tackle three fundamental challenges in the automation of computer tasks: Acquiring Domain-Specific Knowledge: The framework intelligently learns from various external knowledge sources and internal experiences. This dual approach empowers it to build a rich repository of domain-specific knowledge, enhancing its performance in task execution. Planning Over Long Task Horizons: Agent S employs experience-augmented hierarchical planning, a strategic approach that facilitates efficient breakdown and execution of intricate tasks. This feature significantly enhances its ability to manage multiple subtasks efficiently and effectively. Handling Dynamic, Non-Uniform Interfaces: The project introduces the Agent-Computer Interface (ACI), an innovative solution that enhances the interaction between agents and users. Utilizing Multimodal Large Language Models (MLLMs), Agent S can navigate and manipulate diverse graphical user interfaces seamlessly. Through these pioneering features, Agent S provides a robust framework that addresses the complexities involved in automating human interaction with machines, setting the stage for myriad applications in AI and beyond. Who is the Creator of Agent S? While the concept of Agent S is fundamentally innovative, specific information about its creator remains elusive. The creator is currently unknown, which highlights either the nascent stage of the project or the strategic choice to keep founding members under wraps. Regardless of anonymity, the focus remains on the framework's capabilities and potential. Who are the Investors of Agent S? As Agent S is relatively new in the cryptographic ecosystem, detailed information regarding its investors and financial backers is not explicitly documented. The lack of publicly available insights into the investment foundations or organisations supporting the project raises questions about its funding structure and development roadmap. Understanding the backing is crucial for gauging the project's sustainability and potential market impact. How Does Agent S Work? At the core of Agent S lies cutting-edge technology that enables it to function effectively in diverse settings. Its operational model is built around several key features: Human-like Computer Interaction: The framework offers advanced AI planning, striving to make interactions with computers more intuitive. By mimicking human behaviour in tasks execution, it promises to elevate user experiences. Narrative Memory: Employed to leverage high-level experiences, Agent S utilises narrative memory to keep track of task histories, thereby enhancing its decision-making processes. Episodic Memory: This feature provides users with step-by-step guidance, allowing the framework to offer contextual support as tasks unfold. Support for OpenACI: With the ability to run locally, Agent S allows users to maintain control over their interactions and workflows, aligning with the decentralised ethos of Web3. Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

733 Total ViewsPublished 2025.01.14Updated 2025.01.14

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