[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-dfa4fd62-754c-4c08-b7c4-5f8bc4c7f678":3},{"id":4,"title":5,"summary":6,"content":7,"original_url":8,"source_id":9,"tags":10,"translations":23,"news_slug":29,"published_at":30,"created_at":31,"modified_at":32,"is_published":33,"publish_type":34,"image_url":7,"view_count":35},"dfa4fd62-754c-4c08-b7c4-5f8bc4c7f678","上线一周调用量增 68 倍,腾讯混元 Hy3 在 OpenRouter 全球登顶","腾讯混元大模型 Hy3 自 7 月初正式开源以来表现远超预期——7 月 15 日官方披露,Hy3 在 OpenRouter 全球大模型调用量总榜登顶,总调用量较上代 Hy2 暴涨 68 倍。\n\nHy3 是 295B 总参数、激活仅 21B 的稀疏 MoE 模型,GitHub 自定位 \"reasoning and agent\",主打同尺寸段的推理与 Agent 能力,同时强调成本效率。A21B 这种高稀疏度设计意味着推理时实际激活参数不到总量的 7%,在保留能力的同时把单次调用成本压到\"接近稠密 20B 级\"。这也是它在 OpenRouter 这种\"性价比投票\"聚合平台上能跑出来的根本原因——调用方用脚投票,价格\u002F能力比才是关键。\n\n68 倍增长与 OpenRouter 登顶本质上是开发者社区对\"中国系 MoE + Agent\"组合的一次真实压力测试,而非纸面 benchmark。头部大厂已把\"调用量\"作为开源成功的新指标,意味着 LLM 竞争正从\"谁能训出来\"转向\"谁敢被广泛调用\"。对中型闭源 API 提供商而言,Hy3 这类高性价比开源 MoE 已构成直接挤压。",null,"https:\u002F\u002F36kr.com\u002Fnewsflashes\u002F3896804710647431","d46ec0a7-501b-4ef8-9c89-2391b2701b3b",[11,14,17,20],{"id":12,"name":13,"slug":13,"description":7,"color":7},"120fa59a-ff6f-4537-9bf5-f818df636a0e","benchmark",{"id":15,"name":16,"slug":16,"description":7,"color":7},"a8002d98-9df1-4ab9-94d4-a7625af634c4","china-ai",{"id":18,"name":19,"slug":19,"description":7,"color":7},"01598627-1ea6-4b27-a5d8-874971571a71","llm",{"id":21,"name":22,"slug":22,"description":7,"color":7},"b9bd9039-fcdb-41a8-b85b-fc1587def2b9","open-source",[24],{"id":25,"lang":26,"title":27,"summary":28,"content":7},"7bf0d41e-f1ae-4cec-babd-985b5198eab6","en","Call volume up 68× in one week: Tencent Hunyuan Hy3 tops OpenRouter globally","Tencent's Hunyuan large model Hy3 has performed far beyond expectations since its open-source release in early July — on July 15, the company disclosed that Hy3 has topped OpenRouter's global LLM call-volume leaderboard, with total call volume up 68× over its predecessor Hy2. Hy3 is a 295B-total, 21B-activated sparse MoE model, with GitHub self-positioning as \"reasoning and agent\", focused on reasoning and Agent capabilities in the same size tier, while emphasizing cost efficiency. This A21B high-sparsity design means that at inference, the actually activated parameters are less than 7% of the total, preserving capability while compressing per-call cost to \"close to a dense 20B tier\". This is fundamentally why it can emerge on OpenRouter, a \"price-performance vote\" aggregation platform — callers vote with their feet, and the price\u002Fcapability ratio is what matters. The 68× growth and OpenRouter topping are essentially a real-world stress test of the \"Chinese MoE + Agent\" combination by the developer community, rather than paper benchmarks. The leading labs have made \"call volume\" a new metric for open-source success, meaning LLM competition is shifting from \"who can train it\" to \"who dares be widely called\". For mid-sized closed-source API providers, high-price-performance open-source MoE models like Hy3 already constitute direct pressure.","tencent-hunyuan-hy3-openrouter","2026-07-16T00:01:00Z","2026-07-16T00:05:50.290972Z","2026-07-16T00:05:50.290983Z",true,"agent",108]