腾讯AI，翻身了吗？

定焦One07-13

文 | 定焦One 陈丹编辑 | 魏佳在大模型密集交卷的上周，前OpenAI研究员姚顺雨，也交出了加入腾讯后的第一份正式答卷。7月6日，腾讯发布混元Hy3正式版。没有声势浩大的发布会，也没有铺天盖地的营销，这款旗舰模型以一种不太符合大厂惯例的低调方式进入市场。但在开发者一端，它激起的水花并不小。上线三天后，处于限时免费阶段的Hy3升至全球大模型API调用平台OpenRouter最受欢迎模型榜单...

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魏佳在大模型密集交卷的上周，前OpenAI研究员姚顺雨，也交出了加入腾讯后的第一份正式答卷。7月6日，腾讯发布混元Hy3正式版。没有声势浩大的发布会，也没有铺天盖地的营销，这款旗舰模型以一种不太符合大厂惯例的低调方式进入市场。但在开发者一端，它激起的水花并不小。上线三天后，处于限时免费阶段的Hy3升至全球大模型API调用平台OpenRouter最受欢迎模型榜单第八位。接入腾讯办公智能体WorkBuddy后，调用量迅速冲高，排队率一度超过50%，项目组不得不紧急扩容。资本市场也给出反应，发布当天，腾讯股价上涨4.82%。这多少有些出人意料。过去两年，阿里、字节不断加码模型、应用和算力基础设施，智谱、DeepSeek等AI公司也各自凭借爆款模型刷足了存在感。唯独腾讯，常被排除在国内大模型第一梯队之外。它有微信、QQ和庞大的产业生态，却始终没有拿出一款足以改变行业判断的基础模型。外界甚至开始怀疑，腾讯究竟是在等待更合适的入场时机，还是已经在这一轮技术竞赛中慢了下来。现在看来，腾讯没有躺平。引入姚顺雨并重组混元研发体系之后，腾讯近期又被曝吸纳其前同事田永龙。模型之外，腾讯还参与了可灵最高30亿美元的融资，并传出洽谈成为AI智能体公司Manus最大股东的消息。从人才、模型到基础设施，这家过去两年显得过于克制的互联网巨头，正在重新提高对AI的下注力度。Hy3还不足以证明腾讯已经追上所有对手，它更像是一个阶段性信号。腾讯重新建立了一套能够把模型、产品和工程体系连接起来的研发方法，也重新获得了进入开发者主流候选清单的机会。但这只是第一步。对腾讯而言，真正的问题已经不只是能否再造出一款更强的模型，而是这种能力能否连续迭代，以及它最终能否在微信里变成一个真正被用户使用、能够完成任务和交易的Agent。01 Hy3不是最强，但够腾讯重回牌桌只看参数和公开榜单，Hy3并不是一款一眼可见的“最强模型”。在这一轮国产模型更新中，DeepSeek V4 Pro、智谱的GLM-5.2、MiniMax M3都在争夺能力上限：有的将总参数推至万亿级，有的把上下文拉到100万Token，有的在代码和长程Agent任务中占优。相比之下，Hy3总参数为2950亿，支持256K上下文，并没有试图在每一项指标上压倒对手。判断它的真实位置，需要看两件事。第一，是它在具体任务中的能力边界。在衡量软件工程能力的SWE-bench Verified上，Hy3获得78分，落后于Claude Fable 5等闭源模型，也排在GLM-5.2和DeepSeek V4 Pro之后。但在难度更高的SWE-bench Pro上，Hy3以57.9分反超DeepSeek V4 Pro。在更接近真实执行环境的WildClawBench上，它又超过GLM-5.1和DeepSeek V4 Pro，位居开放模型前列。腾讯组织的270名专业人员盲测则显示，Hy3整体表现高于GLM-5.1，优势集中在前端开发、数据存储和持续集成等场景。资深Agent从业者赵江杰告诉“定焦One”，Hy3目前处于“整体能力第二梯队上沿、开放与低成本模型第一梯队”。它在前端开发、常规代码、搜索浏览和工具调用上具备较强竞争力，但还没有在高难度任务上全面领先。实际使用中，高频、中低难度且结果可验证的任务，已经可以由它独立完成；中等复杂任务可以交由它执行后复核；核心架构设计和敏感操作，仍不适合无监督交付。因此，如果“赶上”意味着成为能力最强的国产模型，Hy3还没有做到；但如果意味着重新进入开发者的视野，腾讯已经重新拿到了一张入场券。第二，是它对工程化落地和成本控制的重视。Hy3采用MoE架构，总参数2950亿，单次推理只激活约210亿参数。它没有不断堆高峰值能力，而是在模型容量、运行速度和算力成本之间寻找平衡。对企业而言，模型成本不只是单次Token价格。一个Agent完成任务，往往需要多轮推理、连续调用工具、读取和修改文件，并反复核验中间结果。当使用规模扩大到数千名员工，单次调用中微小的成本差异，会被并发量和任务链条迅速放大。更少的激活参数，意味着Hy3具备降低推理开销和部署门槛的架构基础。但激活参数少，并不天然等于真实成本低。赵江杰指出，模型效率还取决于硬件、量化方式、推理框架、上下文长度、输出长度、并发规模和任务成功率。腾讯目前证明的是Hy3有降低成本的可能性，但在统一条件下，Hy3还需验证能否提供更低的首Token延迟、更高的吞吐量，以及更低的成功任务成本。稳定性同样是成本的一部分。企业需要的不一定是模型偶尔表现惊艳，而是在几十次连续调用中少出错、不失忆、不中断。腾讯公布的数据显示，Hy3在不同Agent框架下运行SWE-bench Verified时，准确率波动被控制在4%以内；在内部场景中，幻觉率和多轮对话问题率也明显下降。赵江杰介绍，市场对Hy3的实际评价，更接近“一款工程型、性价比突出、Agent倾向明显，但复杂认知任务还不够均衡的模型”，而不是一款全面领先的通用模型。Hy3 Preview发布后，日均Token消耗增长20倍，WorkBuddy中主动选择该模型的用户增长6倍。正式版上线后，WorkBuddy算力消耗迅速触顶，排队率一度超过50%，联合项目组紧急调度算力扩容。与此同时，腾讯将Hy3接入元宝、CodeBuddy、ima和Marvis等产品，用于生成文档、制作表格、编辑文件、管理电脑和编排工作流。它的热度也没有局限在腾讯体系内。在OpenRouter 7月的编程模型使用量排名中，Hy3进入前四，与GLM-5.2、MiniMax M3和DeepSeek V4系列处于相近的调用梯队。但这些数据仍需谨慎看待。目前Hy3在OpenRouter限时免费，WorkBuddy的调用增长，也可能受到积分、限免和内部导流影响。真正的考验，要等到免费期结束之后。即便如此，Hy3已完成了混元过去未完成的一步：让外部开发者愿意主动试用，让腾讯内部产品开始把真实任务交给它。它没有证明腾讯拥有最强模型，但证明腾讯重新拥有了一款“能用的模型”。02 混元真正补的，是造模型的方法谈及国内互联网巨头的AI布局，不少从业者过去对腾讯的评价很直接：场景很多，但大模型不行。混元早在2023年就已经发布。此后两年，腾讯不断补齐参数规模、多模态和长上下文能力，也将模型陆续接入会议、文档、广告、游戏和云服务。但相比以开源建立开发者生态的阿里，或凭借推理能力和低成本突围的DeepSeek，混元始终缺少一个足够清晰的位置。马化腾曾用“漏水的船”形容腾讯在AI浪潮中的处境，看似已经上船，却还没有坐稳。落到混元身上，真正的漏洞不在于腾讯没有产品、场景或数据，而是它没有把这些资源持续转化成模型进化的能力。最初的混元，走的是一条典型的“大而全”路线：先训练一款覆盖尽可能多任务的通用底模，再接入腾讯云和内部业务。这种方式帮助腾讯迅速补课，也让混元陷入同质化竞争。各项能力都有，但开发者很难找到必须选择它的理由。元宝接入DeepSeek，是腾讯第一次明显把产品体验放在模型归属之前。对用户而言，重要的是任务能否完成，而不是底层调用了哪一家模型。外部模型可以帮助腾讯迅速补齐产品短板，也能让它更快看清用户真正需要什么。这是腾讯对模型与产品关系的一次调整：产品不再必须等待自研模型成熟，模型也不再天然拥有内部流量。但这条路同样有边界。如果腾讯的应用长期建立在别人的模型之上，它掌握的只是入口，而不是AI时代的技术供给。模型价格如何调整、能力何时升级、敏感数据能否处理、产品反馈能否进入训练闭环，都将取决于外部供应商。多模型策略可以争取时间，却不能替代一款自主、可控且能够持续迭代的基础模型。真正的变化，发生在姚顺雨加入、混元研发体系重组之后。2025年9月，姚顺雨从OpenAI转投腾讯；同年12月，腾讯正式任命其为首席AI科学家，同时负责大语言模型和AI基础设施。他的加入，是腾讯重新组织混元研发体系的标志性事件。从此之后，模型、算力、数据和评测，开始被纳入一条更集中的决策链。腾讯没有急着训练一个参数更大的模型，而是先重做造模型的基础工程：重建预训练和强化学习系统，扩充和清洗数据，重新调整后训练流程。公开榜单也不再是唯一标准，真实产品反馈、人工盲测和内部任务，开始进入评测体系。Hy3正是这套方法下的第一批结果。它集中解决推理、代码、工具调用和长程Agent任务。研发顺序也被倒转过来，先确定办公、编程和知识管理需要什么样的模型，再反推架构、数据和训练方式。产品也不再只是模型完成后的分发渠道，而成为训练体系的一部分。姚顺雨在今年6月的腾讯云AI产业应用大会上表示，重新出发的混元模型坚持与产品深度Co‑Design，通过多产品数据回流与体系化训练，在优化模型尺寸的同时持续提升性能。赵江杰认为，Hy3对腾讯的意义，超出一款模型本身。它为模型成本建立了锚点，让产品反馈重新进入训练闭环，也检验腾讯能否把分散在微信、办公、云服务和开发工具中的应用生态，组织成真正的执行能力。过去两年，腾讯真正缺的，是一套能够稳定造出模型、让模型进入产品，再让产品反馈推动模型继续进化的方法。Hy3暂时证明，这套循环开始重新运转，但一次成功还不足以证明腾讯已经建立起长期竞争力。03 混元之外，腾讯还差什么？Hy3让腾讯重新拥有了一台可用的自研发动机，但这台发动机在腾讯的AI版图里，还不足以驱动一切。腾讯总裁刘炽平在3月财报会上表示，AI不会是一场只产生一个冠军的竞赛。“大量现有应用将推出自身智能体与智能体能力，不同模型也将竞争赢得智能体的采用。这是一个更精彩、去中心化、人人可参与的世界。”腾讯首席战略官詹姆斯·米切尔所将其描述为一条“性价比曲线”：未来成功的智能体，会根据不同任务的能力要求和成本约束，自主选择合适的模型；不同模型，则分布在这条曲线的不同位置。“我们希望成为其中一员，而不是唯一选择。”按照这一判断，未来的AI市场不会由某一个模型包揽所有需求，而会形成一个由模型、智能体、应用和基础设施共同组成的多层竞争格局。这也决定了混元的角色：它不足以被腾讯拿去和别人拼胜负，但它是腾讯不能没有的底盘。未来，混元不需要包揽腾讯体系内的所有任务，也不必成为每一款产品的默认模型。高难度、低频任务可以调用能力更强的外部模型；高频、敏感、需要私有化部署或对成本要求更高的任务，则更多交给自研模型。但这不意味着混元不重要。赵江杰将自研模型的战略价值概括为：成本锚点、供应安全、产品共训、私有化合规、持续学习能力，以及参与下一代技术竞争的资格。没有自研模型，腾讯的产品依然可以借助外部供应商迅速补齐体验，但它会在AI最关键的生产函数上长期受制于人。真正决定腾讯AI天花板的，是另一套东西。腾讯手里的牌是14亿微信月活入口、身份权限体系、小程序工具生态、支付与交易能力、企业微信里的组织流程，以及云基础设施。与对手相比，阿里有电商和云但没有社交入口，字节有流量但在小程序工具生态和企业组织侧深度不足，DeepSeek和智谱在模型层强却没有生态。腾讯在“模型-入口-工具-交易”这条链路上更加完整。但理论上的优势还没有直接变现。真正的商业价值，取决于它能够成功完成多少任务，这些任务本身有多大价值，调用成本有多高，以及执行失败可能带来多大风险。正如赵江杰所说，一款能力只有90分，却能以较低成本、安全地调用微信身份、小程序、企业流程和支付系统的模型，可能比一款能力达到100分、却只能返回文本的外部模型更有商业价值。这也指向腾讯AI战略真正需要补上的两块能力。第一，是连续多个版本保持前沿水平的模型能力。Hy3暂时缓解了腾讯在这一环上的焦虑，但一次追赶，还不足以证明长期竞争力。一款模型偶尔在某几个榜单上取得高分，与一家企业能够连续多个版本稳定处于前沿，是两件不同的事。前者可能来自一次架构选择、数据调整或训练周期，后者则要求组织、算力、数据、人才和产品反馈持续协同。第二，是一个被用户高频采用、可信可控的微信原生Agent。腾讯生态里的每一块拼图都很硬，但它们至今没有被一款产品完整串联起来。微信里被寄予厚望的原生Agent“小微”仍在灰度测试，能否真正调动小程序、调用支付、完成交易，都没有答案。只有当模型能够调动腾讯生态中的工具、服务和交易能力，微信的入口优势才会真正转化成AI时代的执行优势。因此，腾讯AI战略未来的检验标准，最终可以被归结为两条线：技术端，混元能否连续迭代，形成长期优势；产品端，腾讯能否造出一个超级原生Agent。用户留存、付费率、任务成功率、生产流量和收入规模，都是这两条线上的具体指标。赵江杰表示，如果混元长期无法承接大规模生产流量，不能服务敏感数据和私有化场景，也无法通过腾讯的产品反馈形成独特能力，它最终可能只是一项昂贵的技术储备。如果微信Agent始终停留在聊天、搜索和内容生成层面，无法进入工具调用和交易环节，腾讯庞大的生态也很难自动转化成AI优势。腾讯AI的考验，还将继续。","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":false,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":1,"need_auth":false,"need_login_tip":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":0,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"CCBot/2.0 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