3月曾火爆全网、邀请码被炒至10万元的AI智能体Manus所属公司蝴蝶效应突然被Meta收购。 蝴蝶效应国内关联企业北京蝴蝶效应科技有限公司成立于2022年4月20日，创始人为肖弘。肖弘是一位90后，江西吉安人，毕业于华中科技大学，创业起 点在武汉，曾开发过两款微信生态的插件：微信公众号排版工具壹伴和企业微信客户关系管理工具微伴，卖给一家独角兽公司。 12月30日，Manus在官网发布消息称，"Manus即将加入Meta"，同时Manus将继续通过App和网站为用户提供产品和订阅服务，并继续在新加坡运营。据晚 点，此次Meta收购金额达数十亿美元。 Manus投资人真格基金合伙人刘元撰文提到，Meta创始人扎克伯格是Manus的长期用户，这也是Meta自成立以来第三大的并购，仅次于WhatsApp和Scale AI。合并完成后，蝴蝶效应将在公司、团队和产品层面继续保持独立运营，同时与Meta旗下核心全球消费级产品进行深度整合。 Manus产品邀请码一度被炒至10万元 公开资料显示，Manus系初创公司蝴蝶效应推出的智能体产品。今年3月，该产品风靡科技圈，被称为首款真正意义上的通用AI Agent（智能体）。 ...

北京时间12月30日，Manus官方宣布，"Manus 即将加入 Meta。" 于Manus而言，作为一家初创公司，Meta的收购是对Manus 在通用 AI Agent 领域里工作的认可。于 Meta而言，此次收购系Meta历史上第三大规模收购案，数十亿美元价格仅次于2014年12月190亿美元收 购 WhatsApp，2025年6月140亿美元收购 Scale.ai。 技术路线上，整个大模型赛道迈入基础大模型增长瓶颈，从"无限数据"进入"数据有限"阶段。Gemini 3 预训练负责人之一Sebastian Borgeaud此前表示，规模依然重要，但架构创新和数据创新的权重已显著提 升，甚至变得更为关键。这样的节点，拥有一定规模订阅用户群体以及工程化能力的Manus ，顺势进入 Meta视野。 据Manus官方12月初统计的数据，上线至今，Manus 已处理超过 147 万亿个 token，并创建了超过 8000 万台虚拟计算机。此次与Meta携手，Manus方面表示，将进一步巩固 Manus 在 AI 应用层的战略位置 ——将人工智能能力转化为可规模化、可靠的系统，在实际使用场景中端到端执行用户交给的任务 ...

专注早期投资，欢迎投递商业计划书至 dream@zhenfund.com 以下文章来源于真格基金 ，作者与你同在的 真格基金 . 今早，Manus 突然发文称已经加入 Meta。"对我们而言，这不只是一条新闻，更是对 Manus 在通用 AI Agent 领域里工作的认可。" 根据《晚点 LatePost》报道，Meta 这次收购金额达数十亿美元，是 Meta 成立以来第三大收购，花费仅次于 WhatsApp 和 Scale AI。在 Meta 收购 前，Manus 正以 20 亿美元估值进行新一轮融资，而双方这次收购谈判前后用时仅十余天。 根据公开报道，2024 年初，字节跳动曾试图以 3000 万美元收购 Monica（公司前身） ，但被拒绝了，坚持保持独立。2024 年底，Monica 完成了一 轮融资，估值接近 1 亿美元。Manus 于 2025 年 3 月上线后，Butterfly Effect 在 2025 年 4 月完成了一轮由 Benchmark 领投的 7500 万美元融资，估 值约为 5 亿美元。随后，美国财政部对这笔投资是否符合 2023 年关于投资中国人工智能公司的限制规定进行了审查 ...

Manus被Meta收购了！ 智东西12月30日报道，今天，根据Manus与Meta的官宣公告，Meta收购了爆款通用Agent产品Manus的母公司蝴蝶效应。Manus服务将继续维持 运营和销售，并整合进Meta的消费者与企业产品生态体系。 Manus在X平台官宣收购 Meta超级智能实验室（MSL）负责人Alexandr Wang（汪韬）也转发了相关消息，并配文称Manus团队在探索当今模型的能力过剩问题上，处 于世界一流水平。此外，MSL正在新加坡招聘，Manus团队的100名成员已经加入MSL在当地的组织。 汪韬在X平台转发相关消息 另据晚点报道，这笔交易的规模达到数十亿美元，收购前Manus正以20亿美元的估值寻求新一轮融资。蝴蝶效应的长期投资者真格基金称，这 笔交易是Meta成立以来的第三大收购，花费仅次于WhatsApp和Scale AI。收购完成后，蝴蝶效应创始人兼CEO肖弘将加入Meta，担任Meta副 总裁一职。 Manus称这笔收购是对其在通用AI Agent"开创性工作"的认可。自推出以来，Manus的Agent已处理超过147万亿个token，创建了超过8000万台 虚拟机。 Man ...

在 8 月份宣布突破 9000 万美金年化收入后《 Manus 年化收入突破 9000 万美金，红杉中国投了一个 AI 床垫 》， Manus 昨晚宣布其 ARR 已经突破了 1 亿美金 ，成为从 0 到 1 亿美金 ARR 最快的初创公司。 前几天更新的版本则可以直接通过 Manus 来做移动开发了，这块我之前介绍过专注于开发 App 的 AI Coding 产品，《 创立 6 个月的 AI 卖了 8000 万美 金没融资一个创始人，App 的 AI Coding 也火了 》。 有网友说通过 Manus 开发了一个完整的移动 App，我简单体验了一下让它构建一个 AI 笔记产品，效果还不错，包括后端、数据库这些全都自己设计好 了，我只需要集成一个 OpenAI 的 API 即可，并且给出了发布到 App Store 的指南。 Manus 没有公布用户的分布情况，不过我在 X 上简单做了一下搜索，发现有不少日本用户分享了通过 Manus 做各种产品的帖子，特别是用它来做移动 App 和 Web 产品这块，我估计来自日本的用户有不少比例。 Manus 的总收入年化运行率则超过了 1.25 亿美金，这块数据包含了 ...

Core Insights - OpenAI officially launched ChatGPT Agent on July 17, marking its entry into the general AI Agent market, which is anticipated to reshape the internet landscape and become a trillion-dollar traffic entry point [1][50] - The emergence of ChatGPT Agent raises questions about whether the market will be dominated by tech giants or if startups can maintain a foothold due to technological barriers and differentiated approaches [1][39] Summary by Categories 1. ChatGPT Agent Launch - The introduction of ChatGPT Agent signifies the opening of the general AI Agent battlefield, with OpenAI's CEO Sam Altman and researchers presenting the product in a live stream [1] - The launch is seen as a strategic move ahead of the anticipated GPT-5 release, suggesting a competitive response to emerging AI startups [1] 2. Functionality and Tools - ChatGPT Agent can assist users in various tasks, such as ordering products online or generating presentations, driven by two tools: Deep Research and Operator [2][4] - Deep Research focuses on in-depth analysis and report generation, while Operator allows users to perform specific actions on the web [4] 3. Technical Approaches - The article outlines four main technical approaches in the AI Agent space: - **Browser-based Approach**: OpenAI's ChatGPT Agent operates primarily through web browsers, allowing extensive access to online information but suffers from slow performance and high token consumption [7][12] - **Sandbox + Browser Approach**: Manus combines a sandbox environment with browser capabilities, offering high local execution efficiency but limited external access [14][20] - **Large Model + Sandbox Approach**: GensPark utilizes a large language model within a sandbox, sacrificing generality for speed and stability, focusing on specific tasks [24][28] - **Workflow + Tool Integration Approach**: Companies like Pokee integrate pre-designed workflows with third-party tools, resulting in faster execution but limited generality [32][34] 4. Future of AI Agents - The competition in the AI Agent market is expected to intensify, with the potential for agents to become the primary means of internet interaction, leading to a decline in traditional web traffic [39][41] - The concept of "ghost clicks" suggests that future internet traffic will be driven by agents rather than human users, fundamentally altering advertising and information dissemination models [41][45] 5. Market Dynamics - OpenAI's entry into the general AI Agent market is seen as a pivotal moment, with implications for both existing companies and new entrants aiming to capture market share [1][42] - The article emphasizes the need for companies to enhance user retention and reliability through specialized workflows and tools, rather than solely relying on broad capabilities [36][37]

Core Insights - The introduction of ChatGPT Agent marks the beginning of a competitive landscape for general AI agents, potentially reshaping the market dynamics and becoming a significant traffic entry point for the next generation of the internet [2][3][64]. Group 1: ChatGPT Agent Overview - OpenAI's ChatGPT Agent was introduced on July 17, showcasing its ability to assist users in various tasks, such as ordering products or generating presentations [4][5]. - The ChatGPT Agent integrates two previously separate tools, Deep Research and Operator, to combine search and execution capabilities [8][10]. Group 2: Technical Approaches in AI Agents - There are four main technical approaches in the AI agent landscape: browser-based, sandbox virtual machine, large model with sandbox, and workflow plus tool integration [11][59]. - The browser-based approach, exemplified by OpenAI's ChatGPT Agent, offers high versatility but suffers from slow performance and high token consumption [12][15][20]. - The sandbox virtual machine approach, represented by Manus, provides high local execution efficiency but has limited access to external services [23][33][38]. - The large model with sandbox approach, as seen in GensPark, sacrifices generality for speed and stability, focusing on specific workflows [40][51]. - The workflow plus tool integration approach, utilized by companies like Pokee, emphasizes speed and delivery but lacks general applicability [52][57]. Group 3: Market Dynamics and Future Trends - The competition in the AI agent market is expected to intensify, with the potential for new companies to emerge as leaders [66][69]. - The concept of "ghost clicks" suggests that future internet traffic will be driven by agents rather than human users, leading to significant changes in advertising and content monetization [67][72]. - OpenAI's ChatGPT currently handles approximately 2.5 billion user commands daily, equating to an annualized volume of 912.5 billion, which represents 18% of Google's annual search volume [75][76].

Core Insights - OpenAI has entered the general AI Agent market with the launch of ChatGPT Agent, aiming to capture future "traffic entry points" [1] - The product is perceived as a hasty response rather than a well-thought-out strategy, with subpar performance according to industry experts [1] - Existing competitors like Manus and Genspark have already established their presence in the Agent space, raising questions about OpenAI's technological differentiation [1] Technology Analysis - The current landscape of general AI Agents features four major technological factions: browsers, virtual machines, large language models, and workflow integration [1] - Each faction has its own operational principles and advantages, as well as drawbacks, highlighting the trade-offs made between "universality" and "stability" [1] Future Implications - As AI Agents become the primary interface for internet interactions, traditional web traffic is expected to decline rapidly, leading to significant shifts in the competitive landscape among major players [1] - The advertising ecosystem is likely to be disrupted, prompting a reevaluation of strategies by companies in this space [1] - The question remains as to which entity will emerge as the ultimate winner in this trillion-dollar traffic entry point battle [1]

Core Viewpoint - The article emphasizes the rapid growth and potential of AI Agents, predicting that 2025 will be a significant year for their widespread application across various industries, enhancing efficiency and creating substantial business value [2][3]. AI Agent Market Overview - OpenAI's founder Sam Altman predicts that AI Agents will save time and improve efficiency across industries, acting as "digital employees" capable of performing tasks like research, booking flights, and coding [2]. - The Chinese AI Agent market is projected to exceed 850 billion yuan by 2028, with a compound annual growth rate of 73% [4]. Investment Trends - Major tech companies like Microsoft and Google are heavily investing in AI Agents, with Microsoft CEO Satya Nadella stating that Agents will drive more applications [6]. - In China, startups like Manus and Genspark have gained significant attention and funding, with Manus raising $75 million and Genspark securing $160 million in investments [7][8]. Competitive Landscape - The article highlights a shift in investor sentiment towards vertical AI Agents rather than general-purpose ones, as large companies dominate the general market [4][10]. - Investors believe that focusing on niche markets will yield better opportunities compared to broad consumer-targeted AI Agents [4][10]. Challenges for General AI Agents - The entry of large companies into the general AI Agent space is seen as a threat to startup projects, which may struggle without sufficient resources and technology [11]. - Existing general AI Agent startups like Manus face challenges in scaling and competing against established players with more resources [11]. Vertical AI Agent Opportunities - Vertical AI Agents are gaining traction, with several startups receiving significant funding for specialized applications in areas like design and customer service [14][15]. - Companies that leverage existing industry knowledge and customer bases to develop vertical AI Agents are likely to have a higher success rate [16]. Future Outlook - The article suggests that while vertical AI Agents currently have an edge, the evolving landscape may allow for opportunities in both vertical and general AI Agent markets [25]. - The integration of generative AI into daily life is expected to continue, with significant increases in usage metrics reported by major platforms [21].

Group 1 - Manus AI has opened access to its product, allowing all users to complete one task daily for free and earn 300 points, along with a one-time bonus of 1000 points [1] - The product, Manus, was previously in high demand with 2 million users on the waiting list, and its invitation codes were sold for as much as 100,000 yuan on secondary markets [1] - Manus is described as the first true general-purpose AI agent capable of independent thinking, planning, and executing complex tasks [1] Group 2 - Manus AI has formed a strategic partnership with Alibaba's Tongyi Qianwen team to develop a Chinese version of Manus, leveraging open-source models and local computing platforms [2] - The company recently completed a funding round led by Silicon Valley venture capital firm Benchmark, raising $75 million (approximately 546 million yuan) [2] - This funding round has increased Manus AI's valuation to nearly $500 million (approximately 3.644 billion yuan), representing a fivefold increase from its previous valuation [2]