[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-010979e2-4e0a-4dcc-8a91-c6a99bfebc04":3},{"id":4,"title":5,"summary":6,"original_url":7,"source_id":8,"tags":9,"published_at":23,"created_at":24,"modified_at":25,"is_published":26,"publish_type":27,"image_url":13,"view_count":28},"010979e2-4e0a-4dcc-8a91-c6a99bfebc04","腾讯混元 Hy3 Preview 开源：295B MoE 剑指 Agent 实用性","4月23日，腾讯发布并开源混元 Hy3 Preview——这是其2026年2月完成预训练与强化学习基础设施重建后推出的首个模型。295B 总参数、21B 激活参数、256K 上下文，核心目标：不再执着 benchmark 刷分，转而剑指 Agent 能力与真实场景落地。Hy3 采用快慢思考融合的混合专家（MoE）架构。这种设计并非腾讯首创——Mixtral、DeepSeek V3 都验证过 MoE 推理效率的优势——但这次的重点在于融合而非单纯堆参数：慢思考处理复杂推理，快思考响应日常任务，21B 激活参数在保证能力的同时控制了推理成本。256K 上下文支持则为复杂 Agent 任务提供了基础。腾讯首席AI科学家姚顺雨强调，他们希望通过自建评测体系规避传统榜单刷分陷阱。这个表态背后是行业共识的变化：头部厂商开始强调真实场景表现而非榜单第一，是行业走向成熟的信号。API 定价低至 1.2 元\u002F百万 Tokens，性价比成为直接卖点。目前 Hy3 已在腾讯云、元宝、QQ、腾讯文档等产品上线，同时支持 OpenClaw、KiloCode 等开源 Agent 框架。与其在通用 benchmark 上硬碰硬，不如在代码生成、Agent 等场景建立开发者生态护城河——这是腾讯的差异化策略。混元重建计划的第一步，能否兑现，社区反馈会是试金石。","https:\u002F\u002Fcloud.tencent.com\u002Fdeveloper\u002Farticle\u002F2660040","d46ec0a7-501b-4ef8-9c89-2391b2701b3b",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"a8002d98-9df1-4ab9-94d4-a7625af634c4","china-ai",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"01598627-1ea6-4b27-a5d8-874971571a71","llm",{"id":18,"name":19,"slug":19,"description":13,"color":13},"b1853a5a-d940-42b7-94f9-0488ee3f2cf7","new-model",{"id":21,"name":22,"slug":22,"description":13,"color":13},"b9bd9039-fcdb-41a8-b85b-fc1587def2b9","open-source","2026-05-08T13:00:00Z","2026-05-08T13:09:43.360530Z","2026-05-08T13:09:43.360539Z",true,"agent",5]