谷歌TPU十年磨剑终出鞘，AI算力市场或迎新变局？

ITBEAR科技资讯12-06

上个月科技圈的焦点，无疑落在了谷歌身上。凭借性能强劲的Gemini 3，谷歌不仅在半个月内实现股价攀升，更是在AI竞技场内外掀起波澜——对内挑战OpenAI，对外直指英伟达的市场地位。这一系列动作，让外界对谷歌自研的TPU（张量处理单元）充满好奇，甚至有人猜测其是否会颠覆英伟达的CUDA生态。TPU并非横空出世的新技术。自2015年启动以来，这一专为AI设计的芯片已迭代至第七代。其诞生源于谷歌的...

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Could the AI computing power market usher in new changes?","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"NVDX":0.6,"NVIW.SI":0.6,"NVD3.UK":0.6,"NVDS":0.6,"NVDS.UK":0.6,"NVD2.UK":0.6,"SNVD.UK":0.6,"NVDU":0.6,"NVDY":0.6,"NVDD":0.6,"GOOGL":1.96,"3NVD.UK":0.6,"NVD":0.6,"NVDA":1.91,"2NVD.UK":0.6,"USJW.SI":0.6},"content_text":"上个月科技圈的焦点，无疑落在了谷歌身上。凭借性能强劲的Gemini 3，谷歌不仅在半个月内实现股价攀升，更是在AI竞技场内外掀起波澜——对内挑战OpenAI，对外直指英伟达的市场地位。这一系列动作，让外界对谷歌自研的TPU（张量处理单元）充满好奇，甚至有人猜测其是否会颠覆英伟达的CUDA生态。TPU并非横空出世的新技术。自2015年启动以来，这一专为AI设计的芯片已迭代至第七代。其诞生源于谷歌的痛点：传统GPU在深度学习训练中效率低下，能耗过高。GPU的通用架构虽能处理图形渲染、科学计算等多种任务，但在AI矩阵运算中，数据频繁在显存与核心间搬运，导致大量能耗浪费在“数据搬运”而非“计算”上。谷歌工程师因此决定砍掉GPU中与AI无关的模块，专注于优化矩阵乘法，最终开发出“脉动阵列”架构——数据在计算单元间高效传递，减少存储读写，显著提升能效。初代TPU仅支持推理任务，功能单一，但能效比已达同期英伟达Tesla K80的30倍。随着技术迭代，第二代TPU通过增加内存容量和传输速度，解锁了训练能力；第三代则通过规模化部署，进一步缩短模型训练周期。然而，尽管TPU在成本与性能上具备优势，其市场渗透却长期受限——谷歌始终将TPU绑定在自家云服务中，仅提供租赁而非销售。这种封闭策略让许多企业望而却步：将核心算力依赖单一供应商，风险过高。即便如此，苹果等巨头仍因成本考量，选择部分采用TPU。转机出现在第七代TPU Ironwood的推出。谷歌首次开放TPU销售，打破“只租不卖”的传统。这一决策迅速引发市场反应：meta被曝正与谷歌洽谈数十亿美元合同，计划从2027年起在数据中心部署TPU，并可能提前启动租赁。消息公布后，谷歌股价上涨2.1%，英伟达则下跌1.8%。有内部人士透露，TPU的商业化或使英伟达损失数十亿美元收入，占其年营收的10%。资本市场同样看好这一变化，博通等TPU供应链企业股价随之攀升。尽管TPU来势汹汹，但其颠覆GPU的可能性仍存争议。作为专用集成电路（ASIC），TPU的优化方向高度聚焦于矩阵计算，在AI大模型训练中表现卓越，但缺乏通用性。若未来AI技术路线转向非矩阵运算领域，TPU的专用性可能成为劣势——四年前的TPU v4已因技术迭代而逐渐退出市场。相比之下，GPU凭借CUDA生态的“软实力”构建了深厚壁垒：开发者代码、库优化甚至错误调试均围绕CUDA展开，迁移至TPU需重构代码、适应新环境，甚至掌握特定语言如JAX，这对中小型企业而言成本过高。即便谷歌自身，其云服务仍依赖大量英伟达GPU以满足客户多样化需求。当前，TPU与GPU的竞争更可能形成“专用与通用”的分野：TPU占据头部企业的定制化需求，GPU继续主导通用市场。这种竞争格局或推动算力成本下降，最终惠及整个行业。无论结果如何，科技巨头在算力领域的博弈，已为AI发展的下一阶段埋下伏笔。","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,"symbols":[],"gpt_button":0,"need_auth":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":0,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)","isDev":false,"isTTM":false,"deviceId":"web-server-community-laohu8-v3","version":"4.35.11","shortVersion":"4.35.11","platform":"web","vendor":"web","appName":"laohu8","isIOS":false,"isAndroid":false,"isTiger":false,"isTHS":false,"isWeiXin":false,"isWeiXinMini":false,"isWeiBo":false,"isQQ":false,"isBaiduSwan":false,"isBaiduBox":false,"isDingTalk":false,"isToutiao":false,"isOnePlus":false,"isHuaWei":false,"isXiaomi":false,"isXiaomiWebView":false,"isOppo":false,"isVivo":false,"isSamsung":false,"isMobile":false},"href":"/m/news/2589807810","isCrawlerRequest":true}