拆解Circle Q1财报:利率红利退潮后,USDC准备下一盘大棋

Odaily星球日报Published on 2026-05-11Last updated on 2026-05-11

Abstract

稳定币发行商Circle于2026年5月11日公布第一季度财报。核心财务数据显示,公司一季度总营收及储备收入为6.94亿美元,略低于市场预期;每股收益为0.21美元,高于预期;净利润为5500万美元,同比下降15%。营收增长放缓主要归因于美联储降息导致的储备资产收益率下降。 尽管整体营收不及预期,但财报中不乏亮点。Circle的非储备收入(如平台服务、API工具等)连续增长,达到4200万美元,显示收入来源趋于多元化。同时,核心盈利指标RLDC Margin连续四个季度提升至41%,表明其成本控制能力增强。 运营方面,USDC流通量达770亿枚,同比增长28%,但其链上交易量同比激增263%,达到21.5万亿美元,显示USDC正被高频用于支付、DeFi等实际场景。此外,Circle披露其支付网络Arc Network已完成2.22亿美元代币预售,估值达30亿美元。公司还推出了面向AI Agent经济的“Agent Stack”基础设施服务。 分析认为,在利率红利退潮的背景下,Circle正积极向非利息收入业务扩张,通过布局支付网络、企业服务和AI基础设施,旨在将USDC从静态的储备资产转变为支撑互联网和新兴经济活动的流动“血液”。

原创 | Odaily 星球日报(@OdailyChina)

作者|Azuma(@azuma_eth)

5 月 11 日美股盘前,稳定币发行商 Circle 正式公布了 2026 年第一季度财报。

财报数据显示,Circle 一季度总营收及储备收入为 6.94 亿美元,略低于市场预期的 7.15 亿美元;EPS 为 0.21 美元,高于市场预期的 0.18 美元;调整后 EBITDA 为 1.51 亿美元,同比增长 24%;净利润为 5500 万美元,同比下降 15%。

受财报发布影响,CRCL 盘前出现大幅波动,近 6% 的盘前涨幅在震荡中被逐渐抹平。截至 22:00,CRCL 美股后一度继续大幅下挫,但随后又快速由跌转涨,暂报 115.74 美元,日内涨幅 2.52%。

核心数据解读

如财报所示,本季度 Circle 的总营收及储备收入(Total Revenue and Reserve Income)为 6.94 亿美元,同比虽增长 20%,但却打断了此前连续多个季度的增长趋势(5.79 亿美元 ➡️ 6.58 亿美元 ➡️ 7.4 亿美元 ➡️ 7.7 亿美元 ➡️ 6.94 亿美元),也未能达到市场预期。

Circle 将收入增长放缓归因于储备回报率(Reserve Return Rate)的下降。2025 年 12 月 10 日,美联储将联邦基金利率目标区间下调 25 个基点至 3.5%-3.75%,进而压缩了 Circle 以美债为主的储备资产收益率。

但在相对弱势的营收下,Circle 的这份财报仍透露了一些值得乐观的局部数据。

一是 Circle 除去储备收入(Reserve Income)之外的其他收入(Other Revenue)创下新高,达 4200 万美元,呈现连续多个季度的增长趋势(2100 万美元 ➡️ 2400 万美元 ➡️ 2900 万美元 ➡️ 3700 万美元 ➡️ 4200 万美元)。

如我们今日下午在《财报、法案、美联储......Circle本周连迎三场大考》一文中所述,这意味着 Circle 的收入来源正在更加多元化,其平台服务、API 工具以及支付产品正在产生实质性的商业收益,对于利息收入的依赖正在下降。

另一个值得关注的数据则是 RLDC Margin,即收入减去分销成本后的利润率,这反映的是扣除分销费用后的核心业务盈利水平,也被普遍视为 Circle 最核心的盈利指标。本季度 Circle 的 RLDC Margin 达到了 41%,实现了连续四个季度的增长(36% ➡️ 39% ➡️ 40% ➡️ 41%),这意味着 Circle 的对分销成本的控制在变得更加高效。

再来看看支出情况。分销与交易成本(Distribution and Transaction Costs)依然是 Circle 最大的支出项,本季度高达 4.05 亿美元,同比增长 17%。这部分支出主要与和 Coinbase 之间的 USDC 分销合同挂钩,该合同将于今年 8 月到期,如何续约(主要看分成比例是否会调整)将极大影响 Circle 后续的支出和利润状况。

除去分销成本外,经营成本(Total Operating Expenses)也从去年的 1.38 亿美元激增至 2.42 亿美元,同比增幅高达 76%。其中最主要的增项来源于补偿费用(Compensation expenses),由 7562 万美元增至 1.38 亿美元,几乎翻倍 —— Circle 解释这主要是受 IPO 后股票薪酬支出(Stock-based compensation)及相关税收的影响。

受支出激增影响,Circle 本季度的经营利润由去年同期的 9294 万美元下滑至 4500 万美元; 归属于普通股股东的净利润从去年同期的 6479 万美元下降至 5525 万美元;每股收益(EPS)为 0.23 美元,稀释后为 0.21 美元。

其他经营亮点

除去核心财务数据外,Circle 还在 Q1 财报中披露了多项经营亮点。

其中最关键的一项数据为,USDC 第一季度末的流通量达到了 770 亿枚,同比增长 28%,但与此同时第一季度 USDC 的链上交易量却达到了惊人的 21.5 万亿美元,同比增长 263%。Visa Onchain Analytics 数据分析亦显示,第一季度 USDC 在全网稳定币交易量中的占比达到了 63%。

交易量增速远大于流通量增速,这意味着每一枚的 USDC 在链上的转手与应用频率大幅提高 —— USDC 不是静态地躺在钱包内,而是在被真实地、高频地用于支付、DeFi、跨境结算等场景。

另外的一项重点是,Circle 还披露旗下支付网络 Arc Network 已完成了 2.22 亿美元的 ARC 代币预售,估值高达 30 亿美元,资方包括 a16z、贝莱德、洲际交易所、渣打、SBI 等鼎鼎大名的机构。今日披露的 ARC 代币白皮书则显示,60% 的代币将分配至生态系统(代币销售、开发者资助、网络增长);25% 将分配至 Circle(协议开发、质押与治理);15% 将分配至长期储备(战略灵活性与经济稳定)。

此外,Circle 旗下面向机构的支付服务 Circle Payments Network(CPN)预估年交易量(根据截止 3 月 31 日的 30 天数据逆推)也已达到了 83 亿美元;四月 Circle 又推出了“托管支付”(Managed Payments)产品以扩展其支付产品,该产品允许金融机构在无需自行管理数字资产的情况下启动稳定币支付业务 。

为了应对 AI Agent 驱动的商业未来,Circle 还宣布推出了 Agent Stack,这是一套面向 AI Agent 经济的基础设施服务与工具套件,旨在为自主运行的 AI Agent 提供高速、低成本的金融服务能力。Circle 联合创始人兼首席执行官 Jeremy Allaire 对此的展望表述是:“随着 ARC 代币的预售、Arc Network 势能的积累,以及 Agent Stack 的推出,我们正在为 AI 原生的经济活动和更具可编程性的互联网金融系统构建值得信赖的基础设施 。”

Circle 的新棋局

在高息红利退潮的宏观背景下(沃什接任美联储后会主推“降息+缩表”策略),Circle 显然不愿完全受制于美联储的利率政策,其布局重点已悄然转向非利息收入的多元化扩张。

从本季报披露的细节来看,在接连推出 CPN、Managed Payments、Agent Stack、Arc Network 等服务之后,Circle 的目标已不只是做一家“稳定币发行商”,而是试图将 USDC 打造成互联网时代的底层美元网络。在这一全新的愿景下,Circle 服务对象已不再局限于交易所或加密原生用户,而是在向跨境支付、企业结算乃至 AI Agent 经济全面延伸。

Circle 的野心已然十分明确:将 USDC 从一种“静态的储备资产”彻底转化为“流动的经济血液”。这或许才是 Circle 真正想下的那盘大棋。

Related Questions

QCircle 2026年第一季度总营收及储备收入是多少?为什么低于市场预期?

ACircle 2026年第一季度总营收及储备收入为6.94亿美元,略低于市场预期的7.15亿美元。收入增长放缓的主要原因是储备回报率的下降。美联储在2025年12月下调了联邦基金利率,导致Circle以美债为主的储备资产收益率降低。

Q在营收增长放缓的情况下,Circle Q1财报中有哪些值得关注的积极局部数据?

ACircle Q1财报中有两个值得关注的积极局部数据:1. 除去储备收入外的其他收入创下新高,达到4200万美元,表明收入来源正变得更加多元化,对利息收入的依赖在下降。2. 核心盈利指标RLDC Margin(收入减去分销成本后的利润率)达到了41%,实现了连续四个季度的增长,说明公司对分销成本的控制更加高效。

Q本季度Circle的经营成本和净利润同比有何变化?主要原因是什么?

A本季度Circle的经营成本从去年同期的1.38亿美元激增至2.42亿美元,同比增幅高达76%。主要原因是补偿费用(特别是IPO后的股票薪酬支出及相关税收)大幅增加。同时,归属于普通股股东的净利润从去年同期的6479万美元下降至5525万美元,同比下降15%。

QUSDC在第一季度的流通量和链上交易量表现如何?这说明了什么?

A截至第一季度末,USDC的流通量达到770亿枚,同比增长28%。然而,其链上交易量达到了惊人的21.5万亿美元,同比增长263%。这意味着每一枚USDC在链上的转手与应用频率大幅提高,USDC正被真实、高频地用于支付、DeFi、跨境结算等场景,而非静态储备。

Q文章指出Circle正在下“一盘大棋”,其具体战略转型和业务扩张方向是什么?

ACircle的战略已从单纯依赖利率红利的稳定币发行商,转向基于USDC构建互联网时代的底层美元网络。其业务正通过推出Circle Payments Network、托管支付服务、Arc Network以及面向AI Agent经济的Agent Stack等产品和服务,向更广泛的跨境支付、企业结算乃至AI Agent经济等领域全面延伸。目标是让USDC从一种“静态的储备资产”彻底转化为“流动的经济血液”。

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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.

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What is AGENT S

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