{"id":86732,"date":"2026-07-29T07:00:36","date_gmt":"2026-07-28T23:00:36","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/86732.html"},"modified":"2026-07-29T07:00:36","modified_gmt":"2026-07-28T23:00:36","slug":"%e6%9c%ac%e5%9c%b0%e8%b7%91%e5%a4%a7%e6%a8%a1%e5%9e%8b%e5%ae%9e%e6%88%98%ef%bc%88%e4%ba%8c%ef%bc%89%ef%bc%9agguf-%e4%b8%8e%e9%87%8f%e5%8c%96%e7%ad%89%e7%ba%a7%e5%88%b0%e5%ba%95%e6%80%8e%e4%b9%88","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/86732.html","title":{"rendered":"# \u672c\u5730\u8dd1\u5927\u6a21\u578b\u5b9e\u6218\uff08\u4e8c\uff09\uff1aGGUF \u4e0e\u91cf\u5316\u7b49\u7ea7\u5230\u5e95\u600e\u4e48\u9009\uff1f"},"content":{"rendered":"

\u672c\u5730\u8dd1\u5927\u6a21\u578b\u5b9e\u6218（\u4e8c）：GGUF \u4e0e\u91cf\u5316\u7b49\u7ea7\u5230\u5e95\u600e\u4e48\u9009？<\/h2>\n

\u672c\u6587\u662f\u300a\u672c\u5730\u5927\u6a21\u578b\u642d\u5e94\u7528\u5b9e\u6218\u300b\u7cfb\u5217\u7b2c 2 \u7bc7\u3002\u4e0a\u4e00\u7bc7\u8dd1\u901a\u4e86\u7b2c\u4e00\u4e2a\u6a21\u578b，\u4f46\u4f60\u5728 Hugging Face \u4e0b\u8f7d\u9875\u9762\u4e00\u5b9a\u5361\u4f4f\u4e86\u2014\u2014\u540c\u4e00\u4e2a\u6a21\u578b\u6709 20 \u4e2a GGUF \u6587\u4ef6，Q4_K_M\u3001Q5_K_S\u3001Q8_0\u3001IQ4_NL\u2026\u2026\u672c\u7bc7\u89e3\u51b3\u8fd9\u4e2a\u9009\u62e9\u9898\u3002<\/p>\n

\n

GGUF \u662f\u4ec0\u4e48<\/h3>\n

GGUF（GGML Universal Format）\u662f llama.cpp \u751f\u6001\u7684\u6a21\u578b\u6587\u4ef6\u683c\u5f0f，2023 \u5e74 8 \u6708\u7531 Georgi Gerganov \u5f15\u5165，\u66ff\u4ee3\u4e86\u65e9\u671f\u7684 GGML \u683c\u5f0f\u3002\u5b83\u7684\u8bbe\u8ba1\u76ee\u6807\u5f88\u660e\u786e：\u4e00\u4e2a\u81ea\u5305\u542b\u7684\u5355\u6587\u4ef6，\u5305\u542b\u6a21\u578b\u6743\u91cd\u3001tokenizer\u3001\u5143\u6570\u636e，\u89e3\u538b\u5373\u7528\u3002<\/p>\n

\u4e3a\u4ec0\u4e48\u8981\u7edf\u4e00\u683c\u5f0f？\u56e0\u4e3a\u5728\u5927\u6a21\u578b\u7684\u4e16\u754c\u91cc，\u4e0d\u540c\u6846\u67b6（PyTorch\u3001TensorFlow\u3001Safetensors）\u7684\u6743\u91cd\u6587\u4ef6\u4e0d\u80fd\u76f4\u63a5\u4e92\u901a\u3002GGUF \u5145\u5f53\u4e86"\u4ea4\u4ed8\u683c\u5f0f"\u7684\u89d2\u8272\u2014\u2014\u6a21\u578b\u53d1\u5e03\u8005\u8f6c\u4e00\u6b21 GGUF，\u6240\u6709\u4f7f\u7528 llama.cpp \u7684\u5de5\u5177（Ollama\u3001LM Studio\u3001Jan\u3001AnythingLLM）\u90fd\u80fd\u76f4\u63a5\u7528\u3002<\/p>\n

\n

\u91cf\u5316\u5230\u5e95\u5728\u505a\u4ec0\u4e48<\/h3>\n

\u4e00\u4e2a 70 \u4ebf\u53c2\u6570\u7684\u6a21\u578b，\u539f\u59cb\u7cbe\u5ea6（FP16）\u65f6\u6743\u91cd\u5360\u7ea6 14GB\u3002\u5927\u90e8\u5206\u6d88\u8d39\u7ea7\u663e\u5361\u6ca1\u90a3\u4e48\u5927\u663e\u5b58，CPU \u63a8\u7406 14GB \u53c8\u592a\u6162\u3002<\/p>\n

\u91cf\u5316\u89e3\u51b3\u8fd9\u4e2a：\u628a\u6bcf\u4e2a\u6743\u91cd\u4ece 16 \u4f4d\u6d6e\u70b9\u538b\u7f29\u5230\u66f4\u5c11\u7684\u6bd4\u7279\u6570\u3002\u6bd4\u5982 4 \u6bd4\u7279\u91cf\u5316\u540e，\u540c\u6837\u7684\u6a21\u578b\u6743\u91cd\u53ea\u5360\u7ea6 3.5GB，\u4f53\u79ef\u7f29\u5c0f 4 \u500d，\u540c\u65f6\u63a8\u7406\u901f\u5ea6\u5927\u5e45\u63d0\u5347\u3002<\/p>\n

\u4ee3\u4ef7\u662f\u7cbe\u5ea6\u635f\u5931\u3002\u4f46\u5b9e\u8df5\u8bc1\u660e，\u6a21\u578b\u7684\u5197\u4f59\u5ea6\u8fdc\u8d85\u60f3\u8c61\u2014\u20144 \u6bd4\u7279\u91cf\u5316\u7684\u6a21\u578b\u5728\u5f88\u591a\u4efb\u52a1\u4e0a\u7684\u8868\u73b0\u548c\u539f\u7248\u51e0\u4e4e\u65e0\u6cd5\u533a\u5206\u3002\u8fd9\u662f LLM \u91cf\u5316\u548c\u4f20\u7edf\u6570\u503c\u8ba1\u7b97\u91cf\u5316\u7684\u6700\u5927\u533a\u522b：\u4f60\u91cf\u5316\u7684\u662f\u795e\u7ecf\u7f51\u7edc\u6743\u91cd，\u4e0d\u662f\u6c42\u89e3\u65b9\u7a0b\u7ec4\u7684\u7cfb\u6570\u3002<\/p>\n

\n

\u91cf\u5316\u7b49\u7ea7\u547d\u540d\u89c4\u5219<\/h3>\n

llama.cpp \u7684\u91cf\u5316\u547d\u540d\u770b\u8d77\u6765\u50cf\u5bc6\u7801，\u62c6\u5f00\u5c31\u6e05\u695a\u4e86：<\/p>\n

Q4_K_M
\n\u2502 \u2502 \u2502
\n\u2502 \u2502 \u2514\u2500 _S（Small）\/ _M（Medium）\/ _L（Large）：\u540c\u6bd4\u7279\u6570\u5185\u7684\u8d28\u91cf-\u4f53\u79ef\u5e73\u8861
\n\u2502 \u2514\u2500\u2500\u2500 K-quant：\u4f7f\u7528 K-means \u805a\u7c7b\u7684\u91cf\u5316\u65b9\u6cd5，\u6bd4\u7eaf\u7ebf\u6027\u91cf\u5316\u66f4\u597d\u5730\u4fdd\u7559\u91cd\u8981\u6743\u91cd
\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500 \u6bd4\u7279\u6570：4 \u8868\u793a\u5e73\u5747\u7ea6 4 \u6bd4\u7279\u6bcf\u4e2a\u6743\u91cd<\/p>\n

\u51e0\u7c7b\u4e3b\u6d41\u91cf\u5316\u7b49\u7ea7\u7684\u5bf9\u7167：<\/p>\n\n\u91cf\u5316\u7c7b\u578b\u7ea6\u6bcf\u53c2\u6570 bit8B \u6a21\u578b\u7ea6\u5927\u5c0f\u8d28\u91cf\u611f\u77e5\u9002\u7528\u573a\u666f<\/tr>\n\n\n\n\n\n\n\n\n\n
Q4_K_M<\/td>\n~4.6<\/td>\n~4.9 GB<\/td>\n\u6781\u8f7b\u5fae\u4e0b\u964d，\u591a\u6570\u4efb\u52a1\u65e0\u6cd5\u611f\u77e5<\/td>\n\u65e5\u5e38\u4f7f\u7528\u6700\u63a8\u8350<\/td>\n<\/tr>\n
Q4_K_S<\/td>\n~4.3<\/td>\n~4.7 GB<\/td>\n\u7565\u4f4e\u4e8e Q4_K_M<\/td>\n\u663e\u5b58\u7d27\u5f20\u65f6\u66ff\u4ee3<\/td>\n<\/tr>\n
Q5_K_M<\/td>\n~5.5<\/td>\n~5.7 GB<\/td>\n\u6bd4 Q4 \u7565\u6709\u63d0\u5347，\u9700\u4ed4\u7ec6\u5bf9\u7167\u624d\u80fd\u611f\u77e5<\/td>\n\u5bf9\u8d28\u91cf\u8981\u6c42\u9ad8\u3001\u6709\u4f59\u91cf<\/td>\n<\/tr>\n
Q6_K<\/td>\n~6.6<\/td>\n~6.7 GB<\/td>\n\u63a5\u8fd1 FP16<\/td>\n\u6781\u9650\u8d28\u91cf\u8ffd\u6c42<\/td>\n<\/tr>\n
Q8_0<\/td>\n~8.5<\/td>\n~8.5 GB<\/td>\n\u6781\u5176\u63a5\u8fd1 FP16<\/td>\n\u4ee3\u7801\/\u6570\u5b66\u7b49\u7cbe\u5ea6\u654f\u611f\u4efb\u52a1<\/td>\n<\/tr>\n
IQ4_NL<\/td>\n~4.5<\/td>\n~4.7 GB<\/td>\n\u7406\u8bba\u4e0a\u6bd4\u4f20\u7edf Q4 \u7565\u597d<\/td>\n\u8ffd\u6c42\u6700\u4f18\u538b\u7f29<\/td>\n<\/tr>\n
Q2_K<\/td>\n~3.1<\/td>\n~3.5 GB<\/td>\n\u660e\u663e\u4e0b\u964d，\u4f46\u4ecd\u53ef\u7528<\/td>\n\u6781\u9650\u786c\u4ef6（\u5982 8GB \u663e\u5b58\u8dd1 8B）<\/td>\n<\/tr>\n
FP16<\/td>\n16.0<\/td>\n~14 GB<\/td>\n\u65e0\u635f\u5931<\/td>\n\u57fa\u51c6\u5bf9\u7167<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u6ce8\u610f\u4e8b\u9879：<\/p>\n

    \n
  • IQ \u7cfb\u5217（Importance-aware Quantization）\u662f\u8f83\u65b0\u7684\u7c7b\u578b，\u6839\u636e\u6743\u91cd\u91cd\u8981\u6027\u5206\u914d\u5408\u9002\u7684\u6bd4\u7279\u6570，\u6bd4\u4f20\u7edf K-quant \u5728\u540c\u7b49\u4f53\u79ef\u4e0b\u8d28\u91cf\u7565\u597d\u3002\u4f46\u4e0d\u662f\u6240\u6709\u6a21\u578b\u90fd\u6709 IQ \u7248\u672c<\/li>\n
  • Q4_K_M \u662f\u793e\u533a\u7edf\u8ba1\u4e0b\u8f7d\u91cf\u6700\u5927\u7684\u7c7b\u578b，\u7ecf\u8fc7\u4e86\u5927\u89c4\u6a21\u5b9e\u9645\u4f7f\u7528\u9a8c\u8bc1<\/li>\n
  • \u4ece Q4_K_M \u5230 Q5_K_M \u7684\u63d0\u5347\u662f\u53ef\u611f\u77e5\u4f46\u5fae\u5c0f\u7684；\u4ece Q4_K_M \u5230 Q2_K \u7684\u4e0b\u964d\u5219\u6bd4\u8f83\u660e\u663e<\/li>\n<\/ul>\n
    \n

    \u600e\u4e48\u6309\u786c\u4ef6\u9009<\/h3>\n

    \u6838\u5fc3\u601d\u8def：\u5148\u7b97\u6a21\u578b\u5927\u6982\u5360\u591a\u5c11\u5185\u5b58\/\u663e\u5b58，\u518d\u5339\u914d\u786c\u4ef6\u4f59\u91cf\u3002<\/p>\n

    \u4f30\u7b97\u516c\u5f0f（\u7ecf\u9a8c\u53c2\u8003）：<\/p>\n

    \u5360\u7528 \u2248 \u53c2\u6570\u91cf(B) \u00d7 \u6bcf\u53c2\u6570 bit \u6570\u91cf \/ 8 \u00d7 1.2 (KV cache + overhead)<\/p>\n

    \u4ee5 8B \u6a21\u578b Q4_K_M（4.6 bit）\u4e3a\u4f8b：8 \u00d7 4.6 \/ 8 \u00d7 1.2 \u2248 5.5 GB\u3002<\/p>\n

    \u786c\u4ef6\u7684\u7ecf\u9a8c\u5339\u914d：<\/p>\n\n\u663e\u5b58\/\u5185\u5b58\u53ef\u8dd1\u6a21\u578b<\/tr>\n\n\n\n\n\n\n\n
    8 GB<\/td>\n8B Q4_K_M（\u52c9\u5f3a），\u63a8\u8350 3B Q4_K_M \u6216 7B Q2_K<\/td>\n<\/tr>\n
    12 GB<\/td>\n8B Q4_K_M \u7a33\u5b9a，14B Q4_K_M \u53ef\u5c1d\u8bd5<\/td>\n<\/tr>\n
    16 GB<\/td>\n8B \u4efb\u610f\u91cf\u5316，14B Q4_K_M \u7a33\u5b9a，32B Q3 \u53ef\u5c1d\u8bd5<\/td>\n<\/tr>\n
    24 GB<\/td>\n14B \u4efb\u610f\u91cf\u5316，32B Q4_K_M，70B Q2<\/td>\n<\/tr>\n
    32 GB<\/td>\n32B \u4efb\u610f\u91cf\u5316，70B Q4_K_M<\/td>\n<\/tr>\n
    48 GB+<\/td>\n70B \u4efb\u610f\u91cf\u5316，\u767e B \u7ea7 Q3\/Q4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    CPU + \u5927\u5185\u5b58（\u7eaf CPU \u63a8\u7406）：\u4ee5\u4e0a\u6362\u4e3a\u7cfb\u7edf\u603b\u5185\u5b58\u5373\u53ef\u8dd1，\u4f46\u901f\u5ea6\u8fdc\u6162\u4e8e GPU\u3002\u7eaf CPU \u4e0b 8B Q4_K_M \u7ea6 5-10 token\/s，14B \u7ea6 2-5 token\/s\u3002\u8d85\u8fc7 32B \u7684\u6a21\u578b\u7eaf CPU \u63a8\u7406\u57fa\u672c\u4e0d\u53ef\u7528\u4e8e\u4ea4\u4e92\u5f0f\u573a\u666f\u3002<\/p>\n

    \n

    \u9009\u62e9\u5fc3\u6cd5：\u591f\u7528\u524d\u63d0\u4e0b\u9009\u6700\u597d\u7684<\/h3>\n

    \u4e0d\u8981\u4ece"\u6211\u7684\u663e\u5361\u6781\u9650\u80fd\u585e\u591a\u5927\u6a21\u578b"\u51fa\u53d1\u3002\u4ece"\u6211\u5178\u578b\u7684\u4efb\u52a1\u9700\u8981\u591a\u5f3a\u7684\u6a21\u578b"\u51fa\u53d1\u3002<\/p>\n

    \u4e09\u5c42\u51b3\u7b56：<\/p>\n

  • \u8d28\u91cf\u9700\u6c42：\u4ee3\u7801\/\u6570\u5b66\/\u521b\u610f\u5199\u4f5c \u2192 \u4f18\u5148\u9ad8\u8d28\u91cf（Q5 \u4ee5\u4e0a）\u3002\u95f2\u804a\/\u7b80\u5355\u7ffb\u8bd1\/\u6458\u8981 \u2192 Q4 \u8db3\u591f<\/li>\n
  • \u786c\u4ef6\u5929\u82b1\u677f：\u7528\u4e0a\u9762\u7684\u516c\u5f0f\u4f30\u7b97\u5019\u9009\u6a21\u578b + \u91cf\u5316\u7684\u5360\u7528，\u786e\u8ba4\u786c\u4ef6\u88c5\u5f97\u4e0b<\/li>\n
  • \u901f\u5ea6\u5e95\u7ebf：GPU \u63a8\u7406\u6700\u597d >15 token\/s，CPU \u63a8\u7406 >5 token\/s（\u7eaf CPU \u7528 Q4 \u751a\u81f3 Q3 \u6765\u63d0\u901f）<\/li>\n

    \u4e0d\u786e\u5b9a\u65f6，\u4ece Q4_K_M \u5f00\u59cb\u2014\u2014\u5b83\u662f\u8d77\u70b9，\u4e0d\u662f\u7ec8\u70b9\u3002\u8dd1\u4e00\u6bb5\u65f6\u95f4\u540e，\u5982\u679c\u611f\u89c9\u8d28\u91cf\u4e0d\u591f，\u5347\u5230 Q5_K_M \u8bd5\u8bd5\u3002\u5982\u679c\u5360\u7528\u592a\u9ad8，\u964d\u5230 IQ4_NL \u6216 Q4_K_S\u3002<\/p>\n

    \n

    \u5c0f\u7ed3<\/h3>\n

    GGUF \u548c\u91cf\u5316\u7684\u6838\u5fc3\u903b\u8f91：\u7528\u7cbe\u5ea6\u6362\u4f53\u79ef\u548c\u901f\u5ea6\u3002Q4_K_M \u662f\u5b89\u5168\u8d77\u70b9，\u5f80\u4e0a\u8ffd\u6c42\u8d28\u91cf\u3001\u5f80\u4e0b\u8ffd\u6c42\u517c\u5bb9\u6027\u3002\u4e0b\u4e00\u7bc7\u8bb2 llama-server\u2014\u2014\u628a\u672c\u5730\u6a21\u578b\u53d8\u6210 OpenAI \u517c\u5bb9\u7684 HTTP API，\u8ba9\u4f60\u7528 openai \u5e93\u5c31\u80fd\u8c03\u672c\u5730\u6a21\u578b\u3002<\/p>\n

    \n

    \u6807\u7b7e：GGUF\u3001\u91cf\u5316\u3001llama.cpp\u3001\u5927\u6a21\u578b\u3001\u672c\u5730\u90e8\u7f72\u3001LLM<\/p>\n","protected":false},"excerpt":{"rendered":"

    \u672c\u5730\u8dd1\u5927\u6a21\u578b\u5b9e\u6218（\u4e8c）：GGUF \u4e0e\u91cf\u5316\u7b49\u7ea7\u5230\u5e95\u600e\u4e48\u9009？\u672c\u6587\u662f\u300a\u672c\u5730\u5927\u6a21\u578b\u642d\u5e94\u7528\u5b9e\u6218\u300b\u7cfb\u5217\u7b2c 2 \u7bc7\u3002\u4e0a\u4e00\u7bc7\u8dd1\u901a\u4e86\u7b2c\u4e00\u4e2a\u6a21\u578b，\u4f46\u4f60\u5728 Hugging Face \u4e0b\u8f7d\u9875\u9762\u4e00\u5b9a\u5361\u4f4f\u4e86\u2014\u2014\u540c\u4e00\u4e2a\u6a21\u578b\u6709 20 \u4e2a GGUF \u6587\u4ef6，Q4_K_M\u3001Q5_K_S\u3001Q8_0\u3001IQ4_NL\u2026\u2026\u672c\u7bc7\u89e3\u51b3\u8fd9\u4e2a\u9009\u62e9\u9898\u3002GGUF \u662f\u4ec0\u4e48
    \nGGUF（GGML Universal Format）<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[99,347,190],"topic":[],"class_list":["post-86732","post","type-post","status-publish","format-standard","hentry","category-server","tag-java","tag-llama","tag-190"],"yoast_head":"\n# \u672c\u5730\u8dd1\u5927\u6a21\u578b\u5b9e\u6218\uff08\u4e8c\uff09\uff1aGGUF \u4e0e\u91cf\u5316\u7b49\u7ea7\u5230\u5e95\u600e\u4e48\u9009\uff1f - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/86732.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"# \u672c\u5730\u8dd1\u5927\u6a21\u578b\u5b9e\u6218\uff08\u4e8c\uff09\uff1aGGUF \u4e0e\u91cf\u5316\u7b49\u7ea7\u5230\u5e95\u600e\u4e48\u9009\uff1f - 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