争夺AI制高点，谷歌和Anthropic必有一战

字母榜01-20

刚发布Cowork的Anthropic又要融资了。知情人士透露，这家公司正在敲定一轮250亿美元的巨额融资，距离上次融资仅仅过了两个多月。为什么Anthropic如此迫切地需要资金？原因很简单，2026年AI大厂之间的竞争，已经不再是模型参数和跑分了，开发者体验和Agent能力转而成为了新贵。例如，智谱首席科学家唐杰此前表示，随着DeepSeek横空出世，Chat范式的探索已经基本结束，因此公司...

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IDE（Agent优先集成开发环境），强调Agent是核心设计理念，而非传统IDE的辅助功能。内置的Mission Control面板允许开发者管理多个自主运行的Agent，这些Agent可以并行处理任务、浏览网页查找文档、甚至在终端中执行命令。从功能上看，Antigravity试图在多任务并行上做出差异化，但核心逻辑仍然是让AI代理替开发者完成编程工作。但是，Antigravity不止原生支持Google自家的Gemini 3 Pro、Deep Think和Flash模型，它同时也支持Anthropic的Claude Sonnet 4.5和Opus 4.5。这个决定背后的逻辑很直白，哪怕开发者更喜欢Claude的模型，谷歌也要确保他们留在谷歌的IDE生态中。话又说回来了，这种策略本身也是一种妥协。作为AI大厂，谷歌在自己的开发工具里支持竞争对手的模型，这在以往是难以想象的。但现实摆在面前，Claude模型更聪明，更会编排任务，更懂开发者。开发者对Claude模型拥有粘性，但对IDE还没有。就像同样是下单麦当劳的外卖，美团和淘宝闪送在优惠力度、派单时间等方面就是不一样。IDE在开发过程中也和平台类似，即便模型相同，输入的需求相同，但是最后得到的结果也是不同的。然而从市场反馈来看，Antigravity的表现并不如谷歌预期。CB Insights的报告显示，在2025年末的AI编程工具市场份额统计中，Antigravity的采用率远低于Cursor和GitHub Copilot这些老牌工具。开发者社区的讨论也印证了这一点，大多数人认为Antigravity的多Agent管理功能虽然新颖，但在实际使用中并不如单一强大的Agent来得高效。不过，Antigravity也并非毫无亮点。Linux之父林纳斯·托瓦兹（Linus Torvalds）此前启动AudioNoise项目，尝试使用Antigravity进行Vibe Coding，比如利用AI生成Python代码，以辅助音频处理工作。林纳斯在项目的README文件中坦言，他对Python并不熟悉，过去通常是通过搜索和复制粘贴来完成Python编程，但现在他干脆跳过这个中间环节，直接让Antigravity来生成代码。林纳斯的背书确实为Antigravity带来了一些关注度，但这个案例本身也暴露了Antigravity的定位问题。AudioNoise只是一个业余项目，Torvalds用AI生成的也只是他不擅长的Python可视化工具部分，核心的C语言音频处理逻辑仍然是他手写的。换句话说，即便是林纳斯这样的顶级程序员，也只是把Antigravity当作一个辅助工具，用来处理自己不熟悉的边缘任务。这恰恰说明了谷歌面临的困境。Claude Code已经可以为开发者处理复杂的编程任务，而Antigravity还停留在辅助工具的层面。02谷歌并非没有优势。事实上，如果单从资源和技术积累来看，谷歌拥有Anthropic难以企及的全栈能力。从芯片到云服务，从模型训练到应用部署，谷歌可以在每个环节进行优化。但问题在于，这种全栈优势在编程工具这个细分市场上，并没有转化为实际的竞争力。前文提到的Cowork，就是一个很好的例子。2026年1月，Anthropic推出了Cowork，这是一个桌面应用功能，让Claude可以直接访问用户电脑上的文件夹，执行复杂的多步骤任务。Cowork的推出进一步扩展了Claude的应用场景，从纯粹的编程工具延伸到了更广泛的知识工作领域。在开发过程中，Anthropic团队主要依靠Claude Code来生成Cowork的代码。换句话说就是，Anthropic已经实现了由AI构建AI，今天能推出Cowork，明天就有可能推出性能更强大的产品。相比之下，谷歌在应用层的动作显得迟缓。谷歌确实也有类似Cowork的产品，叫做Gemini CLI。这个工具在功能上与Cowork相似，可以访问本地文件并执行任务。但问题在于，Gemini CLI并不是用Antigravity开发的，而且只能通过命令行操作，不能像Cowork那样提供图形界面让用户直观地进行交互。从AI编程工具上看，Anthropic从一开始就把Claude Code定位为开发者的协作伙伴，强调长时间、复杂任务的处理能力。而谷歌的Antigravity更像是一个功能集合，通过堆砌特性来吸引用户。OpenAI在这个领域的存在也不容忽视。虽然OpenAI的Codex和GitHub Copilot在市场份额上不如Claude Code，但它们有着别样的优势，那就是与微软的合作，深度绑定GitHub生态将AI编程能力直接嵌入到开发者最常用的平台中。这种策略虽然不如Anthropic激进，但胜在稳健。虽然说了那么谷歌的不好，然而谷歌也有自己的杀手锏，那就是硬件基础设施层的优势逐渐放大。这一点在谷歌与Anthropic的芯片合作上体现得尤为明显。在应用层打得不可开交的同时，谷歌和Anthropic在基础设施层却保持着密切的合作关系。2025年末，Anthropic宣布，将直接采购近100万颗谷歌TPU v7芯片，代号Ironwood。根据SemiAnalysis的分析，这笔交易价值420亿美元，预计将为Anthropic提供超过1GW的算力容量。Anthropic选择TPU而非英伟达GPU，主要基于经济和技术考量。与英伟达的GB200服务器相比，TPU v7集群的总拥有成本降低了约30-44%。在性能方面，TPU v7相比上一代TPU v5p，性能提升了近10倍。每颗TPU v7芯片可以提供4.6 petaFLOPS的FP8计算能力，这个数字与英伟达的B200基本持平，甚至略高一些。而在能效比上，TPU v7更是表现出色，功耗约为600W，远低于英伟达GPU动辄1000W以上的功耗。最关键的是生态兼容性。Claude 4.5 Opus是Anthropic采用多元化算力策略所训练出来的模型，同时可以运行在亚马逊Trainium、英伟达GPU以及谷歌TPU上。TPU在这里面负责算力补充和特定算法优化。一切大模型的基石是Transformer架构，而TPU的脉动阵列（Systolic Array）架构专为Transformer层的大规模矩阵运算设计，相比GPU在同等功耗下矩阵计算效率提升30-80%。而在推理方面，Anthropic通过可以TPU的优化，实现推理时动态激活专家层，减少无效计算，降低延迟。而GPU每一次推理，都必须使用内存进行读写，会浪费大量的电力。换句话说，Anthropic想要让自家的模型用起来更省钱，那他们就更需要TPU，而不是GPU。从供应链角度看，这笔交易也有深层次的战略意义。英伟达GPU产品供不应求的局面已经持续了两年，即便是OpenAI和Meta这样的大客户，也经常面临交付延迟的问题。通过与谷歌的合作，Anthropic打破了对英伟达生态的单边依赖，获得了谷歌的供应保障。对于谷歌来说，这笔交易同样意义重大。谷歌的TPU业务长期以来主要服务于自家的AI训练需求，外部客户相对较少。Anthropic的百万芯片订单不仅带来了可观的收入，更重要的是验证了TPU在商业市场上的竞争力。如果Anthropic能够成功利用TPU训练出更强大的Claude模型，那将是对TPU技术的最好背书。对于谷歌来说，这是一种东边不亮西边亮的策略。即使Gemini没有在应用层战胜Claude，谷歌也会因为Claude逐渐绑定TPU而从中获利。TPU芯片的销售、云服务的租赁、技术支持的费用，这些都是实实在在的收入。而且，随着Anthropic对TPU依赖度的提高，谷歌在这段关系中的话语权也会逐渐增强。但这种策略也有风险。如果Anthropic利用谷歌的TPU训练出了远超Gemini的模型，那谷歌在应用层的竞争将变得更加困难。到那时，谷歌可能会面临一个尴尬的局面，自己的基础设施在支撑竞争对手的成功。03如果说技术和硬件是战争的武器，那么资本就是这场战争的燃料。而在资本层面，Anthropic展现出了惊人的融资能力。2026年初，Anthropic预计完成一笔规模超过250亿美元的融资，这将使其估值达到3500亿美元。要知道，2024年3月，Anthropic的估值还只有615亿美元。到2025年11月，这个数字已经涨到1830亿美元。短短几个月后，估值再次翻倍，直逼OpenAI。支撑这3500亿美元估值的，是实打实的收入增速。Anthropic在其F轮融资公告明确记载，2025年年化收入约10亿美元，在2026年将会达到152亿美元。这种15倍的增长速度是非常夸张的。更重要的是，这种增长不是靠烧钱补贴换来的，而是来自API和订阅的真实付费。投资者看到的不再是一个需要持续输血的研究机构，而是一个有清晰商业模式、能够自我造血的科技公司。Claude Code的成功正是这种转变的最好证明，通过Cowork，它证明了Claude Code不仅是一个技术产品，更是一个可以带来稳定收入的商业产品。本轮融资由Coatue Management和新加坡主权财富基金GIC领投。不过在这之中发生了一件很有意思的事情，红杉资本同时下注了OpenAI、xAI和Anthropic。这种买下整个赛道的打法，在风险投资历史上并不常见。红杉的这一转变发生在其高层人事变动之后。红杉前任负责人鲁洛夫·博塔（Roelof Botha）对于向少数高估值初创公司集中投资持谨慎态度，他曾公开表示，向硅谷砸更多的钱并不能产生更多伟大的公司。但在2025年11月鲁洛夫卸任后，新的领导层显然采取了不同的策略。现在的红杉认为，Anthropic的这笔融资规模如此之大，它已经从风险投资转变为了一种股票投资。红杉持有大量OpenAI和xAI的股份，同时也看好Anthropic，因为这不是一场非此即彼的竞赛，这些公司各自都将拥有独特的能力。在AGI时代，赢家可能不止一个。不同的AI公司会在不同的细分领域占据优势，而不是像传统互联网时代那样，一家独大通吃市场。从这个角度看，红杉的全赛道押注是一种理性的风险对冲。毫不夸张地说，在AI领域，资金本身就是一条护城河。没有百亿美元的入场券，已经无法留在牌桌上。训练一个前沿大模型的成本已经达到数亿美元，而要维持持续的迭代和优化，每年需要投入的资金可能达到数十亿美元。这种资金门槛将大部分玩家排除在外，也只有那些能够持续获得大规模融资的公司才能继续玩下去。微软和英伟达在这轮融资中承诺的投资约为150亿美元。而Anthropic又表示，拿到融资后，很大一部分资金需要用于购买算力。如果Anthropic需从微软Azure采购算力，GPU使用的是英伟达的，这就又变成了左手倒右手的循环，使得云厂商和芯片巨头通过投资锁定了未来的收入。实际上这种资本循环在AI行业已经是常态了。大型科技公司既是AI创业公司的投资者，又是它们的供应商。这种双重身份带来的好处是显而易见的，投资可以获得股权回报，而供应商身份则可以获得稳定的收入。AI创业公司的很大一部分融资，最终会回流到这些大型科技公司手中。Anthropic还透露，公司已聘请知名律所Wilson Sonsini筹备上市事宜，预计将在2026-2027年期间IPO。如果这个计划成真，Anthropic可能比OpenAI更早上市。这将是一个标志性事件，意味着AI行业开始进入成熟期，从纯粹的技术竞赛转向商业化和资本化。相比之下，谷歌虽然也有钱，却没办法像Anthropic一样，在AI编程领域如此专一。谷歌是一家市值超过4万亿美元的巨头，AI只是其众多业务之一。谷歌的主要收入来源是广告，因此谷歌对AI的态度是通过AI来强化以广告为主的现有业务。这种多元化既是优势，也是劣势。优势在于谷歌有足够的资金和资源支撑长期投入，劣势在于注意力和资源必然会被分散。Anthropic可以将所有资源集中在Claude的开发和优化上。这种专注度带来的效率提升是显而易见的。从Claude 3到Claude 4.5，Anthropic的迭代速度远超谷歌的Gemini系列。而Claude Code从推出到占据市场主导地位，也只用了不到一年时间。从长期来看，AI编程的结果可能不会是简单的赢家通吃。谷歌凭借其全栈能力和基础设施优势，在企业市场和大规模部署场景中仍然有很强的竞争力。而Anthropic则可能在开发者工具和高端应用场景中保持领先。两家公司的竞争，更像是在不同维度上的较量，而不是在同一条赛道上的直接对决。但有一点是确定的，编程这块AI高地的争夺，已经成为决定AI行业格局的关键战场。这不仅仅是因为开发者是AI工具的直接用户，更重要的是，开发者是整个数字世界的建设者。掌握了开发者，就掌握了未来软件的生产方式，这才是这场战争真正的意义所在。","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":0,"need_auth":false,"need_login_tip":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":1,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; 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