[{"data":1,"prerenderedAt":646},["ShallowReactive",2],{"page-/post/nezus/2026/06/428b-minimax":3,"pages-grouped-only":167,"surrounding-page":641},{"id":4,"title":5,"author":6,"body":7,"date":156,"description":18,"extension":157,"group":158,"lastmod":159,"meta":160,"navigation":161,"path":162,"rawbody":163,"seo":164,"showTitle":159,"sort":159,"stem":165,"tags":159,"versions":159,"__hash__":166},"content/post/nezus/2026/06/428b-minimax.md","428B参数全部开源，MiniMax这步棋走对了","user",{"type":8,"value":9,"toc":146},"minimark",[10,15,19,22,25,29,32,39,45,51,54,58,61,64,67,70,77,81,84,87,90,93,96,100,106,109,112,115,120,123,126,129,132,137,140],[11,12,14],"h2",{"id":13},"_428b-参数全部开源-minimax-这步棋走对了","428B 参数全部开源， MiniMax 这步棋走对了",[16,17,18],"p",{},"凌晨刷到一条消息，愣了三秒。",[16,20,21],{},"MiniMax 把 M3 模型的权重，直接传到了 HuggingFace 上。428B 总参数， 23B 激活——这体量，放到一年前，只有 OpenAI 和 Google 敢玩。",[16,23,24],{},"而现在，一家中国公司说：权重全开，随便下载。",[11,26,28],{"id":27},"这不只是一个模型是三个能力焊在一起","这不只是一个模型，是三个能力焊在一起",[16,30,31],{},"看 M3 的参数表，第一反应是\"贪心\"。",[16,33,34,38],{},[35,36,37],"strong",{},"编码与 Agent 能力","： SWE-Bench Pro 59.0%， Terminal Bench 2.1 66.0%， SWE-fficiency 34.8%， KernelBench Hard 28.8%， MCP Atlas 74.2%。这串数字翻译成人话——它能读代码、改代码、跑测试、修 Bug ，基本是一个初级程序员的水平。",[16,40,41,44],{},[35,42,43],{},"100 万 token 上下文","：靠自研的 MiniMax 稀疏注意力机制实现。100 万 token 是什么概念？大概能把一整本《三体》塞进去，然后让它帮你找 bug。",[16,46,47,50],{},[35,48,49],{},"原生多模态","：不是后期拼上去的视觉模块，是训练阶段就一起学的。",[16,52,53],{},"三个能力单独拎出来都不差，焊在一起——这就是为什么圈子里的反应不是\"又出一个模型\"，而是\"这东西能跑 Agent 了\"。",[11,55,57],{"id":56},"权重-10-天后发布这句话才是重点","\"权重 10 天后发布\"——这句话才是重点",[16,59,60],{},"注意，传上去的是模型结构和技术报告，权重还要等大约 10 天。",[16,62,63],{},"为什么不一股脑全放出来？我猜有两个原因：",[16,65,66],{},"一是安全审查。428B 的模型，能力边界需要测试，尤其 Agent 能力意味着它能操作文件系统、调用 API ，不能直接裸奔。",[16,68,69],{},"二是节奏感。先放消息炸一波讨论，再放权重引爆第二波传播。这比\"静默上线等你们自己发现\"高明得多。",[16,71,72,73,76],{},"对比一下 DeepSeek 的路线：直接放权重+论文，学术范儿。Qwen 的路线：模型+API 同步上，商业导向。MiniMax 这次的选择，更像是",[35,74,75],{},"一场精心设计的开源营销","。",[11,78,80],{"id":79},"开源军备竞赛已经打到第二轮了","开源军备竞赛，已经打到第二轮了",[16,82,83],{},"2024 年是开源大模型的元年， DeepSeek-V3 和 Qwen-72B 让所有人意识到：开源模型真的能用了。",[16,85,86],{},"2025 年进入分化期。有人做端侧（小模型），有人做垂直（医疗、法律、代码），有人开始卷 Agent 能力。",[16,88,89],{},"2026 年的主题词是**\"Agent-ready 的开源模型\"**。",[16,91,92],{},"MiniMax M3 就是这个赛道的新选手。它的竞争对手不是 GPT-5 或 Claude 4——那些闭源模型不在同一个战场。它真正的对手，是同样开源的 Llama 4、Qwen 3、DeepSeek V4。",[16,94,95],{},"这场仗的打法很清晰：谁能让开发者用最低成本跑出最好的 Agent 效果，谁就赢下生态。",[11,97,99],{"id":98},"_23b-激活参数藏着-minimax-的真实算盘","23B 激活参数，藏着 MiniMax 的真实算盘",[16,101,102,103,76],{},"428B 总参数听着吓人，但关键数字是",[35,104,105],{},"23B 激活参数",[16,107,108],{},"这意味着什么？意味着推理成本远低于同等总参数量的稠密模型。你可以把它理解成：一个有 428 个专家的团队，但每次只叫 23 个人出来干活。",[16,110,111],{},"这对开发者来说是实打实的好消息——跑得起，部署得了，不用租一柜子 H100。",[16,113,114],{},"MiniMax 显然算过这笔账。如果做一个 428B 全激活的模型，推理成本会劝退 90%的开发者。MoE 架构+稀疏注意力，既保住了参数规模带来的能力上限，又控制了推理成本。",[16,116,117],{},[35,118,119],{},"这才是真正聪明的做法。",[11,121,122],{"id":122},"最后说句真话",[16,124,125],{},"开源模型能不能追上闭源？这个问题已经问了两年了。",[16,127,128],{},"我的观察是：在\"通用对话\"这个维度，差距已经很小了。但在\"复杂推理\"和\"超长上下文理解\"上，闭源模型仍然有优势。",[16,130,131],{},"MiniMax M3 试图用 100 万 token 上下文和 Agent 能力来切一个新口子。如果 10 天后放出的权重真能达到技术报告里的数字，那它至少证明了一件事——",[16,133,134],{},[35,135,136],{},"开源模型不一定非要沿着闭源模型的路线追赶，它可以开辟自己的战场。",[16,138,139],{},"这步棋，走对了。",[16,141,142,145],{},[35,143,144],{},"封面高亮关键词",": MiniMax 开源, 428B 参数",{"title":147,"searchDepth":148,"depth":148,"links":149},"",2,[150,151,152,153,154,155],{"id":13,"depth":148,"text":14},{"id":27,"depth":148,"text":28},{"id":56,"depth":148,"text":57},{"id":79,"depth":148,"text":80},{"id":98,"depth":148,"text":99},{"id":122,"depth":148,"text":122},"2026-06-13T00:00:00.000Z","md","#202606AI资讯",null,{},true,"/post/nezus/2026/06/428b-minimax","---\ntitle: \"428B参数全部开源，MiniMax这步棋走对了\"\ndate: 2026-06-13\ngroup: \"#202606AI资讯\"\ndescription: \"凌晨刷到一条消息，愣了三秒。\"\nauthor: user\n---\n\n\n## 428B 参数全部开源， MiniMax 这步棋走对了\n\n凌晨刷到一条消息，愣了三秒。\n\nMiniMax 把 M3 模型的权重，直接传到了 HuggingFace 上。428B 总参数， 23B 激活——这体量，放到一年前，只有 OpenAI 和 Google 敢玩。\n\n而现在，一家中国公司说：权重全开，随便下载。\n\n## 这不只是一个模型，是三个能力焊在一起\n\n看 M3 的参数表，第一反应是\"贪心\"。\n\n**编码与 Agent 能力**： SWE-Bench Pro 59.0%， Terminal Bench 2.1 66.0%， SWE-fficiency 34.8%， KernelBench Hard 28.8%， MCP Atlas 74.2%。这串数字翻译成人话——它能读代码、改代码、跑测试、修 Bug ，基本是一个初级程序员的水平。\n\n**100 万 token 上下文**：靠自研的 MiniMax 稀疏注意力机制实现。100 万 token 是什么概念？大概能把一整本《三体》塞进去，然后让它帮你找 bug。\n\n**原生多模态**：不是后期拼上去的视觉模块，是训练阶段就一起学的。\n\n三个能力单独拎出来都不差，焊在一起——这就是为什么圈子里的反应不是\"又出一个模型\"，而是\"这东西能跑 Agent 了\"。\n\n## \"权重 10 天后发布\"——这句话才是重点\n\n注意，传上去的是模型结构和技术报告，权重还要等大约 10 天。\n\n为什么不一股脑全放出来？我猜有两个原因：\n\n一是安全审查。428B 的模型，能力边界需要测试，尤其 Agent 能力意味着它能操作文件系统、调用 API ，不能直接裸奔。\n\n二是节奏感。先放消息炸一波讨论，再放权重引爆第二波传播。这比\"静默上线等你们自己发现\"高明得多。\n\n对比一下 DeepSeek 的路线：直接放权重+论文，学术范儿。Qwen 的路线：模型+API 同步上，商业导向。MiniMax 这次的选择，更像是**一场精心设计的开源营销**。\n\n## 开源军备竞赛，已经打到第二轮了\n\n2024 年是开源大模型的元年， DeepSeek-V3 和 Qwen-72B 让所有人意识到：开源模型真的能用了。\n\n2025 年进入分化期。有人做端侧（小模型），有人做垂直（医疗、法律、代码），有人开始卷 Agent 能力。\n\n2026 年的主题词是**\"Agent-ready 的开源模型\"**。\n\nMiniMax M3 就是这个赛道的新选手。它的竞争对手不是 GPT-5 或 Claude 4——那些闭源模型不在同一个战场。它真正的对手，是同样开源的 Llama 4、Qwen 3、DeepSeek V4。\n\n这场仗的打法很清晰：谁能让开发者用最低成本跑出最好的 Agent 效果，谁就赢下生态。\n\n## 23B 激活参数，藏着 MiniMax 的真实算盘\n\n428B 总参数听着吓人，但关键数字是**23B 激活参数**。\n\n这意味着什么？意味着推理成本远低于同等总参数量的稠密模型。你可以把它理解成：一个有 428 个专家的团队，但每次只叫 23 个人出来干活。\n\n这对开发者来说是实打实的好消息——跑得起，部署得了，不用租一柜子 H100。\n\nMiniMax 显然算过这笔账。如果做一个 428B 全激活的模型，推理成本会劝退 90%的开发者。MoE 架构+稀疏注意力，既保住了参数规模带来的能力上限，又控制了推理成本。\n\n**这才是真正聪明的做法。**\n\n## 最后说句真话\n\n开源模型能不能追上闭源？这个问题已经问了两年了。\n\n我的观察是：在\"通用对话\"这个维度，差距已经很小了。但在\"复杂推理\"和\"超长上下文理解\"上，闭源模型仍然有优势。\n\nMiniMax M3 试图用 100 万 token 上下文和 Agent 能力来切一个新口子。如果 10 天后放出的权重真能达到技术报告里的数字，那它至少证明了一件事——\n\n**开源模型不一定非要沿着闭源模型的路线追赶，它可以开辟自己的战场。**\n\n这步棋，走对了。\n\n**封面高亮关键词**: MiniMax 开源, 428B 参数",{"title":5,"description":18},"post/nezus/2026/06/428b-minimax","Qsukeeo2IgToBRHCdgvy65fVdvvjCETrYFSUOoAiUZI",[168,175,179,183,187,192,195,199,203,207,211,216,220,224,228,232,236,241,246,250,254,258,262,267,271,275,284,289,293,297,302,306,310,314,318,323,328,333,337,341,345,350,354,358,363,367,371,375,379,384,388,393,397,401,405,410,414,418,423,427,431,435,439,444,448,452,457,461,465,470,474,478,482,486,490,495,499,503,507,508,512,516,520,525,529,533,537,541,546,550,554,558,562,567,571,578,584,589,594,599,604,609,614,619,624,629,635],{"id":169,"path":170,"title":171,"date":172,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/2026-7-16.md","/post/nezus/2026/07/2026-7-16","2026年7月16日下午，台积电法说会上传出一个数字，让全球半导体圈炸了锅。","2026-07-17T00:00:00.000Z","#202607AI资讯","storytelling",{"id":176,"path":177,"title":178,"date":172,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/anthropic-ai.md","/post/nezus/2026/07/anthropic-ai","一个周末干掉四年：Anthropic 用 AI 两周搬完百万行代码，工程师沉默了",{"id":180,"path":181,"title":182,"date":172,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/google-20.md","/post/nezus/2026/07/google-20","欧盟一纸裁决，Google 20年护城河被撕开第一道口子",{"id":184,"path":185,"title":186,"date":172,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/xai-grok.md","/post/nezus/2026/07/xai-grok","xAI给Grok装上定时任务能力",{"id":188,"path":189,"title":190,"date":191,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/apple.md","/post/nezus/2026/07/apple","Apple智能落地中国，阿里千问成幕后赢家","2026-07-16T00:00:00.000Z",{"id":193,"path":194,"title":190,"date":191,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/deepmind.md","/post/nezus/2026/07/deepmind",{"id":196,"path":197,"title":198,"date":191,"tags":159,"group":173,"lastmod":159,"author":6,"sort":159},"content/post/nezus/2026/07/gpt-vibe-coding-paste.md","/post/nezus/2026/07/gpt-vibe-coding-paste","用GPT Vibe Coding一个常用付费软件：Paste",{"id":200,"path":201,"title":202,"date":191,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/grok-build-agent.md","/post/nezus/2026/07/grok-build-agent","马斯克开源Grok Build，编程Agent进入白嫖时代",{"id":204,"path":205,"title":206,"date":191,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/openai-ai.md","/post/nezus/2026/07/openai-ai","OpenAI造了个AI黑客，专攻自家模型",{"id":208,"path":209,"title":210,"date":191,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/wps-comate-copilot.md","/post/nezus/2026/07/wps-comate-copilot","金山办公掏出WPS Comate，正面硬刚微软Copilot",{"id":212,"path":213,"title":214,"date":215,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/295b.md","/post/nezus/2026/07/295b","腾讯把295B大模型塞进了单张显卡","2026-07-15T00:00:00.000Z",{"id":217,"path":218,"title":219,"date":215,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/git-cursor.md","/post/nezus/2026/07/git-cursor","打开一个Git仓库Cursor就自动执行了恶意代码",{"id":221,"path":222,"title":223,"date":215,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/gpt-5-6-mac.md","/post/nezus/2026/07/gpt-5-6-mac","GPT-5.6偷偷删光了我的Mac文件",{"id":225,"path":226,"title":227,"date":215,"tags":159,"group":173,"lastmod":159,"author":6,"sort":159},"content/post/nezus/2026/07/grok-cli-xai.md","/post/nezus/2026/07/grok-cli-xai","Grok CLI 偷传代码：xAI 把你的仓库打包上传了",{"id":229,"path":230,"title":227,"date":231,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/grok-cli-bug-done-xai.md","/post/nezus/2026/07/grok-cli-bug-done-xai","2026-07-14T00:00:00.000Z",{"id":233,"path":234,"title":235,"date":231,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/seedream-5-0-ai.md","/post/nezus/2026/07/seedream-5-0-ai","字节跳动Seedream 5.0：圈一下图片就改了，AI修图进入点选时代",{"id":237,"path":238,"title":239,"date":240,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/post-20260712-ddc9a8.md","/post/nezus/2026/07/post-20260712-ddc9a8","欧盟强推Chat Control 2.0：加密通信的生死时刻","2026-07-12T00:00:00.000Z",{"id":242,"path":243,"title":244,"date":245,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/ai-1-5.md","/post/nezus/2026/07/ai-1-5","AI烧了1.5万亿，能赚回来吗","2026-07-10T00:00:00.000Z",{"id":247,"path":248,"title":249,"date":245,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/ai.md","/post/nezus/2026/07/ai","你刷到的帖子可能全是AI写的",{"id":251,"path":252,"title":253,"date":245,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/chatgpt-openai.md","/post/nezus/2026/07/chatgpt-openai","ChatGPT学会自己干活了",{"id":255,"path":256,"title":257,"date":245,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/musk-anthropic-apology.md","/post/nezus/2026/07/musk-anthropic-apology","马斯克向Anthropic低头认错",{"id":259,"path":260,"title":261,"date":245,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/optimus.md","/post/nezus/2026/07/optimus","马斯克：Optimus不达标就开除团队",{"id":263,"path":264,"title":265,"date":266,"tags":159,"group":173,"lastmod":159,"author":174,"sort":159},"content/post/nezus/2026/07/anthropic-github.md","/post/nezus/2026/07/anthropic-github","Anthropic 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