{"id":80,"date":"2026-03-04T16:20:14","date_gmt":"2026-03-04T08:20:14","guid":{"rendered":"http:\/\/23.95.50.216:8080\/?p=80"},"modified":"2026-03-04T16:20:24","modified_gmt":"2026-03-04T08:20:24","slug":"tesla-t10-%e5%8f%8c%e5%8d%a1%e6%9c%ba%e5%99%a8%e7%9a%84%e6%a8%a1%e5%9e%8b%e9%83%a8%e7%bd%b2%e5%bb%ba%e8%ae%ae-by%e5%8d%83%e9%97%ae","status":"publish","type":"post","link":"https:\/\/deepbule.store\/?p=80","title":{"rendered":"Tesla T10 \u53cc\u5361\u673a\u5668\u7684\u6a21\u578b\u90e8\u7f72\u5efa\u8bae by\u5343\u95ee"},"content":{"rendered":"

\u65e2\u7136\u4f60\u5df2\u7ecf\u89e3\u51b3\u4e86 Tesla T10 \u6700\u68d8\u624b\u7684\u6563\u70ed\u95ee\u9898\uff08\u6539\u88c5\u4e86 2070 \u6da1\u8f6e\u6247\uff09\uff0c\u5e76\u4e14\u8ba1\u5212\u5c06\u8fd9\u4e24\u5f20\u5361\u7ec4\u6210 32GB \u663e\u5b58\u6c60<\/strong> \u4f5c\u4e3a AI \u670d\u52a1\u5668\u4f7f\u7528\uff0c\u8fd9\u662f\u4e00\u4e2a\u975e\u5e38\u5177\u6709\u6027\u4ef7\u6bd4\u7684\u5165\u95e8\u7ea7\u65b9\u6848\u3002<\/p>\n

Turing \u67b6\u6784\uff08RTX 20 \u7cfb\u5217\u6838\u5fc3\uff09\u867d\u7136\u4e0d\u652f\u6301 BF16\uff08Bfloat16\uff09\uff0c\u4f46\u652f\u6301 FP16 \u548c INT8\/INT4 \u91cf\u5316\uff0c\u914d\u5408 32GB \u663e\u5b58\uff0c\u5b8c\u5168\u53ef\u4ee5\u642d\u5efa\u4e00\u4e2a\u5b9e\u7528\u7684\u672c\u5730\u5927\u6a21\u578b\u670d\u52a1\u3002<\/p>\n

\u4ee5\u4e0b\u662f\u9488\u5bf9 \u53cc T10 (32GB)<\/strong> \u914d\u7f6e\u7684\u8be6\u7ec6\u5efa\u8bae\uff1a<\/p>\n

1. \u80fd\u8dd1\u4ec0\u4e48\u6a21\u578b\uff1f\uff08\u6838\u5fc3\u63a8\u8350\uff09<\/h3>\n

\u7531\u4e8e Turing \u67b6\u6784\u7f3a\u4e4f BF16 \u652f\u6301\uff0c\u4e14\u663e\u5b58\u603b\u91cf\u4e3a 32GB\uff0c\u5f3a\u70c8\u5efa\u8bae\u4f7f\u7528 GGUF<\/code> \u683c\u5f0f\u7684\u91cf\u5316\u6a21\u578b<\/strong>\uff0c\u901a\u8fc7 llama.cpp<\/code> (\u6216\u57fa\u4e8e\u5b83\u7684 Ollama, Text-Generation-WebUI) \u8fd0\u884c\u3002<\/p>\n

A. \u9ec4\u91d1\u751c\u70b9\u533a\uff1a7B – 14B \u53c2\u6570\u6a21\u578b (\u5168\u7cbe\u5ea6\u6216\u9ad8\u91cf\u5316)<\/h4>\n

\u8fd9\u662f\u4f60\u76ee\u524d\u914d\u7f6e\u4f53\u9a8c\u6700\u597d\u7684\u533a\u95f4\uff0c\u901f\u5ea6\u6781\u5feb\uff0c\u663e\u5b58\u5360\u7528\u4f4e\uff0c\u751a\u81f3\u53ef\u4ee5\u9884\u7559\u4e00\u90e8\u5206\u7ed9\u957f\u4e0a\u4e0b\u6587\uff08Context Window\uff09\u3002<\/p>\n

    \n
  • \u63a8\u8350\u6a21\u578b\uff1a<\/strong><\/li>\n
  • Qwen2.5-7B-Instruct<\/strong> (\u963f\u91cc\u6700\u65b0\uff0c\u4e2d\u6587\u80fd\u529b\u6781\u5f3a\uff0c\u903b\u8f91\u597d) -> \u63a8\u8350\u91cf\u5316\uff1aQ6_K<\/code> \u6216 Q8_0<\/code> (\u51e0\u4e4e\u65e0\u635f)\u3002<\/li>\n
  • Llama-3.1-8B-Instruct<\/strong> (Meta \u6700\u65b0\uff0c\u82f1\u6587\u53ca\u901a\u7528\u903b\u8f91\u5f3a) -> \u63a8\u8350\u91cf\u5316\uff1aQ8_0<\/code> \u6216 Q6_K<\/code>\u3002<\/li>\n
  • Gemma-2-9B-Instruct<\/strong> (Google\uff0c\u903b\u8f91\u63a8\u7406\u4e0d\u9519) -> \u63a8\u8350\u91cf\u5316\uff1aQ6_K<\/code>\u3002<\/li>\n
  • Yi-1.5-9B-Chat<\/strong> (\u96f6\u4e00\u4e07\u7269\uff0c\u4e2d\u6587\u4f18\u79c0)\u3002<\/li>\n
  • \u663e\u5b58\u5360\u7528\u9884\u4f30\uff1a<\/strong> \u7ea6 6GB – 9GB\u3002<\/li>\n
  • \u5269\u4f59\u8d44\u6e90\uff1a<\/strong> \u4f60\u53ef\u4ee5\u5f00\u542f 16k – 32k<\/strong> \u7684\u4e0a\u4e0b\u6587\u7a97\u53e3\uff0c\u6216\u8005\u540c\u65f6\u8dd1\u4e24\u4e2a\u8fd9\u6837\u7684\u6a21\u578b\u5b9e\u4f8b\u3002<\/li>\n
  • \u9884\u671f\u901f\u5ea6\uff1a<\/strong> \u53cc\u5361\u5e76\u884c\uff0c\u9884\u8ba1\u53ef\u8fbe 40 – 60 tokens\/s<\/strong> (\u975e\u5e38\u5feb\uff0c\u9002\u5408\u5b9e\u65f6\u5bf9\u8bdd)\u3002<\/li>\n<\/ul>\n

    B. \u4e3b\u529b\u5b9e\u7528\u533a\uff1a20B – 35B \u53c2\u6570\u6a21\u578b (\u4e2d\u9ad8\u91cf\u5316)<\/h4>\n

    \u8fd9\u662f 32GB \u663e\u5b58\u7684\u201c\u8212\u9002\u533a\u201d\uff0c\u80fd\u8dd1\u6bd4 7B \u806a\u660e\u5f97\u591a\u7684\u6a21\u578b\uff0c\u9002\u5408\u590d\u6742\u4efb\u52a1\u3001\u4ee3\u7801\u751f\u6210\u3001\u957f\u6587\u6863\u5206\u6790\u3002<\/p>\n

      \n
    • \u63a8\u8350\u6a21\u578b\uff1a<\/strong><\/li>\n
    • Qwen2.5-32B-Instruct<\/strong> (\u76ee\u524d\u7684\u5f00\u6e90\u738b\u8005\u4e4b\u4e00\uff0c\u80fd\u529b\u63a5\u8fd1 Llama-3-70B) -> \u5f3a\u70c8\u63a8\u8350<\/strong>\u3002<\/li>\n
    • \u91cf\u5316\u5efa\u8bae\uff1aQ4_K_M<\/code> (\u7ea6 19GB) \u6216 Q5_K_M<\/code> (\u7ea6 21GB)\u3002<\/li>\n
    • Command R (35B)<\/strong> (\u64c5\u957f RAG \u68c0\u7d22\u589e\u5f3a\u751f\u6210\u548c\u5de5\u5177\u8c03\u7528) -> \u91cf\u5316\u5efa\u8bae\uff1aQ4_K_S<\/code>\u3002<\/li>\n
    • Mixtral-8x7B (MoE)<\/strong> (\u5b9e\u9645\u6fc0\u6d3b\u53c2\u6570\u7ea6 13B\uff0c\u603b\u53c2 47B\uff0c\u4f46\u5728\u63a8\u7406\u65f6\u663e\u5b58\u5360\u7528\u8f83\u5927) -> \u9700 Q3_K_M<\/code> \u6216 Q4_0<\/code> \u624d\u80fd\u585e\u8fdb 32GB \u5e76\u7559\u51fa\u4e0a\u4e0b\u6587\u7a7a\u95f4\u3002<\/li>\n
    • \u663e\u5b58\u5360\u7528\u9884\u4f30\uff1a<\/strong> \u7ea6 18GB – 24GB\u3002<\/li>\n
    • \u5269\u4f59\u8d44\u6e90\uff1a<\/strong> \u53ef\u4fdd\u7559 8GB – 12GB \u7528\u4e8e 16k – 24k<\/strong> \u7684\u4e0a\u4e0b\u6587\u7a97\u53e3\u3002<\/li>\n
    • \u9884\u671f\u901f\u5ea6\uff1a<\/strong> \u7ea6 15 – 25 tokens\/s<\/strong> (\u6d41\u7545\u9605\u8bfb\u901f\u5ea6)\u3002<\/li>\n<\/ul>\n

      C. \u6781\u9650\u6311\u6218\u533a\uff1a70B+ \u53c2\u6570\u6a21\u578b (\u4f4e\u91cf\u5316 + \u7cfb\u7edf\u5185\u5b58\u6ea2\u51fa)<\/h4>\n

      32GB \u663e\u5b58\u65e0\u6cd5\u5b8c\u6574\u52a0\u8f7d 70B \u6a21\u578b\uff0c\u5fc5\u987b\u5229\u7528\u7cfb\u7edf\u5185\u5b58\uff08RAM\uff09\u505a\u6ea2\u51fa\uff08Offload\uff09\uff0c\u901f\u5ea6\u4f1a\u5927\u5e45\u4e0b\u964d\uff0c\u4f46\u80fd\u8dd1<\/strong>\u3002<\/p>\n

        \n
      • \u63a8\u8350\u6a21\u578b\uff1a<\/strong><\/li>\n
      • Llama-3.1-70B-Instruct<\/strong> \/ Qwen2.5-72B-Instruct<\/strong>\u3002<\/li>\n
      • \u91cf\u5316\u5efa\u8bae\uff1aQ2_K<\/code> \u6216 Q3_K_S<\/code> (\u7ea6 24GB – 28GB \u663e\u5b58 + \u5927\u91cf\u7cfb\u7edf\u5185\u5b58)\u3002<\/li>\n
      • \u8fd0\u884c\u65b9\u5f0f\uff1a<\/strong> \u5c06\u5927\u90e8\u5206\u5c42\u653e\u5728 GPU\uff0c\u6700\u540e\u51e0\u5c42\u548c KV Cache \u653e\u5728 CPU \u5185\u5b58\u3002<\/li>\n
      • \u9884\u671f\u901f\u5ea6\uff1a<\/strong> \u7ea6 2 – 5 tokens\/s<\/strong> (\u50cf\u6253\u5b57\u673a\u4e00\u6837\u6162\uff0c\u4ec5\u9002\u5408\u79bb\u7ebf\u5904\u7406\u957f\u6587\u672c\uff0c\u4e0d\u9002\u5408\u804a\u5929)\u3002<\/li>\n
      • \u5efa\u8bae\uff1a<\/strong> \u9664\u975e\u5fc5\u8981\uff0c\u5426\u5219\u4e0d\u63a8\u8350\u65e5\u5e38\u4f7f\u7528\u6b64\u6a21\u5f0f\u3002<\/li>\n<\/ul>\n
        \n

        2. \u8f6f\u4ef6\u6808\u90e8\u7f72\u5efa\u8bae<\/h3>\n

        \u4e3a\u4e86\u6700\u5927\u5316\u5229\u7528\u53cc\u5361\u5e76\u89c4\u907f Turing \u67b6\u6784\u7684\u77ed\u677f\uff0c\u8bf7\u6309\u4ee5\u4e0b\u65b9\u6848\u90e8\u7f72\uff1a<\/p>\n

        \u65b9\u6848 A\uff1aOllama (\u6700\u7b80\u5355\uff0c\u63a8\u8350\u65b0\u624b)<\/h4>\n

        Ollama \u5e95\u5c42\u57fa\u4e8e llama.cpp\uff0c\u81ea\u52a8\u8bc6\u522b\u591a\u5361\u5e76\u5206\u914d\u5c42\u6570\u3002<\/p>\n

          \n
        1. \u5b89\u88c5\uff1a<\/strong>\n
          curl -fsSL https:\/\/ollama.com\/install.sh | sh<\/code><\/pre><\/li>\n
        2. \u914d\u7f6e\u73af\u5883\u53d8\u91cf (\u5173\u952e)\uff1a<\/strong>\n\u786e\u4fdd Ollama \u8bc6\u522b\u5230\u4e24\u5f20\u5361\u3002\u901a\u5e38\u4f1a\u81ea\u52a8\u8bc6\u522b\uff0c\u5982\u679c\u4e0d\u884c\uff0c\u8bbe\u7f6e\uff1a\n
          export OLLAMA_NUM_GPU=2\n# \u5982\u679c\u9700\u8981\u5f3a\u5236\u6307\u5b9a\u663e\u5b58\u5206\u914d\u6bd4\u4f8b\uff08\u901a\u5e38\u4e0d\u9700\u8981\uff0c\u81ea\u52a8\u5e73\u8861\u6700\u597d\uff09\n# export OLLAMA_GPU_OVERHEAD=...<\/code><\/pre><\/li>\n
        3. \u8fd0\u884c\u6a21\u578b\uff1a<\/strong>\n
          ollama run qwen2.5:32b<\/code><\/pre>\n
          Ollama \u4f1a\u81ea\u52a8\u4e0b\u8f7d GGUF \u683c\u5f0f\u5e76\u5c06\u6a21\u578b\u5c42\u5747\u5300\u5206\u5e03\u5728\u4e24\u5f20 T10 \u4e0a\u3002<\/em><\/p><\/li>\n<\/ol>\n
          \u65b9\u6848 B\uff1aText-Generation-WebUI (Oobabooga) (\u529f\u80fd\u6700\u5f3a\uff0c\u9002\u5408\u6298\u817e)<\/h4>\n
          \u5982\u679c\u4f60\u9700\u8981\u66f4\u7cbe\u7ec6\u7684\u63a7\u5236\uff08\u5982\u8c03\u6574\u6e29\u5ea6\u3001Top-P\u3001\u52a0\u8f7d LoRA\u3001\u591a\u7528\u6237\u7ba1\u7406\uff09\u3002<\/p>\n
            \n
          1. \u5b89\u88c5\uff1a<\/strong> \u4f7f\u7528 one-click-installer\u3002<\/li>\n
          2. \u542f\u52a8\u53c2\u6570\uff1a<\/strong>\n\u5728\u542f\u52a8\u811a\u672c\u4e2d\u6dfb\u52a0\uff1a\n
            --model your_model.gguf\n--n-gpu-layers 999 # \u5c3d\u53ef\u80fd\u5c06\u6240\u6709\u5c42\u5378\u8f7d\u5230 GPU\n--tensor-split 1,1 # \u5f3a\u5236\u4e24\u5f20\u5361\u5e73\u5747\u5206\u914d (\u5982\u679c\u81ea\u52a8\u5206\u914d\u4e0d\u5747)\n--context-size 16384 # \u8bbe\u7f6e\u4e0a\u4e0b\u6587\u957f\u5ea6<\/code><\/pre><\/li>\n
          3. \u4f18\u52bf\uff1a<\/strong> \u652f\u6301 API \u63a5\u53e3\uff0c\u65b9\u4fbf\u5bf9\u63a5\u5176\u4ed6\u5e94\u7528\uff08\u5982 Dify, NextChat\uff09\u3002<\/li>\n<\/ol>\n
            \u65b9\u6848 C\uff1avLLM (\u9ad8\u6027\u80fd\u751f\u4ea7\u73af\u5883\uff0c\u4f46\u6709\u95e8\u69db)<\/h4>\n
            \u6ce8\u610f\uff1avLLM \u5bf9 Turing \u67b6\u6784\u652f\u6301\u6709\u9650\uff0c\u4e14\u4e3b\u8981\u4f18\u5316 BF16\u3002\u5bf9\u4e8e T10\uff0c\u53ef\u80fd\u4e0d\u5982 llama.cpp \u7a33\u5b9a\u9ad8\u6548\u3002\u5982\u679c\u8981\u7528\uff0c\u9700\u786e\u8ba4\u7248\u672c\u652f\u6301 FP16 \u63a8\u7406\u4e14\u65e0 BF16 \u4f9d\u8d56\u3002<\/em><\/p>\n
              \n
            • \u5efa\u8bae\uff1a<\/strong> \u73b0\u9636\u6bb5\u4f18\u5148\u9009 llama.cpp\/Ollama<\/strong> \u8def\u7ebf\u3002<\/li>\n<\/ul>\n
              \n
              3. \u5173\u952e\u6ce8\u610f\u4e8b\u9879\u4e0e\u4f18\u5316\u5efa\u8bae<\/h3>\n
              A. \u663e\u5b58\u4e0e\u4e0a\u4e0b\u6587 (Context) \u7684\u6743\u8861<\/h4>\n
                \n
              • \u516c\u5f0f\uff1a<\/strong> \u53ef\u7528\u663e\u5b58 = \u6a21\u578b\u6743\u91cd\u5360\u7528 + (\u4e0a\u4e0b\u6587\u957f\u5ea6 * \u6bcf token \u663e\u5b58\u5360\u7528)<\/code><\/li>\n
              • \u5bf9\u4e8e 32B \u6a21\u578b (Q4)\uff0c\u6743\u91cd\u7ea6\u5360 20GB\u3002\u5269\u4e0b 12GB \u53ef\u4ee5\u7528\u4e8e\u4e0a\u4e0b\u6587\u3002<\/li>\n
              • Q4 \u91cf\u5316\u4e0b\uff0c\u6bcf 1k context \u5927\u7ea6\u5360\u7528 0.5MB – 1MB (\u53d6\u51b3\u4e8e\u5177\u4f53\u5b9e\u73b0\u548c KV Cache \u91cf\u5316)\u3002<\/li>\n
              • \u5efa\u8bae\uff1a<\/strong> \u9ed8\u8ba4\u8bbe\u7f6e Context \u4e3a 16384 (16k)<\/strong> \u6216 24576 (24k)<\/strong>\u3002\u4e0d\u8981\u76f2\u76ee\u5f00\u5230 128k\uff0c\u5426\u5219\u663e\u5b58\u7206\u6ee1\u4f1a\u5bfc\u81f4\u63a8\u7406\u5d29\u6e83\u6216\u6781\u5ea6\u964d\u901f\u3002<\/li>\n<\/ul>\n
                B. \u907f\u514d\u4f7f\u7528\u539f\u751f PyTorch (FP16) \u52a0\u8f7d\u5927\u6a21\u578b<\/h4>\n
                  \n
                • \u4e0d\u8981\u7528 from transformers import ...<\/code> \u76f4\u63a5\u52a0\u8f7d .bin<\/code> \u6216 .safetensors<\/code> \u5168\u96c6\u3002<\/li>\n
                • \u539f\u56e0\uff1aTuring \u5361\u6ca1\u6709 Tensor Core \u5bf9 BF16 \u7684\u652f\u6301\uff0cFP16 \u5bb9\u6613\u6ea2\u51fa\u6216\u7cbe\u5ea6\u635f\u5931\uff0c\u4e14\u539f\u751f\u52a0\u8f7d\u5f88\u96be\u5b8c\u7f8e\u5207\u5206\u663e\u5b58\u3002<\/li>\n
                • \u575a\u6301\u4f7f\u7528 GGUF \u683c\u5f0f<\/strong>\u3002<\/li>\n<\/ul>\n
                  C. PCIe \u5e26\u5bbd\u74f6\u9888<\/h4>\n
                    \n
                  • T10 \u901a\u5e38\u662f PCIe 3.0 x16 \u6216 x8 (\u53d6\u51b3\u4e8e\u4e3b\u677f\u548c\u8f6c\u63a5\u5361)\u3002<\/li>\n
                  • \u53cc\u5361\u4e4b\u95f4\u901a\u4fe1\u8d70 PCIe\uff0c\u901f\u5ea6\u4f1a\u6bd4 NVLink \u6162\u3002<\/li>\n
                  • \u5f71\u54cd\uff1a<\/strong> \u5bf9\u63a8\u7406\u901f\u5ea6\uff08Tokens\/s\uff09\u5f71\u54cd\u8f83\u5c0f\uff08\u56e0\u4e3a\u4e3b\u8981\u662f\u8ba1\u7b97\u5bc6\u96c6\uff09\uff0c\u4f46\u5728\u52a0\u8f7d\u6a21\u578b\u548c\u6781\u9ad8\u5e76\u53d1\u4e0b\u4f1a\u6709\u74f6\u9888\u3002<\/li>\n
                  • \u5efa\u8bae\uff1a<\/strong> \u786e\u4fdd\u4e24\u5f20\u5361\u63d2\u5728\u4e3b\u677f\u7684\u4e0d\u540c PCIe \u63d2\u69fd\u4e0a\uff0c\u5c3d\u91cf\u8ba9 CPU \u901a\u9053\u5206\u914d\u5747\u8861\uff08\u5982 x8\/x8 \u6a21\u5f0f\u4f18\u4e8e x16\/x4\uff09\u3002<\/li>\n<\/ul>\n
                    D. \u7a33\u5b9a\u6027\u76d1\u63a7<\/h4>\n
                    \u4f5c\u4e3a\u670d\u52a1\u5668\u957f\u671f\u8fd0\u884c\uff0c\u5fc5\u987b\u76d1\u63a7\uff1a<\/p>\n
                      \n
                    1. \u6e29\u5ea6\uff1a<\/strong> \u867d\u7136\u6539\u4e86\u98ce\u6247\uff0c\u4f46\u957f\u671f\u6ee1\u8f7d\u4ecd\u9700\u5173\u6ce8\u3002\u8bbe\u5b9a\u9608\u503c\uff08\u5982 85\u2103\uff09\u81ea\u52a8\u62a5\u8b66\u6216\u964d\u9891\u3002<\/li>\n<\/ol>\n
                        \n
                      • \u547d\u4ee4\uff1awatch -n 1 nvidia-smi<\/code><\/li>\n<\/ul>\n
                          \n
                        1. ECC \u9519\u8bef\uff1a<\/strong> Tesla \u5361\u901a\u5e38\u6709 ECC \u663e\u5b58\u3002\u5982\u679c\u9891\u7e41\u51fa\u73b0 ECC \u7ea0\u9519\uff0c\u53ef\u80fd\u5bfc\u81f4\u7cfb\u7edf\u4e0d\u7a33\u5b9a\u3002<\/li>\n<\/ol>\n
                            \n
                          • \u68c0\u67e5\uff1anvidia-smi -q | grep ECC<\/code><\/li>\n<\/ul>\n
                              \n
                            1. \u6301\u4e45\u6a21\u5f0f\uff1a<\/strong> \u786e\u4fdd nvidia-smi -pm 1<\/code> \u5df2\u5f00\u542f\uff0c\u9632\u6b62\u9a71\u52a8\u5728\u65e0\u8d1f\u8f7d\u65f6\u4f11\u7720\u5bfc\u81f4\u5524\u9192\u5ef6\u8fdf\u3002<\/li>\n<\/ol>\n
                              4. \u603b\u7ed3\u914d\u7f6e\u5355<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n
                              \u7ec4\u4ef6<\/th>\n\u63a8\u8350\u914d\u7f6e<\/th>\n\u5907\u6ce8<\/th>\n<\/tr>\n<\/thead>\n
                              \u64cd\u4f5c\u7cfb\u7edf<\/strong><\/td>\nUbuntu 22.04 LTS<\/td>\n\u7a33\u5b9a\uff0c\u9a71\u52a8\u652f\u6301\u597d<\/td>\n<\/tr>\n
                              \u9a71\u52a8<\/strong><\/td>\nNVIDIA Driver 535\/550<\/td>\n\u5fc5\u987b\u5f00\u542f Persistence Mode<\/td>\n<\/tr>\n
                              \u63a8\u7406\u5f15\u64ce<\/strong><\/td>\nOllama<\/strong> (\u9996\u9009) \u6216 Text-Gen-WebUI<\/td>\n\u57fa\u4e8e llama.cpp<\/td>\n<\/tr>\n
                              \u6a21\u578b\u683c\u5f0f<\/strong><\/td>\nGGUF<\/strong> (Q4_K_M \u6216 Q5_K_M)<\/td>\n\u5fc5\u987b\u91cf\u5316<\/td>\n<\/tr>\n
                              \u4e3b\u529b\u6a21\u578b<\/strong><\/td>\nQwen2.5-32B-Instruct<\/strong><\/td>\n32G \u663e\u5b58\u7684\u6027\u4ef7\u6bd4\u4e4b\u738b<\/td>\n<\/tr>\n
                              \u5907\u7528\u6a21\u578b<\/strong><\/td>\nLlama-3.1-8B \/ Qwen2.5-7B<\/td>\n\u9ad8\u901f\u54cd\u5e94\u573a\u666f<\/td>\n<\/tr>\n
                              \u4e0a\u4e0b\u6587\u957f\u5ea6<\/strong><\/td>\n16k – 24k<\/td>\n\u5e73\u8861\u901f\u5ea6\u4e0e\u8bb0\u5fc6\u957f\u5ea6<\/td>\n<\/tr>\n
                              \u5e94\u7528\u573a\u666f<\/strong><\/td>\n\u4e2a\u4eba\u52a9\u624b\u3001\u77e5\u8bc6\u5e93\u95ee\u7b54(RAG)\u3001\u4ee3\u7801\u8f85\u52a9\u3001\u6587\u6848\u5199\u4f5c<\/td>\n\u4e0d\u9002\u5408\u5927\u89c4\u6a21\u8bad\u7ec3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
                              \u4e00\u53e5\u8bdd\u5efa\u8bae\uff1a<\/strong>\n\u628a\u4f60\u7684\u53cc T10 \u5f53\u4f5c\u4e00\u4e2a 32GB \u663e\u5b58\u7684\u201c\u91cf\u5316\u6a21\u578b\u4e13\u7528\u63a8\u7406\u673a\u201d<\/strong>\uff0c\u4e3b\u653b Qwen2.5-32B (Q4\/Q5)<\/strong> \u548c Llama-3-8B (Q8)<\/strong>\uff0c\u8fd9\u5c06\u7ed9\u4f60\u5e26\u6765\u8d85\u8d8a\u8bb8\u591a\u6d88\u8d39\u7ea7\u5355\u5361\uff08\u5982 3060 12G, 4060Ti 16G\uff09\u7684\u667a\u80fd\u4f53\u9a8c\u3002<\/p>","protected":false},"excerpt":{"rendered":"
                              \u65e2\u7136\u4f60\u5df2\u7ecf\u89e3\u51b3\u4e86 Tesla T10 \u6700\u68d8\u624b\u7684\u6563\u70ed\u95ee\u9898\uff08\u6539\u88c5\u4e86 2070 \u6da1\u8f6e\u6247\uff09\uff0c\u5e76\u4e14\u8ba1\u5212\u5c06\u8fd9\u4e24\u5f20\u5361\u7ec4\u6210 3 […]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-80","post","type-post","status-publish","format-standard","hentry","category-blue-notes"],"_links":{"self":[{"href":"https:\/\/deepbule.store\/index.php?rest_route=\/wp\/v2\/posts\/80","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/deepbule.store\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/deepbule.store\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/deepbule.store\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/deepbule.store\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=80"}],"version-history":[{"count":1,"href":"https:\/\/deepbule.store\/index.php?rest_route=\/wp\/v2\/posts\/80\/revisions"}],"predecessor-version":[{"id":81,"href":"https:\/\/deepbule.store\/index.php?rest_route=\/wp\/v2\/posts\/80\/revisions\/81"}],"wp:attachment":[{"href":"https:\/\/deepbule.store\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=80"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/deepbule.store\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=80"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/deepbule.store\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=80"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}