独角兽公司报告：美国湾区一小时车程内，装着全球 90% 的 AI 市值

marsbitPublished on 2026-04-23Last updated on 2026-04-23

Abstract

美国旧金山湾区已成为全球生成式AI的超级集群，集中了全球91%的AI独角兽市值，占所有独角兽总市值的39%。全球独角兽市值高度集中，美国占比达65%，是中国的4倍。新独角兽诞生速度放缓，但平均估值创六年新高，主要由AI公司驱动。AI独角兽估值增速远超非AI公司，生成式AI市值占比从2%飙升至22%。湾区、纽约、洛杉矶和波士顿是美国四大独角兽集群，分别聚焦AI、金融科技/加密、国防/航天及消费、生物科技等行业。此外，大量“僵尸”独角兽滞留估值，但美国活跃独角兽比例较高。

作者: Elad Gil(数据分析:Shreyan Jain)

编译: 深潮 TechFlow

深潮导读: Elad Gil 团队连续六年追踪全球独角兽市值分布,2025 年的数据指向一个清晰结论:旧金山湾区正在成为生成式 AI 的超级集群,一小时车程内集中了全球 91% 的 AI 独角兽市值。与此同时,新独角兽诞生速度放缓,但现存独角兽的平均估值创下六年新高。这份报告用硬数据揭示了全球创业生态的权力重心正在加速向美国、向湾区倾斜。

所有数据截至对应年份的 12 月 31 日,下文中「2025」指 2025 年 12 月 31 日 / 2026 年 1 月 1 日时点的市值。

过去两年,我们经历了后零利率时代的市场修正、OpenAI 和 Anthropic 等前沿 AI 实验室的爆发式崛起,以及围绕「AI 泡沫」的持续争论。数据显示,旧金山湾区已经演变为一个 AI 超级集群,全球 91% 的 AI 私募市值集中在一小时车程的半径内。

往年分析可参考:2019、2020、2021、2023。

核心发现

生成式 AI 让湾区变成超级集群。 湾区目前占全球独角兽市值的约 39%,是第二名城市的 4 倍以上,一年前这个数字还只是 29%。如果只看生成式 AI 独角兽,湾区占比高达 91%。
美国独角兽的绝对主导地位。 美国过去一年新增了近 1.2 万亿美元的独角兽市值,全球占比达到约 65%。欧洲在市值份额上已经超过中国,但也只有 10% 左右。
新一代独角兽更集中在美国和湾区。 2023 年及之后诞生的独角兽中,美国占总市值的 83%,而 2022 年及之前诞生的那批只有 60%。湾区的份额更夸张:新一代 63%,老一代 33%。
新独角兽的诞生速度在放缓。 2022 至 2025 年间只新增了约 300 家独角兽,而此前三年超过 900 家。
但现存独角兽比以往任何时候都更值钱。 独角兽总数仅同比增长 6%,但总市值增长了 33%。平均每家独角兽的市值达到了六年来的最高水平。
估值增长主要由 AI 公司驱动。 2025 年,生成式 AI 独角兽的估值平均同比增长约 22 亿美元,非 AI 独角兽只有约 4 亿美元。生成式 AI 在全球独角兽市值中的占比从 2024 年的 2% 飙升至 22%。湾区的集中度只会继续扩大。
独角兽中心围绕特定行业聚集。 湾区前十大独角兽中有 6 家是 AI 公司;纽约前十有 7 家是金融科技/加密公司;洛杉矶前五有 3 家是国防/航天公司(SpaceX、Anduril、Relativity,占洛杉矶总市值的 83%),前十里还有 4 家消费公司。

数据说明

所有原始数据来自 CB Insights,可在此处查看。有几个注意点:

私募融资轮次在公开数据集中的更新存在滞后,部分独角兽估值可能不是最新的。比如 Anduril、Stripe 和 SpaceX 的最新融资轮次并未反映在数据中。

独角兽市值充其量只是创业生态活跃度的一个粗略的、滞后的代理指标,在公司与估值、城市、行业的映射中难免有误差。但我们认为数据在大方向上是准确的。

独角兽集中度

全球独角兽市值的地理集中度达到了历史最高。美国占所有独角兽市值的 65%,高于一年前的 58% 和 2020 年的 44%。美国的份额是排名第二的中国的约 4 倍。

图注:各国独角兽市值全球占比(含三大异常值)

湾区的独角兽市值同样是第二名城市的 4 倍以上,全球占比从 2024 年的 29% 增长到了 39%:

图注:各城市独角兽市值全球占比(含三大异常值)

即便剔除三个最大的异常值——OpenAI(5000 亿美元)、SpaceX(4000 亿美元)和字节跳动(3000 亿美元),大的生态系统自 2019 年以来也在持续集中。美国的份额稳步上升,中国稳步下滑。欧洲在 2024 年的独角兽总市值已经超过中国,纽约和伦敦也已超过北京。

图注:各国独角兽市值全球占比(剔除三大异常值)

图注:各城市独角兽市值全球占比(剔除三大异常值)

生成式 AI 的超级集中

如果只看 97 家以生成式 AI 产品/服务为核心收入来源的独角兽,湾区的集群效应更加极端。湾区占据了全球 AI 独角兽市值的 91%,没有其他城市超过 2%。

图注:生成式 AI 独角兽市值的城市分布

生成式 AI 独角兽的总市值呈指数级增长,几乎所有增量都来自美国,尤其是湾区。

图注:生成式 AI 独角兽总市值(按国家)

图注:生成式 AI 独角兽总市值(按城市)

AI 独角兽的估值增速远远超过非 AI 独角兽。2025 年全年为独角兽的 48 家 AI 公司,在这一年里的总市值增长了 7780 亿美元。这个数字超过了剩余 1100 多家非 AI 独角兽的市值增幅总和。即便剔除 OpenAI(增加约 3430 亿美元)和 Anthropic(增加约 3340 亿美元),生成式 AI 独角兽的平均估值同比增长仍有约 22 亿美元,是非 AI 独角兽平均增长(约 4.4 亿美元)的 5 倍。

图注:AI 独角兽 vs 非 AI 独角兽的市值增长对比

在相对占比上,生成式 AI 公司从 2023 年占全球独角兽市值的 2% 增长到了 22%。如果这个趋势持续,湾区凭借其对顶尖 AI 公司和人才的事实垄断,在全球独角兽市值中的份额将继续扩大。

图注:生成式 AI 占独角兽总市值的比例变化

(说明:我们只将主要收入直接来源于生成式 AI 的公司归类为「生成式 AI」。完整公司名单可在此处查看。我们纳入了 Cerebras、TensTorrent 等芯片/硬件公司以及 CoreWeave、Crusoe 等基础设施公司,但没有纳入 Databricks 这类更广泛地支持 AI/ML 工作负载的数据基础设施公司,也没有纳入 Anduril 这类将 AI/ML 用于自主系统的机器人/国防公司。)

新增独角兽

图注:年度新增独角兽数量

连续三年高增长之后,新独角兽的诞生速度在过去三年明显放缓。2019 年 12 月至 2022 年 12 月间,平均每年有 300 多家公司首次跻身独角兽行列。2022 年 12 月到 2025 年 12 月,这个数字降到了每年约 100 家,尽管 2025 年相比前两年有所回升。同时,过去三年有 45 家公司因估值下调或关停而失去独角兽资格,而前三年只有 16 家,说明 2021/2022 年零利率时代虚高估值的修正仍在持续。

图注:独角兽数量 vs 总市值趋势

虽然独角兽的数量基本持平,但总市值增长显著。过去一年,全球独角兽总市值从约 4.4 万亿美元增长到约 5.8 万亿美元,增幅 33%。这是一次强力反弹,特别是相对于 2023 年总市值实际同比缩水的情况。历史上市值增长更多由新公司跻身独角兽驱动,但 2025 年约 80% 的市值增长来自现有独角兽的估值提升。结果是平均每家独角兽的市值从约 30 亿美元上升到约 44 亿美元,是我们做这项分析六年来的最高值。成为独角兽更难了,但一旦跨过 10 亿美元门槛,这些公司平均而言更值钱,增长也更快。

图注:独角兽平均市值变化趋势

新一代 vs 老一代独角兽

剔除零利率时代虚高估值影响的一种方法是,只看 2023 年之后诞生的独角兽。以下是 2023 年前后两批独角兽的市值分布对比:

图注:2023 年前诞生的独角兽市值分布(按国家/城市)

图注:2023 年及之后诞生的独角兽市值分布(按国家/城市)

新一代独角兽更集中在美国,欧洲和中国的份额下降。2023 年至今新增的独角兽中,湾区占市值的 63%,而老一批独角兽中湾区只占 33%。

「僵尸」独角兽

2021 年 12 月的近 1000 家独角兽中,约 60% 至今保持着独角兽身份,但没有完成任何新一轮融资。这些「僵尸」独角兽在零利率时代融了足够多的钱存活至今,但无法突破当年的估值。它们合计占当前全球独角兽市值的约 1.4 万亿美元,接近全球总量的 25%。

图注:2021 年独角兽中的「僵尸」与「活跃」比例

美国和湾区的「活跃」独角兽(2021 年以来完成了新融资轮次的)比例远高于「僵尸」独角兽。相比之下,欧洲、印度、拉美和纽约的「僵尸」独角兽浓度更高。

图注:各国「僵尸」vs「活跃」独角兽市值分布

图注:各城市「僵尸」vs「活跃」独角兽市值分布

美国四大独角兽集群

在美国内部,四个「产业城市」占据了约 76% 的独角兽数量和约 87% 的独角兽市值:湾区、纽约、洛杉矶和波士顿。其中湾区是绝对龙头,独角兽数量是第二名的 2 倍以上,市值是第二名的 4 倍以上。

图注:美国主要城市独角兽数量

图注:美国主要城市独角兽市值

看各城市前十大独角兽的行业分布,可以清晰看到产业城市的聚集效应:

湾区 = AI 集群(前十中 6 家是生成式 AI)
纽约 = 金融科技/加密集群(前十中 7 家)
洛杉矶 = 国防/航天 + 消费集群(前六中 3 家是国防/航天,前十中 4 家是消费)
波士顿 = 相对均衡,但偏向生物科技/医疗(前十中 3 家)

图注:美国四大城市 Top 10 独角兽行业分布

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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.

565 Total ViewsPublished 2025.01.14Updated 2025.01.14

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