\u6700\u4f4e\u786c\u4ef6\u8981\u6c42<\/h3>\n

\u4f60\u9700\u8981\u5148\u68c0\u67e5\u670d\u52a1\u5668\u7684\u6700\u4f4e\u8981\u6c42\u3002Kimi K3 \u662f\u4e00\u4e2a\u4f53\u91cf\u5de8\u5927\u7684\u6a21\u578b\u3002\u5176\u539f\u59cb\u4e0b\u8f7d\u5927\u5c0f\u7ea6\u4e3a 1.4 TB\u3002\u4f60\u5fc5\u987b\u5177\u5907\u8db3\u591f\u7684\u5b58\u50a8\u7a7a\u95f4\u6765\u5bb9\u7eb3\u6a21\u578b\u6587\u4ef6\u3002K3 \u8fd8\u9700\u8981\u7531\u591a\u5f20 GPU \u7ec4\u6210\u7684\u96c6\u7fa4\u6765\u5b8c\u6210\u63a8\u7406\u3002\u5b98\u65b9\u5e76\u672a\u516c\u5e03\u6700\u4f4e GPU \u6570\u91cf\uff0c\u4f46\u4f60\u5e94\u9884\u671f\u9700\u8981\u4f7f\u7528\u5927\u91cf\u52a0\u901f\u5361\u3002\u8fd9\u4e9b\u6a21\u578b\u901a\u5e38\u8fd8\u9700\u8981 GPU \u4e4b\u95f4\u5177\u5907\u9ad8\u901f\u4e92\u8054\uff0c\u4ee5\u652f\u6301\u5feb\u901f\u63a8\u7406\u4e0e\u5b89\u5168\u6027\u9700\u6c42\u3002\u4f60\u8fd8\u5fc5\u987b\u4e3a\u591a\u6a21\u6001\u63a8\u7406\u5e26\u6765\u7684\u538b\u529b\u505a\u597d\u51c6\u5907\uff0c\u56e0\u4e3a\u5b83\u4f1a\u8fdb\u4e00\u6b65\u52a0\u91cd\u786c\u4ef6\u8d1f\u8f7d\u3002<\/p>\n

\u4e0b\u9762\u662f Kimi K3 \u670d\u52a1\u5668\u6700\u4f4e\u786c\u4ef6\u8981\u6c42\u7684\u5feb\u901f\u6982\u89c8\uff1a<\/p>\n

\n\n\n\n\n <\/colgroup>\n\n\n\n\n\n\n\n

\n \u89c4\u683c<\/p>\n<\/th>\n	\n \u8bf4\u660e<\/p>\n<\/th>\n<\/tr>\n
\n \u5efa\u8bae GPU \u6570\u91cf<\/p>\n<\/td>\n	\n 64 \u5f20\u6216\u66f4\u591a\u52a0\u901f\u5361<\/p>\n<\/td>\n<\/tr>\n
\n \u6700\u4f4e GPU \u6570\u91cf<\/p>\n<\/td>\n	\n \u672a\u516c\u5e03<\/p>\n<\/td>\n<\/tr>\n
\n GPU \u603b\u663e\u5b58<\/p>\n<\/td>\n	\n \u672a\u8bf4\u660e<\/p>\n<\/td>\n<\/tr>\n
\n \u6a21\u578b\u4e0b\u8f7d\u5927\u5c0f<\/p>\n<\/td>\n	\n \u539f\u59cb\u6570\u636e\u7ea6 1.4 TB<\/p>\n<\/td>\n<\/tr>\n
\n \u53c2\u6570\u603b\u91cf<\/p>\n<\/td>\n	\n 2.8 \u4e07\u4ebf\u53c2\u6570<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n \n \u63d0\u793a\uff1a<\/strong>\u4f60\u5e94\u59cb\u7ec8\u4e3a\u5b58\u50a8\u548c\u5185\u5b58\u9884\u7559\u989d\u5916\u4f59\u91cf\u3002\u6a21\u578b\u5728\u63a8\u7406\u8fc7\u7a0b\u4e2d\uff0c\u5f80\u5f80\u8fd8\u9700\u8981\u66f4\u591a\u7a7a\u95f4\u6765\u5b58\u653e\u63a8\u7406\u65e5\u5fd7\u548c\u5b89\u5168\u5907\u4efd\u3002<\/p>\n<\/blockquote>\n \u63a8\u8350\u786c\u4ef6\u914d\u7f6e<\/h3>\n \u5982\u679c\u4f60\u60f3\u83b7\u5f97\u6700\u4f73\u6027\u80fd\u548c\u66f4\u9ad8\u7684\u5b89\u5168\u6027\uff0c\u5c31\u5fc5\u987b\u4f7f\u7528\u4f01\u4e1a\u7ea7\u786c\u4ef6\u3002K3 \u5728\u5f3a\u5927 GPU \u4e0e\u9ad8\u901f\u4e92\u8054\u73af\u5883\u4e0b\u8868\u73b0\u6700\u4f73\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528\u57fa\u4e8e NVIDIA GPU \u7684\u65b9\u6848\uff0c\u4e5f\u53ef\u4ee5\u4f7f\u7528 Apple Mac\u3002\u63a8\u8350\u914d\u7f6e\u5c06\u6709\u52a9\u4e8e\u4f60\u83b7\u5f97\u66f4\u9ad8\u7684\u63a8\u7406\u901f\u5ea6\uff0c\u5e76\u7ef4\u6301\u66f4\u597d\u7684\u5b89\u5168\u6027\u3002<\/p>\n \u4f60\u8fd8\u5fc5\u987b\u8003\u8651\u96c6\u7fa4\u89c4\u6a21\u3002Kimi K3 \u63a8\u7406\u5728\u81f3\u5c11 16 \u5f20 GPU \u7684\u914d\u7f6e\u4e0b\u6548\u679c\u6700\u4f73\u3002\u4f01\u4e1a\u7ea7\u786c\u4ef6\u548c\u7ecf\u9a8c\u4e30\u5bcc\u7684\u8fd0\u7ef4\u4eba\u5458\u4e5f\u6709\u52a9\u4e8e\u63d0\u5347\u5b89\u5168\u6027\u3002\u5728\u90e8\u7f72 K3 \u4e4b\u524d\uff0c\u4f60\u5e94\u59cb\u7ec8\u68c0\u67e5\u786c\u4ef6\u7684\u517c\u5bb9\u6027\u4e0e\u5b89\u5168\u6027\u3002<\/p>\n \n \u6ce8\u610f\uff1a<\/strong>\u8fd9\u662f\u8bbf\u95ee\u63a7\u5236\u4e0e\u5b89\u5168\u4fdd\u969c\u6240\u5fc5\u9700\u7684\u4e00\u6b65\u3002\u670d\u52a1\u5668\u7684\u90e8\u7f72\u4e0e\u7ef4\u62a4\u5fc5\u987b\u7531\u5177\u5907\u4e13\u4e1a\u6280\u80fd\u7684\u4eba\u5458\u8d1f\u8d23\u3002<\/p>\n<\/blockquote>\n Python \u4e0e\u8f6f\u4ef6\u73af\u5883<\/h3>\n \u4f60\u5fc5\u987b\u4e3a Kimi K3 \u5b89\u88c5\u6b63\u786e\u7684\u8f6f\u4ef6\u73af\u5883\u3002K3 \u6a21\u578b\u4f9d\u8d56 Python \u8fdb\u884c\u63a8\u7406\u548c\u7ba1\u7406\u3002\u4f60\u5e94\u4f7f\u7528\u6700\u65b0\u7684\u7a33\u5b9a\u7248 Python\uff0c\u901a\u5e38\u4e3a Python 3.10 \u6216\u66f4\u9ad8\u7248\u672c\u3002Kimi K3 \u8fd8\u9700\u8981 CUDA \u9a71\u52a8\u4ee5\u53ca\u6df1\u5ea6\u5b66\u4e60\u5e93\u6765\u652f\u6301 GPU \u63a8\u7406\u3002\u4f60\u5fc5\u987b\u4fdd\u6301\u8f6f\u4ef6\u5904\u4e8e\u6700\u65b0\u72b6\u6001\uff0c\u4ee5\u786e\u4fdd\u5b89\u5168\u6027\u4e0e\u6027\u80fd\u3002<\/p>\n \n \n \u5b89\u88c5 Python 3.10 \u6216\u66f4\u9ad8\u7248\u672c\u3002<\/p>\n<\/li>\n \n \u4e3a GPU \u63a8\u7406\u914d\u7f6e CUDA \u548c cuDNN\u3002<\/p>\n<\/li>\n \n \u4f7f\u7528 PyTorch \u6216 TensorFlow \u8fdb\u884c\u63a8\u7406\u3002<\/p>\n<\/li>\n \n \u66f4\u65b0\u6240\u6709\u9a71\u52a8\u7a0b\u5e8f\u548c\u5e93\uff0c\u4ee5\u63d0\u5347\u5b89\u5168\u6027\u3002<\/p>\n<\/li>\n \n \u68c0\u67e5\u4e0e\u4f60\u7684\u64cd\u4f5c\u7cfb\u7edf\u662f\u5426\u517c\u5bb9\u3002<\/p>\n<\/li>\n<\/ul>\n \n \u5b89\u5168\u8b66\u793a\uff1a<\/strong>\u4f60\u5fc5\u987b\u59cb\u7ec8\u66f4\u65b0\u8f6f\u4ef6\u548c\u9a71\u52a8\u3002\u8fc7\u65f6\u7684\u8f6f\u4ef6\u53ef\u80fd\u4f1a\u5bfc\u81f4\u63a8\u7406\u9519\u8bef\u548c\u5b89\u5168\u98ce\u9669\u3002<\/p>\n<\/blockquote>\n \u4f60\u5fc5\u987b\u9075\u5faa\u8fd9\u4e9b Kimi K3 \u670d\u52a1\u5668\u8981\u6c42\uff0c\u624d\u80fd\u786e\u4fdd\u63a8\u7406\u6d41\u7a0b\u987a\u7545\u5e76\u5177\u5907\u7a33\u56fa\u7684\u5b89\u5168\u6027\u3002\u4e13\u4e1a\u4eba\u5458\u5c06\u5e2e\u52a9\u4f60\u7ba1\u7406 K3 \u6240\u9700\u7684\u786c\u4ef6\u4e0e\u8f6f\u4ef6\u3002\u5728\u5f00\u59cb\u63a8\u7406\u4e4b\u524d\uff0c\u4f60\u5e94\u59cb\u7ec8\u68c0\u67e5\u81ea\u5df1\u7684\u6574\u4f53\u73af\u5883\u914d\u7f6e\u3002<\/p>\n Kimi K3 \u6a21\u578b\u67b6\u6784<\/strong><\/h2>\n \u4e3a\u4ec0\u4e48\u786c\u4ef6\u81f3\u5173\u91cd\u8981<\/h3>\n \u5728\u90e8\u7f72 Kimi K3 \u65f6\uff0c\u4f60\u4f1a\u9762\u4e34\u72ec\u7279\u7684\u6311\u6218\u3002\u8be5\u6a21\u578b\u4ee5 2.8 \u4e07\u4ebf\u53c2\u6570\u89c4\u6a21\u548c\u591a\u6a21\u6001\u80fd\u529b\u800c\u663e\u5f97\u4e0e\u4f17\u4e0d\u540c\u3002\u5b83\u91c7\u7528\u5f00\u653e\u6743\u91cd\u8bbe\u8ba1\uff0c\u8fd9\u610f\u5473\u7740\u4f60\u53ef\u4ee5\u8bbf\u95ee\u5e76\u4fee\u6539\u6a21\u578b\uff0c\u4ee5\u9002\u914d\u4e0d\u540c\u4efb\u52a1\u3002K3 \u7684\u8d85\u5927\u89c4\u6a21\u5bf9\u786c\u4ef6\u63d0\u51fa\u4e86\u6781\u9ad8\u8981\u6c42\u3002\u4f60\u9700\u8981\u5927\u5bb9\u91cf GPU \u663e\u5b58\u4e0e\u9ad8\u901f\u4e92\u8054\uff0c\u624d\u80fd\u627f\u8f7d\u5176\u590d\u6742\u6027\u3002Kimi K3 \u4f9d\u8d56\u9ad8\u6548\u7684\u6ce8\u610f\u529b\u673a\u5236\u548c\u4e13\u5bb6\u6fc0\u6d3b\u7b56\u7565\u3002\u8fd9\u4e9b\u7279\u6027\u90fd\u9700\u8981\u5927\u91cf\u8ba1\u7b97\u8d44\u6e90\u3002\u82e5\u8981\u5b9e\u73b0\u6700\u4f73\u63a8\u7406\u6548\u7387\uff0c\u4f60\u5fc5\u987b\u91c7\u7528\u62e5\u6709 64 \u5f20\u6216\u66f4\u591a\u52a0\u901f\u5361\u7684\u8d85\u7ea7\u8282\u70b9\u914d\u7f6e\u3002<\/p>\n Kimi K3 \u7684\u67b6\u6784\u4f1a\u5c06\u786c\u4ef6\u63a8\u5411\u6781\u9650\u3002\u9ad8\u663e\u5b58\u4e4b\u6240\u4ee5\u5173\u952e\uff0c\u662f\u56e0\u4e3a\u8be5\u6a21\u578b\u91c7\u7528\u4e86 Mixture-of-Experts\uff08\u4e13\u5bb6\u6df7\u5408\uff09\u7cfb\u7edf\u3002\u8fd9\u4e2a\u7cfb\u7edf\u8d1f\u8d23\u5728\u4f17\u591a\u4e13\u5bb6\u4e4b\u95f4\u8fdb\u884c token \u7684\u8def\u7531\u4e0e\u5904\u7406\u3002\u5b83\u8fd8\u652f\u6301\u957f\u8fbe\u4e00\u767e\u4e07 token \u7684\u8d85\u957f\u4e0a\u4e0b\u6587\u7a97\u53e3\u3002\u4f60\u5fc5\u987b\u4e00\u6b21\u6027\u5b58\u50a8\u5e76\u5904\u7406\u6d77\u91cf\u4fe1\u606f\u3002K3 \u7684\u8fd9\u4e9b\u7279\u6027\u8fdb\u4e00\u6b65\u63d0\u9ad8\u4e86\u5185\u5b58\u9700\u6c42\uff0c\u4e5f\u4f1a\u5bf9\u4f60\u7684\u786c\u4ef6\u9020\u6210\u66f4\u5927\u538b\u529b\u3002<\/p>\n \n \u6ce8\u610f\uff1a<\/strong>Kimi K3 \u91c7\u7528\u4e86\u91cf\u5316\u611f\u77e5\u8bad\u7ec3\u3002\u8fd9\u79cd\u65b9\u6cd5\u63d0\u9ad8\u4e86\u786c\u4ef6\u517c\u5bb9\u6027\uff0c\u5e76\u964d\u4f4e\u4e86\u5185\u5b58\u5360\u7528\u3002\u4f60\u53ef\u4ee5\u5c06\u6a21\u578b\u90e8\u7f72\u5230\u66f4\u5e7f\u6cdb\u7684\u7cfb\u7edf\u4e0a\uff0c\u4f46\u82e5\u60f3\u83b7\u5f97\u6700\u4f73\u6548\u679c\uff0c\u4ecd\u7136\u9700\u8981\u5f3a\u5927\u7684 GPU\u3002<\/p>\n<\/blockquote>\n \u5173\u952e\u7ec4\u6210\u90e8\u5206<\/h3>\n \u4e3a\u4e86\u505a\u597d\u786c\u4ef6\u51c6\u5907\uff0c\u4f60\u5fc5\u987b\u7406\u89e3\u8be5\u6a21\u578b\u7684\u6838\u5fc3\u7ec4\u6210\u3002\u6a21\u578b\u5305\u62ec\uff1a<\/p>\n \n \n \u8d85\u5927\u53c2\u6570\u89c4\u6a21\uff082.8T\uff09\uff0c\u7528\u4e8e\u590d\u6742\u6df1\u5ea6\u5b66\u4e60\u4efb\u52a1\u3002<\/p>\n<\/li>\n \n \u591a\u6a21\u6001\u652f\u6301\uff0c\u53ef\u5904\u7406\u6587\u672c\u3001\u56fe\u50cf\u53ca\u5176\u4ed6\u6570\u636e\u7c7b\u578b\u3002<\/p>\n<\/li>\n \n \u5f00\u653e\u6743\u91cd\u67b6\u6784\uff0c\u4fbf\u4e8e\u7075\u6d3b\u90e8\u7f72\u3002<\/p>\n<\/li>\n \n Mixture-of-Experts \u7cfb\u7edf\uff0c\u7528\u4e8e\u9ad8\u6548\u7684 token \u8def\u7531\u3002<\/p>\n<\/li>\n \n \u91cf\u5316\u611f\u77e5\u8bad\u7ec3\uff0c\u4ee5\u63d0\u5347\u786c\u4ef6\u517c\u5bb9\u6027\u3002<\/p>\n<\/li>\n<\/ul>\n Kimi K3 \u9700\u8981\u9ad8\u6027\u80fd GPU \u52a0\u901f\u4e0e\u9ad8\u5e26\u5bbd\u901a\u4fe1\u3002\u4f60\u5fc5\u987b\u4f7f\u7528\u4f01\u4e1a\u7ea7 GPU \u548c\u9ad8\u901f\u4e92\u8054\u3002\u6a21\u578b\u5728\u8d85\u7ea7\u8282\u70b9\u96c6\u7fa4\u4e2d\u80fd\u83b7\u5f97\u66f4\u597d\u7684\u63a8\u7406\u901f\u5ea6\u4e0e\u53ef\u9760\u6027\u3002\u4f60\u8fd8\u9700\u8981\u5177\u5907\u4e13\u4e1a\u80fd\u529b\u7684\u4eba\u5458\u6765\u8d1f\u8d23 K3 \u7684\u90e8\u7f72\u4e0e\u7ef4\u62a4\u3002\u5145\u5206\u51c6\u5907\uff0c\u624d\u80fd\u786e\u4fdd\u90e8\u7f72\u987a\u5229\u4e14\u5b89\u5168\u7a33\u56fa\u3002<\/p>\n \u786c\u4ef6\u51c6\u5907\u6b65\u9aa4<\/strong><\/h2>\n GPU \u9009\u62e9<\/h3>\n \u4f60\u9700\u8981\u9009\u62e9\u80fd\u591f\u627f\u53d7 K3 \u8d1f\u8f7d\u7684 GPU\u3002K3 \u7684\u6a21\u578b\u89c4\u6a21\u4ee5\u53ca Kimi K3 \u7684\u590d\u6742\u6027\u90fd\u8981\u6c42\u4f7f\u7528\u9ad8\u7aef\u52a0\u901f\u5361\u3002\u4f60\u5e94\u9009\u62e9\u5177\u6709\u5927\u5bb9\u91cf\u663e\u5b58\u548c\u9ad8\u901f\u4e92\u8054\u80fd\u529b\u7684 GPU\u3002\u8bb8\u591a\u7528\u6237\u66f4\u503e\u5411\u4e8e\u4e3a K3 \u9009\u62e9 NVIDIA A100 \u6216\u540c\u7ea7\u522b\u4f01\u4e1a\u7ea7\u663e\u5361\u3002\u4f60\u8fd8\u5fc5\u987b\u786e\u8ba4\u8fd9\u4e9b GPU \u652f\u6301\u6700\u65b0\u7684 CUDA \u548c\u6df1\u5ea6\u5b66\u4e60\u5e93\u3002\u5728\u6b63\u5f0f\u8fd0\u884c\u4e4b\u524d\uff0c\u8bf7\u6309\u4ee5\u4e0b\u6b65\u9aa4\u51c6\u5907\u786c\u4ef6\uff1a<\/p>\n \n \n \u68c0\u67e5\u4f60\u7684 vLLM \u7248\u672c\u662f\u5426\u652f\u6301\u50cf K3 \u8fd9\u6837\u7684\u5927\u578b Mixture-of-Experts \u6a21\u578b\u3002\u5c06\u5f53\u524d\u7248\u672c\u4e0e K3 \u7684\u6a21\u578b\u5361\u8fdb\u884c\u5bf9\u7167\u3002<\/p>\n<\/li>\n \n \u521b\u5efa\u7528\u4e8e\u9884\u90e8\u7f72\u6d4b\u8bd5\u7684\u865a\u62df\u73af\u5883\uff1a<\/p>\n python -m venv ~\/vllm-kimi-staging\r\nsource ~\/vllm-kimi-staging\/bin\/activate\r\npip install -U vllm<\/code><\/pre>\n<\/li>\n \n \u4e3a bf16 \u5206\u7247\u548c\u7f13\u5b58\u9884\u7559\u8db3\u591f\u7684\u78c1\u76d8\u7a7a\u95f4\u3002\u53ef\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n df -h<\/code><\/pre>\n<\/li>\n \n \u5982\u679c\u4f60\u9700\u8981\u8bbf\u95ee\u53d7\u9650\u7684 Kimi \u4ed3\u5e93\uff0c\u8bf7\u767b\u5f55 Hugging Face\uff1a<\/p>\n huggingface-cli login<\/code><\/pre>\n<\/li>\n<\/ol>\n \u5185\u5b58\u4e0e\u5b58\u50a8<\/h3>\n Kimi K3 \u9700\u8981\u5927\u91cf\u5185\u5b58\u548c\u5b58\u50a8\u7a7a\u95f4\u3002\u4f60\u5fc5\u987b\u540c\u65f6\u4e3a\u6a21\u578b\u6587\u4ef6\u548c\u989d\u5916\u7684\u63a8\u7406\u7a7a\u95f4\u505a\u597d\u89c4\u5212\u3002\u4e0b\u8868\u5c55\u793a\u4e86\u4e3b\u8981\u8981\u6c42\uff1a<\/p>\n \n\n\n\n\n <\/colgroup>\n\n\n\n\n\n\n\n \n \u8981\u6c42\u9879<\/p>\n<\/th>\n \n \u6570\u503c<\/p>\n<\/th>\n<\/tr>\n \n \u53c2\u6570\u603b\u91cf<\/p>\n<\/td>\n \n 2.8 \u4e07\u4ebf<\/p>\n<\/td>\n<\/tr>\n \n \u7406\u8bba\u6700\u4f4e\u5b58\u50a8\u9700\u6c42<\/p>\n<\/td>\n \n \u7ea6 1.49 TB<\/p>\n<\/td>\n<\/tr>\n \n \u63a8\u7406\u6240\u9700\u9644\u52a0\u5185\u5b58<\/p>\n<\/td>\n \n \u8f83\u5927\uff08\u89c6\u60c5\u51b5\u800c\u5b9a\uff09<\/p>\n<\/td>\n<\/tr>\n \n \u63a8\u8350\u96c6\u7fa4\u914d\u7f6e<\/p>\n<\/td>\n \n \u591a\u8282\u70b9\u96c6\u7fa4<\/p>\n<\/td>\n<\/tr>\n \n \u4e0a\u4e0b\u6587\u7a97\u53e3<\/p>\n<\/td>\n \n \u4e00\u767e\u4e07 token<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n \u5728\u542f\u52a8 K3 \u4e4b\u524d\uff0c\u4f60\u5e94\u59cb\u7ec8\u68c0\u67e5\u78c1\u76d8\u4f7f\u7528\u60c5\u51b5\u3002\u6a21\u578b\u901a\u5e38\u8fd8\u9700\u8981\u989d\u5916\u7a7a\u95f4\u6765\u4fdd\u5b58\u65e5\u5fd7\u4e0e\u7f13\u5b58\u3002\u591a\u8282\u70b9\u96c6\u7fa4\u6709\u52a9\u4e8e\u5206\u62c5\u5185\u5b58\u8d1f\u8f7d\u5e76\u63d0\u5347\u6027\u80fd\u3002<\/p>\n \u4f9b\u7535\u4e0e\u6563\u70ed<\/h3>\n K3 \u786c\u4ef6\u4f1a\u4ea7\u751f\u5927\u91cf\u70ed\u91cf\uff0c\u5e76\u6d88\u8017\u5927\u91cf\u7535\u529b\u3002\u4f60\u5fc5\u987b\u8ba9\u7cfb\u7edf\u4fdd\u6301\u51c9\u723d\u4e0e\u7a33\u5b9a\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u6700\u4f73\u5b9e\u8df5\uff1a<\/p>\n \n \n \u5c06 K3 \u786c\u4ef6\u653e\u7f6e\u5728\u901a\u98ce\u826f\u597d\u7684\u533a\u57df\uff0c\u907f\u514d\u5bc6\u95ed\u7a7a\u95f4\u3002<\/p>\n<\/li>\n \n \u4f7f\u7528 sudo powermetrics --samplers smc<\/code> \u76d1\u63a7\u6e29\u5ea6\u3002<\/p>\n<\/li>\n \n \u4f7f\u7528\u5916\u90e8\u6563\u70ed\u65b9\u6848\uff0c\u4f8b\u5982\u53f0\u5f0f\u98ce\u6247\u6216\u6563\u70ed\u5e95\u5ea7\u3002<\/p>\n<\/li>\n<\/ul>\n \n \u6ce8\u610f\uff1a\u826f\u597d\u7684\u6563\u70ed\u80fd\u591f\u4fdd\u62a4\u786c\u4ef6\uff0c\u5e76\u4fdd\u6301\u63a8\u7406\u8fc7\u7a0b\u7a33\u5b9a\u3002<\/p>\n<\/blockquote>\n \u4f60\u5fc5\u987b\u8ba4\u771f\u505a\u597d\u786c\u4ef6\u51c6\u5907\u3002\u8fd9\u4e9b\u6b65\u9aa4\u80fd\u591f\u5e2e\u52a9\u4f60\u907f\u514d\u95ee\u9898\uff0c\u5e76\u8ba9 K3 \u90e8\u7f72\u83b7\u5f97\u6700\u4f73\u6548\u679c\u3002<\/p>\n \u73af\u5883\u914d\u7f6e<\/strong><\/h2>\n \u64cd\u4f5c\u7cfb\u7edf\u517c\u5bb9\u6027<\/h3>\n \u4f60\u5fc5\u987b\u9009\u62e9\u4e00\u4e2a\u80fd\u591f\u652f\u6491 Kimi K3 \u8d1f\u8f7d\u7684\u64cd\u4f5c\u7cfb\u7edf\u3002\u5927\u591a\u6570\u7528\u6237\u4f1a\u9009\u62e9 Ubuntu \u6216 CentOS \u7b49 Linux \u53d1\u884c\u7248\u3002\u8fd9\u4e9b\u7cfb\u7edf\u80fd\u591f\u8f83\u597d\u5730\u652f\u6301 GPU \u9a71\u52a8\u548c\u6df1\u5ea6\u5b66\u4e60\u5e93\u3002\u5982\u679c\u4f60\u5728 Apple \u786c\u4ef6\u4e0a\u90e8\u7f72\uff0c\u4e5f\u53ef\u4ee5\u4f7f\u7528 macOS\u3002Windows \u5728 K3 \u573a\u666f\u4e2d\u8f83\u5c11\u89c1\uff0c\u4f46\u53ef\u4ee5\u7528\u4e8e\u6d4b\u8bd5\u3002\u8bf7\u786e\u4fdd\u4f60\u7684\u64cd\u4f5c\u7cfb\u7edf\u652f\u6301 Python 3.10 \u6216\u66f4\u9ad8\u7248\u672c\u3002\u5728\u5b89\u88c5\u4e4b\u524d\uff0c\u4f60\u8fd8\u5e94\u68c0\u67e5\u5e76\u5b89\u88c5\u5b89\u5168\u66f4\u65b0\u3002<\/p>\n \n \u63d0\u793a\uff1a\u5bf9\u4e8e\u7a33\u5b9a\u7684 Kimi K3 \u90e8\u7f72\uff0c\u5efa\u8bae\u4f7f\u7528 Ubuntu 22.04 LTS\u3002\u8fd9\u4e2a\u7248\u672c\u4e0e\u5927\u591a\u6570 GPU \u9a71\u52a8\u548c\u5e93\u90fd\u5177\u6709\u826f\u597d\u517c\u5bb9\u6027\u3002<\/p>\n<\/blockquote>\n \u9a71\u52a8\u4e0e\u4f9d\u8d56\u9879<\/h3>\n \u4f60\u9700\u8981\u4e3a Kimi K3 \u5b89\u88c5\u6b63\u786e\u7684\u9a71\u52a8\u7a0b\u5e8f\u548c\u4f9d\u8d56\u9879\u3002GPU \u9a71\u52a8\u662f\u8fd0\u884c K3 \u6a21\u578b\u7684\u57fa\u7840\u3002\u5982\u679c\u4f60\u5728 NVIDIA \u786c\u4ef6\u4e0a\u90e8\u7f72\uff0c\u5e94\u4f7f\u7528\u6700\u65b0\u7684 NVIDIA CUDA \u9a71\u52a8\u3002\u5bf9\u4e8e Apple \u786c\u4ef6\uff0c\u5219\u5e94\u5b89\u88c5\u6700\u65b0\u7684 macOS \u66f4\u65b0\u3002\u50cf PyTorch \u548c TensorFlow \u8fd9\u6837\u7684\u6df1\u5ea6\u5b66\u4e60\u5e93\u80fd\u591f\u652f\u6301 Kimi K3 \u63a8\u7406\u3002\u4f60\u8fd8\u5fc5\u987b\u5b89\u88c5 cuDNN \u6765\u5b9e\u73b0 GPU \u52a0\u901f\u3002\u59cb\u7ec8\u66f4\u65b0\u9a71\u52a8\u548c\u5e93\uff0c\u4ee5\u907f\u514d\u9519\u8bef\u3002<\/p>\n \u4ee5\u4e0b\u662f\u9a71\u52a8\u4e0e\u4f9d\u8d56\u9879\u7684\u68c0\u67e5\u6e05\u5355\uff1a<\/p>\n \n \n \u5b89\u88c5 CUDA Toolkit\uff0812 \u6216\u66f4\u9ad8\u7248\u672c\uff09<\/p>\n<\/li>\n \n \u5b89\u88c5 cuDNN \u4ee5\u652f\u6301 GPU<\/p>\n<\/li>\n \n \u5b89\u88c5 Python 3.10 \u6216\u66f4\u9ad8\u7248\u672c<\/p>\n<\/li>\n \n \u5b89\u88c5 PyTorch \u6216 TensorFlow<\/p>\n<\/li>\n \n \u66f4\u65b0\u6240\u6709\u9a71\u52a8\u548c\u5e93<\/p>\n<\/li>\n<\/ul>\n \n \u5b89\u5168\u8b66\u793a\uff1a\u8fc7\u65f6\u7684\u9a71\u52a8\u7a0b\u5e8f\u53ef\u80fd\u5bfc\u81f4\u63a8\u7406\u5931\u8d25\u3002\u5728\u8fd0\u884c K3 \u4e4b\u524d\uff0c\u8bf7\u5148\u66f4\u65b0\u4f60\u7684\u7cfb\u7edf\u3002<\/p>\n<\/blockquote>\n \u7f51\u7edc\u914d\u7f6e<\/h3>\n \u4f60\u5fc5\u987b\u4e3a Kimi K3 \u90e8\u7f72\u51c6\u5907\u597d\u7f51\u7edc\u73af\u5883\u3002K3 \u6a21\u578b\u8981\u6c42\u8282\u70b9\u4e4b\u95f4\u5177\u5907\u5feb\u901f\u4e14\u7a33\u5b9a\u7684\u8fde\u63a5\u3002\u5bf9\u4e8e\u591a\u8282\u70b9\u96c6\u7fa4\uff0c\u4f60\u5e94\u4f7f\u7528\u9ad8\u901f\u4ee5\u592a\u7f51\u6216 InfiniBand\u3002\u8bf7\u4f7f\u7528\u9632\u706b\u5899\u548c\u8bbf\u95ee\u63a7\u5236\u6765\u4fdd\u62a4\u7f51\u7edc\u5b89\u5168\u3002Kimi K3 \u7684\u4e0b\u8f7d\u91cf\u53ef\u9ad8\u8fbe 1.4 TB\uff0c\u56e0\u6b64\u4f60\u9700\u8981\u53ef\u9760\u7684\u5e26\u5bbd\u3002\u5728\u5f00\u59cb\u4e0b\u8f7d\u4e4b\u524d\uff0c\u4f60\u5fc5\u987b\u5148\u68c0\u67e5\u7f51\u7edc\u901f\u5ea6\u3002\u5bf9\u4e8e\u4e91\u7aef\u90e8\u7f72\uff0c\u8bf7\u4f7f\u7528\u79c1\u6709\u7f51\u7edc\u6765\u4fdd\u62a4\u6570\u636e\u3002<\/p>\n \u4e0b\u9762\u662f\u4e00\u4efd\u7b80\u5355\u7684\u7f51\u7edc\u914d\u7f6e\u8868\uff1a<\/p>\n \n\n\n\n\n <\/colgroup>\n\n\n\n\n\n\n \n \u7ec4\u4ef6<\/p>\n<\/th>\n \n \u63a8\u8350\u914d\u7f6e<\/p>\n<\/th>\n<\/tr>\n \n \u96c6\u7fa4\u7f51\u7edc<\/p>\n<\/td>\n \n InfiniBand \/ \u4ee5\u592a\u7f51<\/p>\n<\/td>\n<\/tr>\n \n \u5e26\u5bbd<\/p>\n<\/td>\n \n 10 Gbps \u6216\u66f4\u9ad8<\/p>\n<\/td>\n<\/tr>\n \n \u5b89\u5168\u63aa\u65bd<\/p>\n<\/td>\n \n \u9632\u706b\u5899\u3001VPN<\/p>\n<\/td>\n<\/tr>\n \n \u4e0b\u8f7d\u901f\u5ea6<\/p>\n<\/td>\n \n \u6700\u4f4e 1 Gbps<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n \n \u6ce8\u610f\uff1a\u5f3a\u5065\u7684\u7f51\u7edc\u80fd\u591f\u8ba9\u63a8\u7406\u8fc7\u7a0b\u66f4\u7a33\u5b9a\u3001\u66f4\u5b89\u5168\u3002\u5728\u90e8\u7f72 K3 \u4e4b\u524d\uff0c\u8bf7\u5148\u6d4b\u8bd5\u4f60\u7684\u7f51\u7edc\u73af\u5883\u3002<\/p>\n<\/blockquote>\n Kimi K3 \u7684\u90e8\u7f72\u573a\u666f<\/strong><\/h2>\n \u6570\u636e\u4e2d\u5fc3\u4e0e\u4e91\u7aef<\/h3>\n \u4f60\u53ef\u4ee5\u5728\u6570\u636e\u4e2d\u5fc3\u90e8\u7f72 Kimi K3\uff0c\u4e5f\u53ef\u4ee5\u4f7f\u7528 K3 \u4e91\u670d\u52a1\u3002\u6570\u636e\u4e2d\u5fc3\u80fd\u591f\u63d0\u4f9b\u5f3a\u5927\u7684\u57fa\u7840\u8bbe\u65bd\u548c\u9ad8\u901f\u7f51\u7edc\u3002\u4f60\u53ef\u4ee5\u83b7\u5f97\u4f01\u4e1a\u7ea7 GPU \u548c\u53ef\u9760\u4f9b\u7535\u3002K3 \u4e91\u5e73\u53f0\u5219\u5141\u8bb8\u4f60\u6309\u5c0f\u65f6\u79df\u7528 GPU\u3002\u4f60\u53ef\u4ee5\u5728\u9700\u8981\u65f6\u5feb\u901f\u542f\u7528 A100 \u8282\u70b9\u3002\u8fd9\u79cd\u65b9\u5f0f\u975e\u5e38\u9002\u5408\u7a81\u53d1\u6027\u5de5\u4f5c\u8d1f\u8f7d\uff0c\u4ee5\u53ca\u5e0c\u671b\u907f\u514d\u524d\u671f\u8d44\u672c\u652f\u51fa\u7684\u56e2\u961f\u3002Kimi K3 \u4e91\u670d\u52a1\u80fd\u591f\u7b80\u5316\u6269\u5bb9\u4e0e\u7ef4\u62a4\u3002\u4f60\u53ea\u9700\u4e3a\u5b9e\u9645\u4f7f\u7528\u91cf\u4ed8\u8d39\uff0c\u5e76\u5728\u63a8\u7406\u5b8c\u6210\u540e\u91ca\u653e\u8d44\u6e90\u3002\u8bb8\u591a\u56e2\u961f\u4f1a\u5148\u4ece K3 \u4e91\u5f00\u59cb\u8bc4\u4f30\u6027\u80fd\uff0c\u518d\u51b3\u5b9a\u662f\u5426\u91c7\u8d2d\u81ea\u6709\u786c\u4ef6\u3002<\/p>\n \n \u63d0\u793a\uff1aK3 \u4e91\u90e8\u7f72\u53ef\u4ee5\u7f29\u77ed\u642d\u5efa\u65f6\u95f4\uff0c\u5e76\u63d0\u4f9b\u66f4\u9ad8\u7075\u6d3b\u6027\u3002\u4f60\u53ef\u4ee5\u5148\u6d4b\u8bd5\u6a21\u578b\uff0c\u800c\u65e0\u9700\u8d2d\u4e70\u6602\u8d35\u8bbe\u5907\u3002<\/p>\n<\/blockquote>\n \u672c\u5730\u81ea\u5efa\u96c6\u7fa4<\/h3>\n 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\u4f60\u53ef\u4ee5\u5b8c\u5168\u638c\u63a7\u786c\u4ef6\u73af\u5883\u3002<\/p>\n<\/li>\n \n \u4f60\u5fc5\u987b\u81ea\u884c\u5904\u7406\u5347\u7ea7\u548c\u6545\u969c\u6392\u67e5\u3002<\/p>\n<\/li>\n \n \u4f60\u9700\u8981\u5f3a\u5927\u7684 IT \u652f\u6301\u6765\u7ef4\u62a4 K3 \u96c6\u7fa4\u3002<\/p>\n<\/li>\n<\/ul>\n \u4f60\u5fc5\u987b\u8ba4\u771f\u505a\u597d\u786c\u4ef6\u51c6\u5907\u3002\u5728\u5f00\u59cb K3 \u90e8\u7f72\u4e4b\u524d\uff0c\u8bf7\u590d\u6838\u6bcf\u4e00\u4e2a\u6b65\u9aa4\u3002\u786e\u4fdd\u4f60\u7684 GPU\u3001\u5185\u5b58\u548c\u5b58\u50a8\u6ee1\u8db3 Kimi K3 \u7684\u9700\u6c42\u3002\u4e13\u4e1a\u4eba\u5458\u80fd\u591f\u5e2e\u52a9\u4f60\u907f\u514d\u5931\u8bef\uff0c\u5e76\u8ba9 K3 \u4fdd\u6301\u826f\u597d\u8fd0\u884c\u3002\u8bf7\u4f7f\u7528\u68c0\u67e5\u6e05\u5355\u786e\u8ba4\u4f60\u7684\u73af\u5883\u7b26\u5408\u8981\u6c42\u3002\u5728\u6301\u7eed\u4f18\u5316\u4f60\u7684 Kimi \u4e0e K3 \u73af\u5883\u65f6\uff0c\u4e5f\u5e94\u53cd\u590d\u53c2\u8003\u672c\u6307\u5357\u3002\u5468\u5bc6\u89c4\u5212\uff0c\u624d\u80fd\u5e26\u6765\u6700\u4f73\u7ed3\u679c\u3002<\/p>\n \u5e38\u89c1\u95ee\u9898<\/strong><\/h2>\n \u662f\u4ec0\u4e48\u8ba9 Kimi K3 \u4e0e\u5176\u4ed6\u5927\u6a21\u578b\u4e0d\u540c\uff1f<\/h3>\n \u4f60\u9762\u5bf9\u7684\u662f\u4e00\u4e2a\u62e5\u6709 2.8 \u4e07\u4ebf\u53c2\u6570\u7684\u6a21\u578b\u3002Kimi K3 \u91c7\u7528 Mixture-of-Experts \u7cfb\u7edf\uff0c\u5e76\u652f\u6301\u591a\u6a21\u6001\u6570\u636e\u3002\u4f60\u8fd8\u53ef\u4ee5\u4ee5\u5f00\u653e\u6743\u91cd\u65b9\u5f0f\u90e8\u7f72\u5b83\uff0c\u8fd9\u4e3a\u7814\u7a76\u548c\u5b9a\u5236\u4efb\u52a1\u63d0\u4f9b\u4e86\u66f4\u9ad8\u7075\u6d3b\u6027\u3002<\/p>\n \u53ef\u4ee5\u5728\u5355\u53f0\u5de5\u4f5c\u7ad9\u4e0a\u8fd0\u884c Kimi K3 \u5417\uff1f<\/h3>\n \u8981\u5b8c\u6574\u90e8\u7f72 Kimi 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