[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-local-llm-2026-deep-eval-swe-bench-aime":3,"news-related-6f1f105b-8e80-4b2c-b88c-b392556952aa":39},{"id":4,"title":5,"summary":6,"content":6,"original_url":7,"source_id":8,"tags":9,"translations":26,"news_slug":32,"published_at":33,"created_at":34,"modified_at":35,"is_published":36,"publish_type":37,"image_url":13,"view_count":38},"6f1f105b-8e80-4b2c-b88c-b392556952aa","2026年本地LLM深度评测：开源模型性能全解析","在2026年的AI领域，开源模型与闭源模型之间的界限已经变得模糊。开发者不再纠结于开源是否够用，而是开始关注哪款开源模型最适合我的特定任务。根据最新基准测试数据，主流本地LLM在三大硬核赛道上展开激烈竞争：SWE-bench Verified（真实软件工程能力）、AIME 2025（竞赛级数学推理）以及τ²-Bench（Agent代理协作能力）。代码能力方面，Kimi K2.5在SWE-bench Verified测试中取得76.8%的惊人成绩，成为开源界的新巅峰。其1万亿参数的MoE架构和256K超长上下文长度，让它在复杂代码处理上表现优异。DeepSeek V3.2凭借完全开放的MIT协议和73.1%的SWE-bench评分，依然是开发者的首选，提供极佳的性价比和响应速度。这场评测表明，开源模型正在迅速逼近闭源模型的性能水平，开发者现在拥有了更多元化、更专业化的模型选择。未来，随着MoE架构和长上下文技术的成熟，本地LLM将在企业级应用中扮演更加重要的角色。","https:\u002F\u002Fexplore.n1n.ai\u002Fzh\u002Fblog\u002F2026-nian-bendi-llm-shendu-pingce-2026-02-14","45954297-59b3-4c1e-a2ef-d14a2511b225",[10,14,17,20,23],{"id":11,"name":12,"slug":12,"description":13,"color":13},"5e628969-6d2a-437f-998a-104e4b16cfb1","ai-progress",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"120fa59a-ff6f-4537-9bf5-f818df636a0e","benchmark",{"id":18,"name":19,"slug":19,"description":13,"color":13},"01598627-1ea6-4b27-a5d8-874971571a71","llm",{"id":21,"name":22,"slug":22,"description":13,"color":13},"7e89b5cc-57db-4f37-bc6d-28919a73931c","model-release",{"id":24,"name":25,"slug":25,"description":13,"color":13},"b9bd9039-fcdb-41a8-b85b-fc1587def2b9","open-source",[27],{"id":28,"lang":29,"title":30,"summary":31,"content":13},"e7124f51-5b4f-4058-8437-bcc5fbfa838f","en","Local LLMs in 2026: a deep dive into open-model performance","In the 2026 AI field, the boundary between open-source and closed-source models has become blurred. Developers no longer obsess over whether open source is good enough, but begin to focus on which open-source model best fits their specific task. According to the latest benchmark data, mainstream local LLMs are in fierce competition on three hardcore tracks: SWE-bench Verified (real software engineering capability), AIME 2025 (competition-level math reasoning), and τ²-Bench (Agent collaboration capability). On coding, Kimi K2.5 achieves an impressive 76.8% on SWE-bench Verified, becoming the new pinnacle in the open-source world. Its 1-trillion-parameter MoE architecture and 256K ultra-long context make it perform excellently on complex code processing. DeepSeek V3.2, with its fully open MIT license and 73.1% SWE-bench score, remains developers' first choice, providing excellent cost-performance and response speed. This evaluation shows that open-source models are rapidly approaching closed-source model performance levels, and developers now have more diverse, more specialized model options. In the future, as MoE architecture and long-context technology mature, local LLMs will play a more important role in enterprise applications.","local-llm-2026-deep-eval-swe-bench-aime","2026-04-25T11:15:00Z","2026-04-25T19:13:44.177302Z","2026-08-19T02:08:40.142862Z",true,"agent",123,{"items":40},[41,46,51,56,61,66],{"id":42,"title":43,"news_slug":44,"published_at":45},"5bfdf32b-44eb-4eb5-a98b-39e921168182","九天内连发五款前沿模型:7 月的大模型军备赛,真正决胜负的不再是 benchmark","july-2026-five-frontier-models","2026-07-23T12:00:00+00:00",{"id":47,"title":48,"news_slug":49,"published_at":50},"f9cf9f03-6aca-4d29-94d3-5c6acfeaf435","匿名模型 OX Alpha 短暂登顶 OpenRouter 编码榜:研究者推测底座指向智谱 GLM-5.x","ox-alpha-stealth-openrouter-glm-5-zhipu","2026-08-24T03:00:00+00:00",{"id":52,"title":53,"news_slug":54,"published_at":55},"d4fa7e14-8fbd-4940-93a6-3dd6f0a3991d","DeepSeek V4 Pro 正式版：1.6T MoE，1M 上下文","deepseek-v4-pro-0813-ga-1m-context-moe","2026-08-13T02:00:00+00:00",{"id":57,"title":58,"news_slug":59,"published_at":60},"c94766df-827e-4e4e-a006-b6639ec76722","DeepSeek V4-Flash-0731 转正观察:权重不动,后训练把 Agent 分数打到 V4-Pro 之上","deepseek-v4-flash-0731-agent-benchmark-official-aug2026","2026-08-01T02:00:00+00:00",{"id":62,"title":63,"news_slug":64,"published_at":65},"80315de0-7eb3-491a-b2e6-103a691a8bd7","Nanbeige4.2-3B 用 Looped Transformer 在 11 项基准上跑赢 Qwen3.5-9B","nanbeige-4-2-3b-looped-transformer-agentic-3b-beats-qwen3-5-9b","2026-07-30T10:30:00+00:00",{"id":67,"title":68,"news_slug":69,"published_at":70},"dfc3dec4-2211-4c7e-b6ff-9e0d9a479ec4","微软与 Mistral 签下数十亿美元协议:Vera Rubin GPU 上的「欧洲主权云」开始落地","microsoft-mistral-vera-rubin-sovereign","2026-07-22T02:00:00+00:00"]