{"id":87714,"date":"2026-07-30T19:01:53","date_gmt":"2026-07-30T11:01:53","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/87714.html"},"modified":"2026-07-30T19:01:53","modified_gmt":"2026-07-30T11:01:53","slug":"kimi-k3-%e6%8a%80%e6%9c%af%e6%9e%b6%e6%9e%84%e4%b8%8e%e6%80%a7%e8%83%bd%e6%95%b0%e6%8d%ae%e5%88%86%e6%9e%90%ef%bc%9a%e5%bc%80%e6%ba%903%e4%b8%87%e4%ba%bf%e5%8f%82%e6%95%b0%e6%a8%a1%e5%9e%8b%e7%9a%84","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/87714.html","title":{"rendered":"Kimi K3 \u6280\u672f\u67b6\u6784\u4e0e\u6027\u80fd\u6570\u636e\u5206\u6790\uff1a\u5f00\u6e903\u4e07\u4ebf\u53c2\u6570\u6a21\u578b\u7684\u6846\u67b6\u521b\u65b0\u4e0e\u5148\u8fdb\u6027\u5f52\u56e0"},"content":{"rendered":"

\u6458\u8981<\/h3>\n

2026\u5e747\u670816\u65e5，\u6708\u4e4b\u6697\u9762（Moonshot AI）\u5728\u4e16\u754c\u4eba\u5de5\u667a\u80fd\u5927\u4f1a\u671f\u95f4\u6b63\u5f0f\u53d1\u5e03\u65b0\u4e00\u4ee3\u5f00\u6e90\u57fa\u7840\u6a21\u578bKimi K3\u3002\u8be5\u6a21\u578b\u603b\u53c2\u6570\u89c4\u6a21\u8fbe2.8\u4e07\u4ebf，\u662f\u5168\u7403\u9996\u4e2a\u8fdb\u51653\u4e07\u4ebf（3T）\u7ea7\u522b\u7684\u5f00\u6e90\u6743\u91cd\u6a21\u578b，\u539f\u751f\u652f\u6301\u89c6\u89c9\u7406\u89e3，\u4e0a\u4e0b\u6587\u7a97\u53e3\u8fbe100\u4e07token\u3002\u672c\u6587\u57fa\u4e8e\u5b98\u65b9\u6280\u672f\u535a\u5ba2\u3001\u7b2c\u4e09\u65b9\u72ec\u7acb\u8bc4\u6d4b\u4e0e\u591a\u5bb6\u5a92\u4f53\u62a5\u9053，\u4ece\u67b6\u6784\u6846\u67b6\u4e0e\u6027\u80fd\u6570\u636e\u4e24\u4e2a\u7ef4\u5ea6\u5bf9Kimi K3\u8fdb\u884c\u7cfb\u7edf\u6027\u5206\u6790：\u5728\u67b6\u6784\u5c42\u9762，\u91cd\u70b9\u5256\u6790Kimi Delta Attention（KDA）\u6df7\u5408\u7ebf\u6027\u6ce8\u610f\u529b\u3001Attention Residuals（AttnRes）\u6ce8\u610f\u529b\u6b8b\u5dee\u3001Stable LatentMoE\u7a00\u758f\u6df7\u5408\u4e13\u5bb6\u6846\u67b6\u53ca\u91cf\u5316\u611f\u77e5\u8bad\u7ec3\u7b49\u5173\u952e\u6280\u672f；\u5728\u6570\u636e\u5c42\u9762，\u9010\u9879\u5bf9\u6bd4K3\u4e0eClaude Fable 5\u3001GPT-5.6 Sol\u7b49\u524d\u6cbf\u95ed\u6e90\u6a21\u578b\u5728\u7f16\u7a0b\u3001\u667a\u80fd\u4f53\u4e0e\u77e5\u8bc6\u5de5\u4f5c\u57fa\u51c6\u4e0a\u7684\u8868\u73b0\u3002\u5206\u6790\u8868\u660e，K3\u901a\u8fc7\u201c\u67b6\u6784\u6548\u7387\u4f18\u5148\u201d\u7684\u6280\u672f\u8def\u7ebf，\u5c06\u6574\u4f53\u6269\u5c55\u6548\u7387\u8f83\u524d\u4ee3K2\u63d0\u5347\u7ea62.5\u500d，\u5e76\u5728\u957f\u7a0b\u667a\u80fd\u4f53\u4e0e\u7f16\u7a0b\u4efb\u52a1\u4e0a\u8fbe\u5230\u5f00\u6e90\u6a21\u578b\u524d\u6240\u672a\u6709\u7684\u9ad8\u5ea6，\u7efc\u5408\u667a\u80fd\u4f4d\u5217\u5168\u7403\u7b2c\u56db\u3001\u5f00\u6e90\u7b2c\u4e00\u3002\u6700\u540e，\u672c\u6587\u4ece\u56db\u4e2a\u7ef4\u5ea6\u5f52\u56e0\u5176\u5148\u8fdb\u6027，\u5e76\u5ba2\u89c2\u8ba8\u8bba\u5176\u5c40\u9650\u3002<\/p>\n

\u5173\u952e\u8bcd：Kimi K3；\u6df7\u5408\u4e13\u5bb6\u67b6\u6784；\u7ebf\u6027\u6ce8\u610f\u529b；\u91cf\u5316\u611f\u77e5\u8bad\u7ec3；\u957f\u7a0b\u667a\u80fd\u4f53；\u5f00\u6e90\u5927\u6a21\u578b<\/p>\n

\u4e00\u3001\u5f15\u8a00<\/h3>\n

\u81ea2022\u5e74\u672b\u5927\u8bed\u8a00\u6a21\u578b\u8fdb\u5165\u516c\u4f17\u89c6\u91ce\u4ee5\u6765，\u5f00\u6e90\u4e0e\u95ed\u6e90\u4e24\u6761\u6280\u672f\u8def\u7ebf\u4e4b\u95f4\u7684\u7ade\u4e89\u59cb\u7ec8\u662f\u884c\u4e1a\u5173\u6ce8\u7684\u7126\u70b9\u30022025\u5e74\u81f32026\u5e74\u95f4，\u5f00\u6e90\u6a21\u578b\u5728\u53c2\u6570\u89c4\u6a21\u4e0e\u80fd\u529b\u8fb9\u754c\u4e0a\u6301\u7eed\u903c\u8fd1\u95ed\u6e90\u65d7\u8230，\u800cKimi K3\u7684\u53d1\u5e03\u5c06\u8fd9\u4e00\u8d8b\u52bf\u63a8\u5411\u4e86\u65b0\u7684\u4e34\u754c\u70b9：2.8\u4e07\u4ebf\u7684\u603b\u53c2\u6570\u89c4\u6a21\u4f7f\u5176\u8d85\u8d8aDeepSeek-V4-Pro（1.6\u4e07\u4ebf），\u6210\u4e3a\u8fc4\u4eca\u53c2\u6570\u91cf\u6700\u5927\u7684\u5f00\u6e90\u6743\u91cd\u6a21\u578b，\u540c\u65f6\u4e5f\u662f\u5168\u7403\u9996\u4e2a\u8fc8\u51653T\u7ea7\u522b\u7684\u5f00\u6e90\u6a21\u578b\u3002<\/p>\n

\u503c\u5f97\u6ce8\u610f\u7684\u662f，K3\u7684\u610f\u4e49\u5e76\u975e\u5355\u7eaf\u4f9d\u8d56\u53c2\u6570\u5806\u780c\u3002\u5728\u8fc7\u53bb12\u4e2a\u6708\u4e2d，Kimi\u7cfb\u5217\u67099\u4e2a\u6708\u4fdd\u6301\u5f00\u6e90\u6a21\u578b\u7684\u89c4\u6a21\u4e0a\u9650，\u4eceK2\u5230K3\u7684\u5feb\u901f\u8fed\u4ee3\u80cc\u540e，\u662f\u4e00\u5957\u56f4\u7ed5\u201c\u7a00\u758f\u5316\u3001\u7ebf\u6027\u5316\u3001\u91cf\u5316\u201d\u5c55\u5f00\u7684\u7cfb\u7edf\u6027\u67b6\u6784\u5de5\u7a0b\u3002\u7406\u89e3K3\u4e3a\u4f55\u5148\u8fdb，\u9700\u8981\u56de\u7b54\u4e09\u4e2a\u95ee\u9898：\u5176\u4e00，2.8\u4e07\u4ebf\u53c2\u6570\u5982\u4f55\u88ab\u201c\u9a6f\u670d\u201d\u4e3a\u53ef\u8bad\u7ec3\u3001\u53ef\u63a8\u7406\u3001\u53ef\u8d1f\u62c5\u7684\u7cfb\u7edf；\u5176\u4e8c，\u5404\u9879\u57fa\u51c6\u6570\u636e\u7a76\u7adf\u8bf4\u660e\u4e86\u4ec0\u4e48；\u5176\u4e09，\u5176\u6280\u672f\u8def\u7ebf\u5bf9\u6574\u4e2a\u5f00\u6e90\u751f\u6001\u610f\u5473\u7740\u4ec0\u4e48\u3002\u672c\u6587\u5373\u56f4\u7ed5\u8fd9\u4e09\u4e2a\u95ee\u9898\u5c55\u5f00\u3002<\/p>\n

\u4e8c\u3001\u6a21\u578b\u6982\u51b5\u4e0e\u6838\u5fc3\u89c4\u683c<\/h3>\n

Kimi K3\u662f\u4e00\u6b3e\u7a00\u758f\u6df7\u5408\u4e13\u5bb6（Sparse Mixture-of-Experts）\u5927\u8bed\u8a00\u6a21\u578b，\u4e3b\u8981\u9762\u5411\u957f\u7a0b\u7f16\u7a0b\u3001\u77e5\u8bc6\u5de5\u4f5c\u4e0e\u6df1\u5ea6\u63a8\u7406\u7b49\u9ad8\u667a\u80fd\u9700\u6c42\u573a\u666f\u3002\u6a21\u578b\u539f\u751f\u652f\u6301\u89c6\u89c9\u7406\u89e3，\u53ef\u63a5\u53d7\u6587\u672c\u4e0e\u56fe\u50cf\u8f93\u5165；\u4e0a\u4e0b\u6587\u7a97\u53e3\u8fbe100\u4e07（1,048,576）token，\u76f8\u5f53\u4e8e\u4e00\u6b21\u6027\u5904\u7406\u300a\u4e09\u4f53\u300b\u4e09\u90e8\u66f2\u4f53\u91cf\u7684\u6587\u672c\u3002\u6a21\u578b\u5206\u4e3aK3 Max（\u901a\u7528\u5bf9\u8bdd\u4e0e\u667a\u80fd\u4f53\u4efb\u52a1）\u4e0eK3 Swarm Max（\u5927\u89c4\u6a21\u5e76\u884c\u5b50\u667a\u80fd\u4f53\u534f\u540c）\u4e24\u4e2a\u7248\u672c，\u5b8c\u6574\u6743\u91cd\u4ee5\u4fee\u6539\u7248MIT\u8bb8\u53ef\u8bc1（Modified MIT License）\u4e8e2026\u5e747\u670827\u65e5\u524d\u516c\u5f00\u3002\u5176\u6838\u5fc3\u89c4\u683c\u5982\u4e0b\u8868\u6240\u793a：<\/p>\n\n\u7ef4\u5ea6\u89c4\u683c<\/tr>\n\n\n\n\n\n\n\n\n\n\n\n
\u53d1\u5e03\u65b9 \/ \u53d1\u5e03\u65f6\u95f4<\/td>\n\u6708\u4e4b\u6697\u9762（Moonshot AI），2026\u5e747\u670816\u65e5<\/td>\n<\/tr>\n
\u67b6\u6784\u7c7b\u578b<\/td>\n\u7a00\u758f\u6df7\u5408\u4e13\u5bb6（Sparse MoE）\u81ea\u56de\u5f52Transformer<\/td>\n<\/tr>\n
\u603b\u53c2\u6570 \/ \u6fc0\u6d3b\u53c2\u6570<\/td>\n2.8\u4e07\u4ebf \/ \u7ea6410\u4ebf（896\u4e2a\u4e13\u5bb6\u4e2d\u6fc0\u6d3b16\u4e2a）<\/td>\n<\/tr>\n
\u6838\u5fc3\u6280\u672f<\/td>\nKDA\u6df7\u5408\u7ebf\u6027\u6ce8\u610f\u529b\u3001AttnRes\u6ce8\u610f\u529b\u6b8b\u5dee\u3001Stable LatentMoE<\/td>\n<\/tr>\n
\u4e0a\u4e0b\u6587\u7a97\u53e3<\/td>\n100\u4e07（1,048,576）token<\/td>\n<\/tr>\n
\u591a\u6a21\u6001\u80fd\u529b<\/td>\n\u539f\u751f\u652f\u6301\u89c6\u89c9\u7406\u89e3（\u6587\u672c+\u56fe\u50cf\u8f93\u5165）<\/td>\n<\/tr>\n
\u91cf\u5316\u65b9\u6848<\/td>\n\u91cf\u5316\u611f\u77e5\u8bad\u7ec3：MXFP4\u6743\u91cd + MXFP8\u6fc0\u6d3b<\/td>\n<\/tr>\n
\u7248\u672c<\/td>\nK3 Max（\u901a\u7528）\u3001K3 Swarm Max（\u5e76\u884c\u591a\u667a\u80fd\u4f53）<\/td>\n<\/tr>\n
\u5f00\u6e90\u534f\u8bae<\/td>\n\u4fee\u6539\u7248MIT\u8bb8\u53ef\u8bc1（Modified MIT），\u6743\u91cd2026\u5e747\u670827\u65e5\u524d\u516c\u5f00<\/td>\n<\/tr>\n
\u6269\u5c55\u6548\u7387<\/td>\n\u8f83\u524d\u4ee3K2\u63d0\u5347\u7ea62.5\u500d<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u4e09\u3001\u67b6\u6784\u6846\u67b6\u5206\u6790<\/h3>\n

\u53c2\u6570\u89c4\u6a21\u7684\u63d0\u5347\u53ea\u662f\u8868\u8c61，K3\u771f\u6b63\u7684\u6280\u672f\u4ef7\u503c\u5728\u4e8e\u5176\u67b6\u6784\u8bbe\u8ba1\u5982\u4f55\u8ba9\u4e07\u4ebf\u7ea7\u53c2\u6570\u201c\u53ef\u8bad\u7ec3\u3001\u53ef\u63a8\u7406\u3001\u53ef\u8d1f\u62c5\u201d\u3002\u672c\u8282\u6309\u6ce8\u610f\u529b\u673a\u5236\u3001\u6df1\u5ea6\u4fe1\u606f\u6d41\u3001\u4e13\u5bb6\u8def\u7531\u3001\u8bad\u7ec3\u4f18\u5316\u4e0e\u90e8\u7f72\u91cf\u5316\u4e94\u4e2a\u5c42\u9762\u9010\u4e00\u62c6\u89e3\u3002<\/p>\n

3.1 Kimi Delta Attention（KDA）\u6df7\u5408\u7ebf\u6027\u6ce8\u610f\u529b<\/h4>\n

\u4f20\u7edf\u5168\u91cf\u6ce8\u610f\u529b（Full Attention）\u7684\u8ba1\u7b97\u91cf\u968f\u5e8f\u5217\u957f\u5ea6\u5448\u5e73\u65b9\u7ea7\u589e\u957f，\u5728\u767e\u4e07token\u7ea7\u4e0a\u4e0b\u6587\u4e2d，\u663e\u5b58\u5360\u7528\u4e0e\u89e3\u7801\u5ef6\u8fdf\u90fd\u4f1a\u81a8\u80c0\u5230\u4e0d\u53ef\u7528\u7a0b\u5ea6\u3002KDA\u662f\u6708\u4e4b\u6697\u9762\u81ea\u7814\u7684\u6df7\u5408\u7ebf\u6027\u6ce8\u610f\u529b\u673a\u5236，\u5176\u6838\u5fc3\u601d\u60f3\u662f\u5c06\u957f\u4e0a\u4e0b\u6587\u62c6\u5206\u4e3a\u201c\u5df2\u538b\u7f29\u7684\u5386\u53f2\u72b6\u6001\u201d\u4e0e\u201c\u65b0\u5230\u6765\u7684\u589e\u91cf（Delta）\u201d\u4e24\u90e8\u5206：\u5386\u53f2\u90e8\u5206\u4ee5\u7ebf\u6027\u65b9\u5f0f\u7ef4\u62a4\u4e00\u4e2a\u7d27\u51d1\u7684\u8bb0\u5fc6\u72b6\u6001，\u65b0token\u4ec5\u9700\u91cd\u70b9\u5173\u6ce8\u53d8\u5316\u90e8\u5206，\u4ece\u800c\u628a\u8d85\u957f\u5e8f\u5217\u7684\u6ce8\u610f\u529b\u5f00\u9500\u4ece\u5e73\u65b9\u7ea7\u538b\u56de\u8fd1\u4f3c\u7ebf\u6027\u3002<\/p>\n

\u5b98\u65b9\u6570\u636e\u663e\u793a，KDA\u5728\u767e\u4e07token\u573a\u666f\u4e0b\u53ef\u5b9e\u73b0\u6700\u9ad86.3\u500d\u7684\u89e3\u7801\u52a0\u901f\u3002\u8fd9\u4e00\u6570\u5b57\u7684\u5de5\u7a0b\u610f\u4e49\u5728\u4e8e：100\u4e07token\u4e0a\u4e0b\u6587\u4ece\u201c\u5b9e\u9a8c\u5ba4\u91cc\u7684\u5bf9\u6807\u6307\u6807\u201d\u53d8\u6210\u4e86\u201c\u751f\u4ea7\u73af\u5883\u4e2d\u53ef\u8d1f\u62c5\u7684\u80fd\u529b\u201d，\u8fd9\u662fK3\u80fd\u591f\u539f\u751f\u652f\u6301\u8d85\u957f\u4e0a\u4e0b\u6587\u7a97\u53e3\u7684\u67b6\u6784\u57fa\u7840\u3002<\/p>\n

3.2 Attention Residuals（AttnRes）\u6ce8\u610f\u529b\u6b8b\u5dee<\/h4>\n

\u6df1\u5ea6\u7f51\u7edc\u4e2d，\u4fe1\u606f\u4ece\u6d45\u5c42\u5411\u6df1\u5c42\u4f20\u9012\u65f6\u5b58\u5728\u8870\u51cf\u4e0e\u7a00\u91ca\u95ee\u9898\u2014\u2014\u6a21\u578b\u5c42\u6570\u8d8a\u6df1，\u65e9\u671f\u5c42\u5b66\u5230\u7684\u6709\u6548\u7279\u5f81\u8d8a\u5bb9\u6613\u88ab\u4e2d\u95f4\u5c42\u201c\u51b2\u6de1\u201d\u3002\u4f20\u7edfTransformer\u5728\u5404\u5c42\u4e4b\u95f4\u5747\u5300\u7d2f\u79ef\u8868\u793a，\u800cAttnRes\u6539\u53d8\u4e86\u4fe1\u606f\u5728\u6df1\u5ea6\u65b9\u5411\u7684\u6d41\u52a8\u65b9\u5f0f：\u5b83\u5141\u8bb8\u6a21\u578b\u5728\u4e0d\u540c\u5c42\u7ea7\u4e4b\u95f4\u6709\u9009\u62e9\u5730\u68c0\u7d22\u8868\u793a，\u800c\u975e\u65e0\u5dee\u522b\u5730\u9010\u5c42\u53e0\u52a0\u3002\u6362\u8a00\u4e4b，\u6a21\u578b\u53ef\u4ee5\u81ea\u884c\u51b3\u5b9a\u54ea\u4e9b\u4fe1\u606f\u4ece\u6d45\u5c42\u76f4\u63a5\u53d6\u7528\u3001\u54ea\u4e9b\u9700\u8981\u6df1\u5165\u5e95\u5c42\u52a0\u5de5，\u76f8\u5f53\u4e8e\u5728\u5c42\u95f4\u67b6\u8bbe\u4e86\u201c\u4fe1\u606f\u9ad8\u901f\u516c\u8def\u201d\u3002<\/p>\n

\u5b98\u65b9\u7ed9\u51fa\u7684\u6536\u76ca\u6570\u636e\u662f：\u4ee5\u4e0d\u52302%\u7684\u989d\u5916\u8ba1\u7b97\u5f00\u9500，\u6362\u6765\u7ea625%\u7684\u8bad\u7ec3\u6548\u7387\u63d0\u5347\u3002\u5728\u5904\u7406\u590d\u6742\u3001\u6df7\u4e71\u7684\u957f\u6587\u672c\u65f6，AttnRes\u663e\u8457\u52a0\u6df1\u4e86\u6a21\u578b\u7684\u4e0a\u4e0b\u6587\u7406\u89e3\u6df1\u5ea6，\u4fdd\u6301\u957f\u8ddd\u79bb\u8bed\u4e49\u7684\u8fde\u8d2f\u6027\u3002<\/p>\n

3.3 Stable LatentMoE \u7a00\u758f\u6df7\u5408\u4e13\u5bb6\u67b6\u6784<\/h4>\n

K3\u7684MoE\u5c42\u5171\u914d\u7f6e896\u4e2a\u4e13\u5bb6\u6a21\u5757，\u6bcf\u4e2atoken\u4ec5\u6fc0\u6d3b\u5176\u4e2d16\u4e2a，\u7a00\u758f\u5ea6\u7ea61.8%\u2014\u2014\u8fd9\u4e00\u7a00\u758f\u6c34\u5e73\u5728\u4e1a\u754c\u5c5e\u4e8e\u76f8\u5f53\u6fc0\u8fdb\u7684\u8bbe\u8ba1\u3002\u201c\u5927\u603b\u53c2\u3001\u5c0f\u6fc0\u6d3b\u201d\u7684\u7ed3\u6784\u4f7f\u6a21\u578b\u80fd\u591f\u4ee52.8\u4e07\u4ebf\u7684\u53c2\u6570\u5e93\u5b58\u50a8\u77e5\u8bc6\u4e0e\u89c4\u5f8b，\u4f46\u5355\u6b21\u524d\u5411\u63a8\u7406\u4ec5\u8c03\u7528\u7ea6410\u4ebf\u6fc0\u6d3b\u53c2\u6570，\u5728\u63a7\u5236\u8ba1\u7b97\u6210\u672c\u7684\u540c\u65f6\u6700\u5927\u5316\u6a21\u578b\u5bb9\u91cf\u3002<\/p>\n

\u5982\u6b64\u9ad8\u7684\u7a00\u758f\u5ea6\u5bf9\u8def\u7531\u7a33\u5b9a\u6027\u4e0e\u8bad\u7ec3\u6536\u655b\u63d0\u51fa\u4e86\u4e25\u5cfb\u6311\u6218\u3002Stable LatentMoE\u6846\u67b6\u6b63\u662f\u4e3a\u6b64\u8bbe\u8ba1：\u5b83\u5728\u6f5c\u5728\u7a7a\u95f4（Latent Space）\u4e2d\u7a33\u5b9a\u5927\u89c4\u6a21\u7a00\u758f\u8bad\u7ec3\u7684\u52a8\u6001，\u786e\u4fdd896\u4e2a\u4e13\u5bb6\u5728\u957f\u8fbe\u6570\u4e07\u4ebftoken\u7684\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u4fdd\u6301\u8d1f\u8f7d\u5747\u8861\u4e0e\u68af\u5ea6\u7a33\u5b9a\u3002<\/p>\n

3.4 \u8def\u7531\u4e0e\u8bad\u7ec3\u4f18\u5316\u673a\u5236<\/h4>\n

\u56f4\u7ed5\u7a00\u758fMoE\u7684\u8bad\u7ec3，K3\u5f15\u5165\u4e86\u4e09\u9879\u914d\u5957\u673a\u5236：<\/p>\n

  • Quantile Balancing（\u5206\u4f4d\u6570\u5747\u8861）：\u4f20\u7edf\u4e13\u5bb6\u8d1f\u8f7d\u5747\u8861\u4f9d\u8d56\u542f\u53d1\u5f0f\u89c4\u5219\u4e0e\u654f\u611f\u7684\u8d85\u53c2\u6570\u8c03\u8282，Quantile Balancing\u5219\u76f4\u63a5\u4ece\u8def\u7531\u5668（Router）\u5206\u6570\u7684\u5206\u4f4d\u6570\u63a8\u5bfc\u4e13\u5bb6\u5206\u914d\u65b9\u6848，\u4ee5\u7edf\u8ba1\u5b66\u65b9\u6cd5\u66ff\u4ee3\u4eba\u5de5\u7ecf\u9a8c，\u5f7b\u5e95\u6d88\u9664\u4e86\u4e00\u4e2a\u6781\u96be\u8c03\u4f18\u7684\u5747\u8861\u8d85\u53c2\u6570\u3002<\/li>\n
  • Per-Head Muon\u4f18\u5316\u5668：\u5c06Muon\u4f18\u5316\u5668\u6269\u5c55\u5230\u9010\u6ce8\u610f\u529b\u5934（Per-Head）\u7c92\u5ea6，\u5bf9\u6bcf\u4e2a\u6ce8\u610f\u529b\u5934\u72ec\u7acb\u4f18\u5316，\u4f7f\u5927\u89c4\u6a21\u8bad\u7ec3\u4e0b\u7684\u5b66\u4e60\u8fc7\u7a0b\u66f4\u5177\u81ea\u9002\u5e94\u6027\u3002<\/li>\n
  • Sigmoid Tanh Unit（SiTU）\u4e0eGated MLA：\u524d\u8005\u6539\u8fdb\u6fc0\u6d3b\u51fd\u6570\u7684\u63a7\u5236\u80fd\u529b，\u540e\u8005\u589e\u5f3a\u6ce8\u610f\u529b\u7684\u9009\u62e9\u6027\u3002\u4e8c\u8005\u4e0eKDA\u3001AttnRes\u534f\u540c，\u5171\u540c\u4fdd\u969c\u4e862.8\u4e07\u4ebf\u53c2\u6570\u89c4\u6a21\u4e0b\u8bad\u7ec3\u7684\u7a33\u5b9a\u4e0e\u9ad8\u6548\u3002<\/li>\n

    3.5 \u91cf\u5316\u611f\u77e5\u8bad\u7ec3\u4e0e\u63a8\u7406\u90e8\u7f72\u4f18\u5316<\/h4>\n

    K3\u4ece\u76d1\u7763\u5fae\u8c03（SFT）\u9636\u6bb5\u8d77\u5373\u5e94\u7528\u91cf\u5316\u611f\u77e5\u8bad\u7ec3（Quantization-Aware Training, QAT），\u91c7\u7528MXFP4\u6743\u91cd\u4e0eMXFP8\u6fc0\u6d3b\u7684\u7ec4\u5408，\u800c\u975e\u8bad\u7ec3\u5b8c\u6210\u540e\u518d\u505a\u91cf\u5316\u538b\u7f29\u3002\u8fd9\u4e00\u8def\u7ebf\u4f7f\u6a21\u578b\u6743\u91cd\u663e\u5b58\u5360\u7528\u964d\u81f3\u4f20\u7edf16\u6bd4\u7279\u7cbe\u5ea6\u7684\u7ea6\u56db\u5206\u4e4b\u4e00，\u540c\u65f6\u6700\u5927\u9650\u5ea6\u4fdd\u7559\u4e86\u7cbe\u5ea6\u3002<\/p>\n

    \u5728\u7cfb\u7edf\u5c42\u9762，\u4e3a\u9632\u6b62\u5927\u89c4\u6a21\u4e13\u5bb6\u5e76\u884c（Expert Parallelism）\u4e0b\u7684\u8d1f\u8f7d\u5931\u8861\u62d6\u57ae\u541e\u5410，K3\u91c7\u7528\u4e86\u5b8c\u5168\u5747\u8861\u7684\u4e13\u5bb6\u5e76\u884c\u8bad\u7ec3\u65b9\u6cd5，\u5173\u952e\u8def\u5f84\u4e0a\u65e0\u4e3b\u673a\u540c\u6b65；\u63a8\u7406\u4fa7，\u5b98\u65b9\u5efa\u8bae\u4ee564\u5361\u4ee5\u4e0a\u8d85\u8282\u70b9（Supernode）\u914d\u7f6e\u90e8\u7f72，\u5e76\u5411vLLM\u793e\u533a\u8d21\u732e\u4e86\u9002\u914dKDA\u7684\u524d\u7f00\u7f13\u5b58（Prefix Caching）\u65b9\u6848\u3002\u8fd9\u4e9b\u5de5\u7a0b\u4f18\u5316\u5171\u540c\u652f\u6491\u4e86K3\u57282.8T\u89c4\u6a21\u4e0e\u767e\u4e07\u4e0a\u4e0b\u6587\u4e0b\u4ecd\u5177\u7ade\u4e89\u529b\u7684token\u5b9a\u4ef7：\u7f13\u5b58\u547d\u4e2d\u8f93\u51650.30\u7f8e\u5143\/\u767e\u4e07token\u3001\u672a\u547d\u4e2d3.00\u7f8e\u5143\/\u767e\u4e07token\u3001\u8f93\u51fa15.00\u7f8e\u5143\/\u767e\u4e07token，\u7ea6\u4e3aClaude Fable 5\u5b9a\u4ef7\u7684\u4e09\u5206\u4e4b\u4e00\u3002<\/p>\n

    \u56db\u3001\u57fa\u51c6\u6027\u80fd\u6570\u636e\u5206\u6790<\/h3>\n

    4.1 \u7f16\u7a0b\u4e0e\u957f\u7a0b\u667a\u80fd\u4f53\u57fa\u51c6<\/h4>\n

    \u7f16\u7a0b\u4e0e\u957f\u7a0b\u667a\u80fd\u4f53\u4efb\u52a1\u662fK3\u6700\u6838\u5fc3\u7684\u4f18\u52bf\u533a\u3002\u5b98\u65b9\u8bc4\u6d4b\u4e0e\u7b2c\u4e09\u65b9\u590d\u6838\u663e\u793a，K3\u5728\u516d\u9879\u7f16\u7a0b\u57fa\u51c6\u4e2d\u7a33\u5b9a\u4f4d\u5c45\u524d\u4e09，\u5e76\u5728SWE Marathon\u4e0eProgram Bench\u4e0a\u9886\u5148\u5168\u90e8\u53c2\u8bc4\u6a21\u578b：SWE Marathon\u53d6\u5f9742.0\u5206，\u9ad8\u4e8eClaude Fable 5\u768435.0\u5206\u4e0eGPT-5.6 Sol\u768439.0\u5206；Program Bench\u53d6\u5f9777.8\u5206，\u9ad8\u4e8eGPT-5.6 Sol\u768477.6\u5206\u4e0eFable 5\u768476.8\u5206；Terminal Bench 2.1\u53d6\u5f9788.3\u5206，\u4ec5\u4ee50.5\u5206\u4e4b\u5dee\u6b21\u4e8eGPT-5.6 Sol\u768488.8\u5206\u3002\u5728\u9700\u8981\u6df1\u5ea6\u7f51\u9875\u68c0\u7d22\u80fd\u529b\u7684BrowseComp\u4e0a，K3\u4ee591.2\u5206\u8d85\u8fc7GPT-5.6 Sol（90.4）\u4e0eFable 5（88.0）\u3002\u5176\u77ed\u677f\u51fa\u73b0\u5728FrontierSWE（81.2\u5206\u5bf9Fable 5\u768486.6\u5206）\u4e0eDeepSWE（67.5\u5206，\u6392\u540d\u7b2c\u4e09）\u4e0a\u3002<\/p>\n

    \u7279\u522b\u503c\u5f97\u4e00\u63d0\u7684\u662f\u72ec\u7acb\u7b2c\u4e09\u65b9\u8bc4\u6d4bFrontend Code Arena（\u524d\u7aef\u4ee3\u7801\u7ade\u6280\u573a）：\u8be5\u8bc4\u6d4b\u91c7\u7528\u533f\u540d\u53cc\u76f2\u6295\u7968\u673a\u5236，\u5f00\u53d1\u8005\u5bf9\u540c\u4e00\u4efb\u52a1\u7684\u4e24\u4e2a\u533f\u540d\u6a21\u578b\u8f93\u51fa\u6295\u7968，\u8eab\u4efd\u5728\u6295\u7968\u540e\u624d\u63ed\u6653，\u53ef\u6709\u6548\u964d\u4f4e\u54c1\u724c\u504f\u8bef\u3002K3\u4e0a\u7ebf\u9996\u65e5\u5373\u4ee51679 Elo\u5206\u767b\u9876\u5168\u7403\u7b2c\u4e00，\u8d85\u8fc7Claude Fable 5（1631）\u4e0eGPT-5.6 Sol（1618），\u5e76\u5728\u4e03\u4e2a\u524d\u7aef\u7ec6\u5206\u65b9\u5411\u4e2d\u516d\u9879\u6392\u540d\u7b2c\u4e00\u3002<\/p>\n

    \u56fe1：Kimi K3\u4e0e\u524d\u6cbf\u95ed\u6e90\u6a21\u578b\u5728\u7f16\u7a0b\u53ca\u667a\u80fd\u4f53\u57fa\u51c6\u4e0a\u7684\u5bf9\u6bd4
    \n\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\"<\/p>\n

    4.2 \u901a\u7528\u667a\u80fd\u4f53\u4e0e\u77e5\u8bc6\u5de5\u4f5c\u57fa\u51c6<\/h4>\n

    \u5728\u901a\u7528\u667a\u80fd\u4f53\u65b9\u5411，K3\u5728Automation Bench（30.8\u5206）\u4e0eSpreadsheetBench 2（34.8\u5206）\u4e0a\u5747\u5217\u7b2c\u4e00，JobBench\u4ee552.9\u5206\u6b21\u4e8eFable 5\u768457.4\u5206；\u89c6\u89c9\u667a\u80fd\u4f53\u65b9\u5411，ZeroBench（\u5e26\u5de5\u5177）\u53d6\u5f9741.0\u5206\u4e0eGPT-5.5\u5e76\u5217\u7b2c\u4e00，CharXiv RQ（\u5e26\u5de5\u5177）91.3\u5206\u4ec5\u6b21\u4e8eFable 5\u3002\u5728\u77e5\u8bc6\u5de5\u4f5c\u7c7b\u57fa\u51c6\u4e0aK3\u5448\u73b0\u5168\u9762\u9886\u5148\u6001\u52bf：Online Exp Bench 75.5\u5206（GPT-5.5\u4e3a70.6\u3001Claude Opus 4.8\u4e3a65.9）\u3001DECK-Bench 73.5\u5206\u3001Finance-Bench 62.6\u5206\u5747\u8d85\u8fc7\u6240\u6709\u53c2\u8bc4\u95ed\u6e90\u6a21\u578b\u3002\u6b64\u5916，\u53d1\u5e03\u65f6\u5b98\u65b9\u62a5\u544a\u5176\u5728GPQA Diamond\u4e0a\u53d6\u5f9793.5%，\u4e3a\u8be5\u57fa\u51c6\u6709\u8bb0\u5f55\u4ee5\u6765\u5f00\u6e90\u6743\u91cd\u6a21\u578b\u7684\u6700\u597d\u6210\u7ee9\u3002<\/p>\n

    4.3 \u7efc\u5408\u6392\u540d\u4e0e\u77ed\u677f\u5206\u6790<\/h4>\n

    \u7efc\u5408\u7ef4\u5ea6\u4e0a，K3\u5728Artificial Analysis Intelligence Index v4.1\u4e2d\u53d6\u5f9757.11\u5206，\u4f4d\u5217\u5168\u7403\u7b2c\u56db，\u6b21\u4e8eClaude Fable 5（59.86）\u3001GPT-5.6 Sol max（58.89）\u4e0eGPT-5.6 Sol xhigh（57.65），\u9ad8\u4e8eClaude Opus 4.8（55.69）\u3001Grok 4.5（53.83）\u4e0eGLM-5.2（51.09），\u7a33\u5c45\u5f00\u6e90\u6a21\u578b\u7b2c\u4e00\u4f4d\u3002<\/p>\n

    \u5728\u4e0eClaude Fable 5\u768414\u9879\u5171\u540c\u57fa\u51c6\u5bf9\u6bd4\u4e2d，Fable 5\u8d62\u4e0b\u7ea68\u9879\u3001K3\u8d62\u4e0b\u7ea66\u9879：K3\u80dc\u51fa\u7684\u96c6\u4e2d\u5728\u957f\u7a0b\u667a\u80fd\u4f53\u7f16\u7a0b\u3001BrowseComp\u4e0eTerminal Bench 2.1\u7b49\u201c\u505a\u4e8b\u578b\u201d\u4efb\u52a1，Fable 5\u5219\u5728\u66f4\u5e7f\u4e49\u7684\u63a8\u7406\u4e0e\u89c6\u89c9\u4efb\u52a1\u4e0a\u4fdd\u6301\u4f18\u52bf\u3002\u6708\u4e4b\u6697\u9762\u5728\u5b98\u65b9\u6587\u6863\u4e2d\u4ea6\u5766\u627f，K3\u6574\u4f53\u8868\u73b0\u4ecd\u843d\u540e\u4e8e\u4e24\u6b3e\u6700\u5f3a\u95ed\u6e90\u6a21\u578b，\u5728\u667a\u80fd\u4f53\u73af\u5883\u5207\u6362\u65f6\u5bf9\u63a8\u7406\u5386\u53f2\u7684\u4e22\u5931\u8f83\u4e3a\u654f\u611f，\u7efc\u5408\u6613\u7528\u6027\u5b58\u5728\u5dee\u8ddd\u3002\u8fd9\u79cd\u5982\u5b9e\u62ab\u9732\u77ed\u677f\u7684\u6001\u5ea6\u53cd\u800c\u4e3a\u5176\u8d62\u5f97\u4e86\u793e\u533a\u7684\u5c0a\u91cd\u3002<\/p>\n

    \u56fe2：Artificial Analysis\u7efc\u5408\u667a\u80fd\u6307\u6570\u6392\u540d（2026\u5e747\u6708）
    \n\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\"<\/p>\n

    4.4 \u957f\u7a0b\u5de5\u7a0b\u5b9e\u6218\u6848\u4f8b<\/h4>\n

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    \u4e94\u3001\u5148\u8fdb\u6027\u5f52\u56e0\u5206\u6790<\/h3>\n

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    \u516d\u3001\u5c40\u9650\u6027\u4e0e\u8ba8\u8bba<\/h3>\n

    \u5ba2\u89c2\u5730\u770b，K3\u4ecd\u5b58\u5728\u56db\u65b9\u9762\u5c40\u9650\u3002<\/p>\n

  • \u7efc\u5408\u63a8\u7406\u80fd\u529b\u5c1a\u6709\u5dee\u8ddd：\u7efc\u5408\u667a\u80fd\u6307\u657057.11\u5206\u4ecd\u843d\u540e\u4e8eFable 5\u4e0eGPT-5.6 Sol，\u5728FrontierSWE\u3001HLE-Full\u7b49\u4f20\u7edf\u6df1\u5ea6\u63a8\u7406\u57fa\u51c6\u4e0a\u5dee\u8ddd\u660e\u663e（HLE-Full\u4e3a43.5\u5206\u5bf953.3\u5206）\u3002<\/li>\n
  • \u6613\u7528\u6027\u77ed\u677f：\u6a21\u578b\u5728\u5207\u6362\u667a\u80fd\u4f53\u73af\u5883\u65f6\u5bf9\u63a8\u7406\u5386\u53f2\u4e22\u5931\u654f\u611f，\u5b9e\u9645\u90e8\u7f72\u4f53\u9a8c\u900a\u4e8e\u4e24\u5927\u95ed\u6e90\u65d7\u8230\u3002<\/li>\n
  • \u81ea\u90e8\u7f72\u95e8\u69db\u6781\u9ad8：2.8\u4e07\u4ebf\u53c2\u6570\u5373\u4fbf\u7ecf\u8fc7MXFP4\u91cf\u5316，\u6743\u91cd\u5b58\u50a8\u3001\u4e13\u5bb6\u5e76\u884c\u901a\u4fe1\u4e0eKV\u7f13\u5b58\u4ecd\u8981\u6c42\u5927\u89c4\u6a21\u52a0\u901f\u5668\u96c6\u7fa4，\u5b98\u65b9\u5efa\u8bae64\u5361\u4ee5\u4e0a\u8d85\u8282\u70b9\u914d\u7f6e，\u666e\u901a\u673a\u6784\u96be\u4ee5\u672c\u5730\u8fd0\u884c\u3002<\/li>\n
  • \u4e25\u683c\u610f\u4e49\u4e0a\u5c5e\u4e8e\u5f00\u653e\u6743\u91cd（Open-Weight）\u800c\u975e\u5b8c\u6574\u5f00\u6e90：\u8bad\u7ec3\u6570\u636e\u4e0e\u8bad\u7ec3\u4ee3\u7801\u5e76\u672a\u516c\u5f00，\u5b66\u672f\u590d\u73b0\u5b58\u5728\u8fb9\u754c\u3002<\/li>\n

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    \u4e03\u3001\u7ed3\u8bba<\/h3>\n

    Kimi K3\u7684\u4ef7\u503c\u4e0d\u53ea\u5728\u4e8e2.8\u4e07\u4ebf\u8fd9\u4e00\u6570\u5b57，\u800c\u5728\u4e8e\u5b83\u8bc1\u660e\u4e86\u4e24\u4ef6\u4e8b：\u7b2c\u4e00，\u901a\u8fc7KDA\u3001AttnRes\u4e0eStable LatentMoE\u6784\u6210\u7684\u67b6\u6784\u7ec4\u5408，\u4e07\u4ebf\u53c2\u6570\u7ea7\u6a21\u578b\u53ef\u4ee5\u5728\u7a00\u758f\u5316\u3001\u7ebf\u6027\u5316\u4e0e\u4f4e\u6bd4\u7279\u5316\u7684\u6280\u672f\u8def\u7ebf\u4e0b\u88ab\u9ad8\u6548\u8bad\u7ec3\u4e0e\u90e8\u7f72，\u6269\u5c55\u6548\u7387\u8f83\u524d\u4ee3\u63d0\u5347\u7ea62.5\u500d；\u7b2c\u4e8c，\u5f00\u6e90\u6a21\u578b\u5df2\u7ecf\u80fd\u591f\u5728\u957f\u7a0b\u667a\u80fd\u4f53\u3001\u7f16\u7a0b\u4e0e\u77e5\u8bc6\u5de5\u4f5c\u7b49\u6700\u590d\u6742\u7684\u4efb\u52a1\u7c7b\u522b\u4e0a\u4e0e\u6700\u5f3a\u95ed\u6e90\u6a21\u578b\u540c\u53f0\u7ade\u4e89，\u5e76\u5728\u5176\u4e2d\u591a\u9879\u53d6\u5f97\u7b2c\u4e00\u3002\u5b83\u4ecd\u6709\u660e\u663e\u77ed\u677f\u2014\u2014\u7efc\u5408\u63a8\u7406\u3001\u6613\u7528\u6027\u4e0e\u90e8\u7f72\u6210\u672c\u2014\u2014\u4f46\u4f5c\u4e3a\u5168\u7403\u9996\u4e2a3T\u7ea7\u5f00\u6e90\u6a21\u578b，K3\u4e3a\u5f00\u6e90\u9635\u8425\u6811\u7acb\u4e86\u65b0\u7684\u6807\u6746，\u4e5f\u4e3a\u540e\u7eed\u7814\u7a76\u63d0\u4f9b\u4e86\u4e00\u6761\u6e05\u6670\u7684\u6280\u672f\u8def\u7ebf：\u672a\u6765\u7684\u6a21\u578b\u7ade\u4e89，\u5c06\u8d8a\u6765\u8d8a\u591a\u5730\u53d6\u51b3\u4e8e\u67b6\u6784\u6548\u7387\u800c\u975e\u53c2\u6570\u89c4\u6a21\u672c\u8eab\u3002<\/p>\n

    \u53c2\u8003\u6587\u732e<\/h3>\n
  • Cryptalist. Moonshot AI \u53d1\u5e03 Kimi K3：\u5168\u7403\u9996\u6b3e\u62e5\u67092.8\u4e07\u4ebf\u53c2\u6570\u7684\u5f00\u6e90\u6a21\u578b[EB\/OL]. (2026-07-17).<\/li>\n
  • \u6f8e\u6e43\u65b0\u95fb. 2.8\u4e07\u4ebf！\u5168\u7403\u53c2\u6570\u6700\u5927\u5f00\u6e90\u6a21\u578bKimi K3\u53d1\u5e03[EB\/OL]. (2026-07-17).<\/li>\n
  • Roboflow Playground. Claude Opus 5 vs Kimi K3: Vision Model Comparison[EB\/OL]. (2026-07-24).<\/li>\n
  • ZAKER. \u6708\u4e4b\u6697\u9762\u53d1\u5e03Kimi K3：2.8\u4e07\u4ebf\u53c2\u6570，\u6210\u5168\u7403\u6700\u5927\u5f00\u6e90\u6743\u91cd\u6a21\u578b[EB\/OL]. (2026-07-24).<\/li>\n
  • Moonshot AI. Kimi K3 Tech Blog: Open Frontier Intelligence[EB\/OL]. (2026-07).<\/li>\n
  • Bleap Finance. Kimi K3 Review 2026: Benchmarks, Pricing & Claude Fable 5 Comparison[EB\/OL]. (2026-07-22).<\/li>\n
  • \u6398\u91d1. Kimi K3\u91cd\u78c5\u5f00\u6e90：2.8\u4e07\u4ebf\u53c2\u6570\u767b\u9876\u7f16\u7a0b\u8bc4\u6d4b，\u4e2d\u56fd\u5927\u6a21\u578b\u7684\u201c\u7b2c\u4e8c\u4e2aDeepSeek\u65f6\u523b\u201d[EB\/OL]. (2026-07-19).<\/li>\n
  • \u65b0\u6d6a\u79d1\u6280. Kimi K3\u53d1\u5e03：2.8T\u53c2\u6570\u5168\u7403\u9996\u4e2a\u5f00\u6e903T\u7ea7\u6a21\u578b，\u524d\u7aef\u4ee3\u7801Arena\u767b\u9876[EB\/OL]. (2026-07-17).<\/li>\n","protected":false},"excerpt":{"rendered":"

    \u6458\u8981
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