[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-qwen3-coder-next-80b-3b-active-gated-deltanet":3,"topics-all":36,"news-related-0c28281d-1b70-4206-ae2d-3219f1e4fbb9":55},{"id":4,"title":5,"summary":6,"content":6,"original_url":7,"source_id":8,"tags":9,"translations":23,"news_slug":29,"published_at":30,"created_at":31,"modified_at":32,"is_published":33,"publish_type":34,"image_url":13,"view_count":35},"0c28281d-1b70-4206-ae2d-3219f1e4fbb9","Qwen3-Coder-Next：稀疏MoE架构重塑代码智能效率边界","5月8日，阿里Qwen团队发布Qwen3-Coder-Next，一款专为主动式编程（Agentic Coding）设计的80B参数MoE模型，每次前向传播仅激活3B参数，却具备与Dense模型相当的编程能力，引发开放权重社区广泛讨论。\n\n核心技术在于Gated DeltaNet配合Gated Attention，将Attention的二次计算复杂度转为线性，使模型得以在维持262K token超长上下文的同时避免指数级延迟惩罚。在仓库级任务中，吞吐量比同级别Dense模型提升约10倍。训练阶段引入Best-Fit Packing策略，有效缓解了长上下文场景下的幻觉问题，保持了上下文信息的完整性。\n\n该模型以Apache 2.0许可证开源，权重已在HuggingFace发布4个变体，并附有详细技术报告。在编程Agent成为行业竞争焦点的当下，小激活、大能力的稀疏MoE设计为本地部署提供了全新范式——开发者得以在消费级硬件上，以3B模型的资源消耗，获得80B量级的结构化代码理解能力，直接冲击了此前只有闭源大模型才能触及的能力天花板。","https:\u002F\u002Fventurebeat.com\u002Ftechnology\u002Fqwen3-coder-next-offers-vibe-coders-a-powerful-open-source-ultra-sparse","17ff6400-4413-4b16-86fb-99951dbbd08d",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"e676a5cf-1f24-472f-a765-86fa21a1bc3c","ai-model",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"e82b2d09-81b2-43d1-977e-e018443b3c14","coding-agent",{"id":18,"name":19,"slug":19,"description":13,"color":13},"7e89b5cc-57db-4f37-bc6d-28919a73931c","model-release",{"id":21,"name":22,"slug":22,"description":13,"color":13},"b9bd9039-fcdb-41a8-b85b-fc1587def2b9","open-source",[24],{"id":25,"lang":26,"title":27,"summary":28,"content":13},"eff5951c-c3d3-4f9d-91be-5b1d40ecf213","en","Qwen3-Coder-Next: sparse MoE reshapes coding efficiency","On May 8, Alibaba's Qwen team released Qwen3-Coder-Next, an 80B-parameter MoE model purpose-built for Agentic Coding, activating only 3B parameters per forward pass yet possessing programming capability comparable to Dense models, sparking wide discussion in the open-weights community.\n\nThe core technology lies in Gated DeltaNet combined with Gated Attention, converting Attention's quadratic compute complexity to linear, allowing the model to maintain 262K token ultra-long context while avoiding exponential-order latency penalties. On repository-level tasks, throughput improves about 10× compared to same-tier Dense models. The training stage introduces a Best-Fit Packing strategy, effectively mitigating hallucination issues in long-context scenarios while preserving the integrity of contextual information.\n\nThe model is open-sourced under the Apache 2.0 license, with weights published in 4 variants on HuggingFace, along with a detailed technical report. At a time when coding agents are becoming the competitive focus of the industry, the small-activation-large-capability sparse MoE design provides a new paradigm for local deployment — developers can obtain 80B-tier structured code understanding capability at the resource cost of a 3B model on consumer-grade hardware, directly challenging the capability ceiling previously only accessible to closed-source large models.","qwen3-coder-next-80b-3b-active-gated-deltanet","2026-05-08T10:00:00Z","2026-05-08T10:05:10.079600Z","2026-08-19T02:08:40.142862Z",true,"agent",180,[37,46],{"slug":38,"tag_slug":38,"title_zh":39,"title_en":40,"intro_zh":41,"intro_en":42,"id":43,"is_active":33,"created_at":44,"modified_at":45},"ai-for-science","AI for Science 2026：从 UniPert 到 GPT-Rosalind 的硬核进化","AI for Science 2026: from UniPert to GPT-Rosalind","生命科学、化学材料、物理世界模型——AI 正在从\"语言工具\"变成\"实验伙伴\"。本专题收录 AI 在三大科学方向的关键节点：UniPert 统一基因与化学扰动空间、GPT-Rosalind 端到端生命科学推理、达摩院 AI 智能体 28 小时找到 4 种超导新材料、Anthropic Claude Science 把工作台做成标准品。","From language tool to lab partner — AI is reshaping life sciences, chemistry\u002Fmaterials, and physical world models. This topic covers the key milestones: UniPert unifying genetic-chemical perturbation spaces, GPT-Rosalind's end-to-end life-sciences reasoning, DAMO's AI agent discovering 4 superconducting materials in 28 hours, and Anthropic's Claude Science workbench going mainstream.","988a4300-5fab-41c4-b5d8-63711a2dc757","2026-09-10T01:34:15.296649Z","2026-09-10T01:34:15.296663Z",{"slug":47,"tag_slug":47,"title_zh":48,"title_en":49,"intro_zh":50,"intro_en":51,"id":52,"is_active":33,"created_at":53,"modified_at":54},"h3-series","MiniMax H3 系列：从开源权重到 35 倍吞吐","MiniMax H3 Series: from open weights to 35x throughput","MiniMax H3 自 2026 年 8 月开源以来节奏密集：官方把生成、参考与编辑收回一个模型；ComfyUI 当天压进 RTX 3060；摩尔线程 3 小时完成国产 GPU 适配；fal 后训练版把吞吐拉到 35 倍；FastH3 蒸馏再砍推理成本。本专题持续追踪 H3 的发布—开源—蒸馏—部署全链路。","Since MiniMax open-sourced H3 in August 2026 the pace has been relentless: one unified omni-modal model, same-day ComfyUI support down to an RTX 3060, a 3-hour Day-0 port to Moore Threads GPUs, fal's post-trained H3 Max at 35x throughput, and FastH3 distillation cutting inference cost further. This topic tracks the full H3 chain — release, open weights, distillation, deployment.","83ef0daa-3c31-4cb3-86ed-e5ee58654d5f","2026-09-08T07:33:19.942193Z","2026-09-08T07:33:19.942209Z",{"items":56},[57,62,67,72,77,82],{"id":58,"title":59,"news_slug":60,"published_at":61},"cb5ee922-ad27-4a5a-9b2b-8382903876df","Mozilla 把模型选择权交还给用户:Mistral Small 4 进 Firefox 默认菜单","mistral-small-4-firefox-smart-window-beta","2026-09-22T03:00:00+00:00",{"id":63,"title":64,"news_slug":65,"published_at":66},"89a79f9a-bfd2-4ebe-8f03-92fa74a3a34f","Ornith-1.5 开源：模型自己出题、自己搭考场，397B 到 9B 三档齐发","ornith-1-5-self-improvement-open-models","2026-08-20T13:30:00+00:00",{"id":68,"title":69,"news_slug":70,"published_at":71},"9f800588-ad3b-4eee-a8a6-e2db1ac8f014","GLM-5.3:只靠后训练把 743B 基座打成新 SOTA,网络安全的\"涌现\"打了 Z.ai 一个措手不及","glm-5-3-post-training-emergent-cyber","2026-08-14T08:00:00+00:00",{"id":73,"title":74,"news_slug":75,"published_at":76},"1e7d0673-aecc-42b5-8560-92a2b4d4daf6","快手 KAT-Coder-V2.5 把 Agentic Coding 训练改写成基础设施工程","kuaishou-kat-coder-v2-5","2026-07-27T06:00:00+00:00",{"id":78,"title":79,"news_slug":80,"published_at":81},"962927f4-dba2-4160-8e26-4c9fa4cdbb55","高德 ABot 全栈升级:把机器人拆成操作系统,M0.5 论文给出软总线答案","gaode-abot-m0-5-soft-bus","2026-07-22T10:30:00+00:00",{"id":83,"title":84,"news_slug":85,"published_at":86},"6ceaf229-f1a2-4231-b531-797a99faa194","Ornith-1.0：模型自写 RL harness，SWE-Bench 比肩 Opus 4.7","ornith-1-0-397b-moe-swe-bench-opus-4-7","2026-06-26T18:01:01+00:00"]