\n| \u6ca1\u6709\u72ec\u663e<\/td>\n | llama-b9326-bin-win-cpu-x64.zip<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n **NVIDIA \u7528\u6237\u6ce8\u610f：**\u9664\u4e86\u4e3b\u5305，\u8fd8\u8981\u4e0b\u8f7d cudart-llama-bin-win-cuda-12.4-x64.zip，\u5b83\u5305\u542b CUDA \u8fd0\u884c\u65f6 DLL，\u7f3a\u5931\u4f1a\u5bfc\u81f4\u542f\u52a8\u62a5\u9519\u3002<\/p>\n \u7b2c\u4e8c\u6b65：\u89e3\u538b\u4e0e\u76ee\u5f55\u51c6\u5907<\/h4>\n\u26a0\ufe0f \u94c1\u5f8b：\u8def\u5f84\u4e0d\u80fd\u6709\u4e2d\u6587\u3002 llama.cpp \u5bf9\u4e2d\u6587\u8def\u5f84\u652f\u6301\u4e0d\u4f73，\u89e3\u538b\u5230\u4e2d\u6587\u76ee\u5f55\u4f1a\u62a5\u5404\u79cd\u83ab\u540d\u5176\u5999\u7684\u9519\u8bef\u3002<\/p>\n \u5c06\u538b\u7f29\u5305\u89e3\u538b\u5230\u7eaf\u82f1\u6587\u8def\u5f84，\u4f8b\u5982 D:\\\\llama-cpp \u6216 C:\\\\llama\u3002<\/p>\n CUDA \u7528\u6237：\u628a DLL \u5305\u7684\u5185\u5bb9\u4e5f\u89e3\u538b\u5230\u540c\u4e00\u76ee\u5f55（\u8986\u76d6\u76f8\u540c\u6587\u4ef6\u5373\u53ef）\u3002<\/p>\n \u65b0\u5efa\u4e00\u4e2a models \u5b50\u76ee\u5f55：<\/p>\n D:\\\\llama-cpp\\\\
\n\u251c\u2500\u2500 llama-server.exe \u2190 \u4e3b\u7a0b\u5e8f（\u8fd9\u662f\u6211\u4eec\u8981\u7528\u7684）
\n\u251c\u2500\u2500 llama-cli.exe \u2190 \u547d\u4ee4\u884c\u63a8\u7406\u5de5\u5177
\n\u251c\u2500\u2500 llama-quantize.exe \u2190 \u91cf\u5316\u5de5\u5177
\n\u251c\u2500\u2500 models\\\\ \u2190 \u653e\u6a21\u578b\u6587\u4ef6
\n\u2502 \u251c\u2500\u2500 Qwen3.6-35B-A3B-Q4_K_M.gguf
\n\u2502 \u2514\u2500\u2500 mmproj-Qwen3.6-35B-A3B-f16.gguf
\n\u2514\u2500\u2500 *.dll (CUDA DLLs)<\/p>\n 💡 \u79d1\u666e：llama.cpp \u662f\u4ec0\u4e48？
\nllama.cpp \u662f\u4e00\u4e2a\u7eaf C\/C++ \u5b9e\u73b0\u7684\u5927\u6a21\u578b\u63a8\u7406\u5f15\u64ce，\u7531\u793e\u533a\u5f00\u53d1\u8005 @ggerganov \u521b\u5efa\u3002\u5b83\u4e0d\u4f9d\u8d56 Python\u3001PyTorch \u7b49\u91cd\u578b\u6846\u67b6，\u53ea\u9700\u4e00\u4e2a exe \u5c31\u80fd\u8dd1\u5927\u6a21\u578b\u3002\u5b83\u652f\u6301 GGUF \u683c\u5f0f（\u4e00\u79cd\u9ad8\u6548\u7684\u6a21\u578b\u91cf\u5316\u683c\u5f0f），\u81ea\u5e26 K-Quants \u91cf\u5316\u7b97\u6cd5，\u80fd\u5c06\u6a21\u578b\u4ece FP16 \u538b\u7f29\u5230 2-8 bit，\u540c\u65f6\u5c3d\u91cf\u4fdd\u6301\u7cbe\u5ea6\u3002\u5b83\u8fd8\u5185\u7f6e\u4e86 HTTP \u670d\u52a1\u5668（llama-server），\u63d0\u4f9b\u517c\u5bb9 OpenAI API \u7684\u63a5\u53e3，\u8ba9\u4efb\u4f55\u652f\u6301 OpenAI SDK \u7684\u5de5\u5177\u90fd\u80fd\u63a5\u5165\u3002<\/p>\n \u4e94\u3001\u9636\u6bb5\u4e8c：\u4e0b\u8f7d\u6a21\u578b\u2014\u2014\u9009\u62e9\u5408\u9002\u7684\u91cf\u5316\u7b49\u7ea7<\/h3>\n\u7b2c\u4e09\u6b65：\u7406\u89e3 GGUF \u91cf\u5316<\/h4>\nGGUF \u662f llama.cpp \u56e2\u961f\u5f00\u53d1\u7684\u6a21\u578b\u6587\u4ef6\u683c\u5f0f\u3002\u7b80\u5355\u8bf4，\u5b83\u5c06\u6a21\u578b\u6743\u91cd\u4ece\u539f\u59cb\u7684 FP32\/FP16 \u538b\u7f29\u5230\u66f4\u4f4e\u7684\u7cbe\u5ea6\u3002\u5c31\u597d\u50cf\u628a\u4e00\u5f20\u8d85\u9ad8\u5206\u8fa8\u7387\u7167\u7247\u4ece RAW \u683c\u5f0f\u538b\u7f29\u6210 JPEG\u2014\u2014\u6587\u4ef6\u5c0f\u4e86，\u4f46\u4eba\u773c\u770b\u4e0d\u51fa\u592a\u5927\u5dee\u522b\u3002<\/p>\n \u5728 HuggingFace \u641c\u7d22 Qwen3.6-35B-A3B GGUF，\u63a8\u8350\u4ece bartowski \u6216 unsloth \u7684\u4ed3\u5e93\u4e0b\u8f7d，\u4ed6\u4eec\u662f GGUF \u683c\u5f0f\u7684\u4e3b\u8981\u8d21\u732e\u8005，\u91cf\u5316\u8d28\u91cf\u6709\u4fdd\u969c\u3002<\/p>\n \n\u663e\u5b58\u63a8\u8350\u91cf\u5316\u6587\u4ef6\u5927\u5c0f\u7cfb\u7edf\u5185\u5b58\u63a8\u7406\u901f\u5ea6\u8bf4\u660e<\/tr>\n \n\n| 24GB (4090)<\/td>\n | Q4_K_M<\/td>\n | ~21GB<\/td>\n | 16GB+<\/td>\n | ~130 tok\/s<\/td>\n | \u5b8c\u5168GPU，\u6781\u81f4\u901f\u5ea6<\/td>\n<\/tr>\n | \n| 12-16GB<\/td>\n | IQ4_XS<\/td>\n | ~19GB<\/td>\n | 32GB+<\/td>\n | ~40-60 tok\/s<\/td>\n | \u5206\u5c42\u52a0\u8f7d，\u90e8\u5206\u8d70\u5185\u5b58<\/td>\n<\/tr>\n | \n| 8GB<\/td>\n | Q3_K_M \/ IQ4_NL<\/td>\n | ~16GB<\/td>\n | 32GB+<\/td>\n | ~15-30 tok\/s<\/td>\n | \u5927\u90e8\u5206\u8d70\u5185\u5b58<\/td>\n<\/tr>\n | \n| 6GB<\/td>\n | IQ2_M<\/td>\n | ~11GB<\/td>\n | 16GB+<\/td>\n | ~8-15 tok\/s<\/td>\n | \u51e0\u4e4e\u5168\u8d70\u5185\u5b58，GPU\u4ec5\u8f85\u52a9<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \u91cf\u5316\u7ea7\u522b\u8bf4\u660e：<\/p>\n \n- \n
Q4_K_M<\/p>\n ：4-bit K-quants \u7684\u4e2d\u95f4\u7248\u672c，\u7cbe\u5ea6\u548c\u538b\u7f29\u7387\u7684\u6700\u4f73\u5e73\u8861\u70b9，\u63a8\u8350\u663e\u5b58\u5145\u8db3\u65f6\u4f7f\u7528<\/p>\n<\/li>\n - \n
Q3_K_M<\/p>\n ：3-bit K-quants，\u727a\u7272\u5c11\u91cf\u7cbe\u5ea6\u6362\u53d6\u66f4\u5c0f\u4f53\u79ef<\/p>\n<\/li>\n - \n
IQ2_M<\/p>\n ：2-bit \u5de5\u4e1a\u91cf\u5316，\u538b\u7f29\u7387\u6700\u9ad8\u4f46\u7cbe\u5ea6\u635f\u5931\u6700\u5927，\u662f 6G \u663e\u5b58\u7684"\u6551\u547d\u7a3b\u8349"<\/p>\n<\/li>\n<\/ul>\n **\u8fd8\u8981\u4e0b\u8f7d\u8fd9\u4e2a\u6587\u4ef6：**\u60f3\u8981\u591a\u6a21\u6001\u770b\u56fe\u529f\u80fd，\u8fd8\u5fc5\u987b\u4e0b\u8f7d\u5bf9\u5e94\u7684 mmproj \u6295\u5f71\u6587\u4ef6（\u7ea6 1.3GB）\u3002\u8fd9\u4e2a\u6587\u4ef6\u8d1f\u8d23\u5c06\u89c6\u89c9\u7f16\u7801\u5668\u7684\u8f93\u51fa"\u6295\u5f71"\u5230\u8bed\u8a00\u6a21\u578b\u7684\u5d4c\u5165\u7a7a\u95f4，\u8ba9 LLM \u80fd"\u770b\u61c2"\u56fe\u7247\u3002\u6ca1\u6709\u5b83，\u4e0a\u4f20\u6309\u94ae\u4f1a\u7070\u8272\u4e0d\u53ef\u70b9\u51fb\u3002<\/p>\n \u5168\u90e8\u653e\u8fdb models\\\\ \u76ee\u5f55\u3002<\/p>\n 💡 \u4e3a\u4f55\u91cf\u5316\u7248\u672c\u7684\u6a21\u578b\u6587\u4ef6\u6bd4\u539f\u59cb\u53c2\u6570\u5c0f\u8fd9\u4e48\u591a？
\n\u539f\u59cb FP16 \u7cbe\u5ea6：35B \u00d7 2 bytes = 70GB
\nQ4_K_M \u91cf\u5316\u540e：35B \u00d7 0.5 bytes \u2248 17.5GB（\u52a0\u4e0a overhead \u7ea6 21GB）
\nIQ2_M \u91cf\u5316\u540e：35B \u00d7 0.25 bytes \u2248 8.75GB（\u52a0\u4e0a overhead \u7ea6 11GB）
\n\u8fd9\u5c31\u662f\u91cf\u5316\u7684\u9b54\u529b\u2014\u2014\u7528 15%-30% \u7684\u7cbe\u5ea6\u635f\u5931，\u6362\u6765 4-8 \u500d\u7684\u663e\u5b58\u8282\u7701\u3002<\/p>\n \u516d\u3001\u9636\u6bb5\u4e09：\u542f\u52a8\u6a21\u578b\u2014\u2014\u8ba9\u5927\u6a21\u578b\u8dd1\u8d77\u6765<\/h3>\n\u7b2c\u56db\u6b65：\u4e00\u6761\u547d\u4ee4\u542f\u52a8<\/h4>\n\u5728 D:\\\\llama-cpp\\\\ \u76ee\u5f55\u6253\u5f00 PowerShell（Shift + \u53f3\u952e\u7a7a\u767d\u5904 \u2192 \u5728\u6b64\u5904\u6253\u5f00 PowerShell）\u3002<\/p>\n \u7eaf\u6587\u672c\u5bf9\u8bdd（\u4e0d\u9700\u8981\u770b\u56fe）：<\/p>\n .\\\\llama-server.exe -m \u201cmodels\\\\Qwen3.6-35B-A3B-Q4_K_M.gguf\u201d -ngl 999 -c 32768 -n 8192 –jinja –port 8080<\/p>\n \u591a\u6a21\u6001（\u652f\u6301\u770b\u56fe）：<\/p>\n .\\\\llama-server.exe -m \u201cmodels\\\\Qwen3.6-35B-A3B-Q4_K_M.gguf\u201d –mmproj \u201cmodels\\\\mmproj-Qwen3.6-35B-A3B-f16.gguf\u201d -ngl 999 -c 32768 -n 8192 –jinja –port 8080<\/p>\n 6G \u663e\u5b58\u7528\u6237（\u7528 IQ2_M，\u7f29\u5c0f context）：<\/p>\n .\\\\llama-server.exe -m \u201cmodels\\\\Qwen3.6-35B-A3B-IQ2_M.gguf\u201d –mmproj \u201cmodels\\\\mmproj-Qwen3.6-35B-A3B-f16.gguf\u201d -ngl 999 -c 8192 -n 4096 –jinja –port 8080<\/p>\n \u53c2\u6570\u8be6\u89e3：<\/p>\n \n- \n
-m<\/p>\n ：\u6a21\u578b\u6587\u4ef6\u8def\u5f84<\/p>\n<\/li>\n - \n
–mmproj<\/p>\n ：\u591a\u6a21\u6001\u6295\u5f71\u6587\u4ef6\u8def\u5f84\u3002\u4e0d\u52a0\u5c31\u4e0d\u80fd\u770b\u56fe<\/p>\n<\/li>\n - \n
-ngl 999<\/p>\n ：\u5c3d\u91cf\u628a\u6a21\u578b\u5c42\u5378\u8f7d\u5230 GPU \u663e\u5b58\u3002999 \u662f"\u80fd\u653e\u5c31\u653e"，\u653e\u4e0d\u4e0b\u7684\u81ea\u52a8\u8d70\u7cfb\u7edf\u5185\u5b58<\/p>\n<\/li>\n - \n
-c<\/p>\n ：\u4e0a\u4e0b\u6587\u957f\u5ea6（context size）\u30028192 \u2248 6000 \u5b57\u4e2d\u6587\u3002\u663e\u5b58\u5c0f\u5c31\u8bbe\u5c0f\u4e00\u70b9<\/p>\n<\/li>\n - \n
-n<\/p>\n ：\u6700\u5927\u751f\u6210\u957f\u5ea6（max tokens）\u30024096 \u2248 3000 \u5b57\u4e2d\u6587<\/p>\n<\/li>\n - \n
–jinja<\/p>\n ：Qwen3.6 \u5fc5\u987b\u52a0\u8fd9\u4e2a\u53c2\u6570\u3002\u5b83\u542f\u7528 Jinja2 \u6a21\u677f\u5f15\u64ce\u6765\u6e32\u67d3\u804a\u5929\u6a21\u677f\u3002\u4e0d\u52a0\u4f1a\u51fa\u73b0\u56de\u590d\u5f02\u5e38\u3001\u683c\u5f0f\u9519\u4e71\u3001\u65e0\u9650\u91cd\u590d\u7b49\u95ee\u9898<\/p>\n<\/li>\n - \n
–port<\/p>\n ：HTTP \u670d\u52a1\u7aef\u53e3，\u9ed8\u8ba4 8080<\/p>\n<\/li>\n<\/ul>\n \u770b\u5230\u8fd9\u884c\u8f93\u51fa\u5c31\u6210\u529f\u4e86：<\/p>\n main: server is listening on http:\/\/127.0.0.1:8080<\/p>\n \u6d4f\u89c8\u5668\u6253\u5f00 http:\/\/localhost:8080\u3002\u4f60\u5c31\u80fd\u770b\u5230\u4e00\u4e2a\u5b8c\u6574\u7684\u804a\u5929\u754c\u9762\u4e86\u3002<\/p>\n \u7b2c\u4e94\u6b65：\u4e00\u952e\u542f\u52a8\u811a\u672c<\/h4>\n\u6bcf\u6b21\u6572\u547d\u4ee4\u592a\u70e6\u3002\u65b0\u5efa\u4e00\u4e2a \u542f\u52a8\u6a21\u578b.cmd \u6587\u4ef6，\u7c98\u8d34\u4ee5\u4e0b\u5185\u5bb9：<\/p>\n @echo off
\nchcp 65001 >nul
\ncd \/d "%~dp0"
\necho =============================================
\necho Qwen3.6-35B-A3B \u672c\u5730\u5927\u6a21\u578b\u542f\u52a8\u5668
\necho =============================================
\necho.
\necho [1] Q4_K_M（24G \u663e\u5b58\u63a8\u8350，\u9ad8\u901f）
\necho [2] IQ4_NL（8-12G \u663e\u5b58，\u5747\u8861）
\necho [3] IQ2_M（6G \u663e\u5b58，\u7701\u663e\u5b58\u6a21\u5f0f）
\necho [4] \u81ea\u5b9a\u4e49\u6a21\u578b\u6587\u4ef6
\necho.
\nset \/p choice=\u8bf7\u8f93\u5165\u6570\u5b57 [1-4]：
\nif "%choice%"=="1" set "MODEL=Qwen3.6-35B-A3B-Q4_K_M.gguf"& set "CTX=-c 32768 -n 8192"
\nif "%choice%"=="2" set "MODEL=Qwen3.6-35B-A3B-IQ4_NL.gguf"& set "CTX=-c 32768 -n 8192"
\nif "%choice%"=="3" set "MODEL=Qwen3.6-35B-A3B-IQ2_M.gguf"& set "CTX=-c 8192 -n 4096"
\n.\\\\llama-server.exe -m "models\\\\%MODEL%" -ngl 999 %CTX% –jinja –host 127.0.0.1 –port 8080
\npause<\/p>\n \u653e\u5728 D:\\\\llama-cpp\\\\ \u76ee\u5f55，\u53cc\u51fb\u8fd0\u884c\u5373\u53ef\u3002<\/p>\n \u4e03\u3001\u9636\u6bb5\u56db：\u63a5\u5165 Hermes Agent\u2014\u2014\u4f60\u7684\u672c\u5730 AI \u52a9\u624b<\/h3>\n\u7b2c\u516d\u6b65：\u5b89\u88c5 Hermes Agent<\/h4>\nHermes Agent \u662f\u4e00\u4e2a\u5f00\u6e90\u7684 AI Agent \u6846\u67b6，\u652f\u6301\u672c\u5730\u90e8\u7f72\u3002\u5b83\u80fd\u8ba9\u5927\u6a21\u578b\u81ea\u52a8\u89c4\u5212\u4efb\u52a1\u3001\u8c03\u7528\u5de5\u5177\u3001\u6267\u884c\u4ee3\u7801\u3002<\/p>\n pipx install hermes-agent<\/p>\n 💡 pipx \u662f\u4ec0\u4e48？
\npipx \u662f\u4e00\u4e2a\u4e13\u95e8\u7528\u4e8e\u5b89\u88c5 Python \u547d\u4ee4\u884c\u5de5\u5177\u7684\u5305\u7ba1\u7406\u5668\u3002\u5b83\u4f1a\u4e3a\u6bcf\u4e2a\u5de5\u5177\u521b\u5efa\u72ec\u7acb\u7684\u865a\u62df\u73af\u5883，\u907f\u514d\u4f9d\u8d56\u51b2\u7a81\u3002\u5982\u679c\u4f60\u8fd8\u6ca1\u5b89\u88c5 pipx，\u5148\u8fd0\u884c：python -m pip install pipx<\/p>\n \u7b2c\u4e03\u6b65：\u914d\u7f6e\u8fde\u63a5\u672c\u5730\u6a21\u578b<\/h4>\nhermes model<\/p>\n \u9009\u62e9 Custom endpoint，\u7136\u540e\u586b\u5199：<\/p>\n \n- \n
Base URL：http:\/\/127.0.0.1:8080\/v1<\/p>\n<\/li>\n - \n
API Key：<\/p>\n \u4efb\u610f\u503c\u6216\u7559\u7a7a<\/p>\n<\/li>\n - \n
Model：<\/p>\n \u7559\u7a7a\u5373\u53ef<\/p>\n<\/li>\n<\/ul>\n \u9a8c\u8bc1\u914d\u7f6e：\u5728\u7ec8\u7aef\u8f93\u5165 hermes，\u7136\u540e\u53d1\u4e00\u6761\u6d88\u606f\u3002\u5982\u679c Agent \u6b63\u5e38\u56de\u590d，\u540c\u65f6 llama-server \u7a97\u53e3\u6709\u8bf7\u6c42\u65e5\u5fd7，\u5c31\u8bf4\u660e\u5168\u90e8\u641e\u5b9a\u3002<\/p>\n ![\"\"](\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260826030916-6a8e58dc53088.png\") <\/p>\n
\u7b2c\u516b\u6b65：Hermes Agent \u80fd\u505a\u4ec0\u4e48？<\/h4>\n\u63a5\u5165\u540e，\u4f60\u7684\u672c\u5730\u6a21\u578b\u4e0d\u518d\u53ea\u662f"\u804a\u5929\u673a\u5668\u4eba"，\u800c\u662f\u771f\u6b63\u80fd\u5e72\u6d3b\u7684 AI \u52a9\u624b：<\/p>\n \n- \n
\u81ea\u52a8\u6267\u884c\u4efb\u52a1：<\/p>\n \u201c\u5e2e\u6211\u5199\u4e00\u4e2a Python \u811a\u672c，\u8bfb\u53d6\u5f53\u524d\u76ee\u5f55\u4e0b\u6240\u6709 CSV \u6587\u4ef6\u5e76\u5408\u5e76\u201d<\/p>\n<\/li>\n - \n
\u8c03\u7528\u5de5\u5177：<\/p>\n \u5b83\u53ef\u4ee5\u641c\u7d22\u6587\u4ef6\u3001\u8fd0\u884c\u547d\u4ee4\u3001\u64cd\u4f5c API<\/p>\n<\/li>\n - \n
\u81ea\u4e3b\u89c4\u5212：<\/p>\n \u590d\u6742\u4efb\u52a1\u53ef\u62c6\u89e3\u4e3a\u591a\u4e2a\u6b65\u9aa4\u9010\u6b65\u6267\u884c<\/p>\n<\/li>\n - \n
\u4ee3\u7801\u751f\u6210：<\/p>\n \u751f\u6210\u4ee3\u7801\u5e76\u81ea\u52a8\u8fd0\u884c\u8c03\u8bd5<\/p>\n<\/li>\n - \n
\u56fe\u7247\u5206\u6790：<\/p>\n \u4e0a\u4f20\u622a\u56fe\u8ba9\u5b83\u5206\u6790\u95ee\u9898\u3001\u63d0\u53d6\u6587\u5b57<\/p>\n<\/li>\n<\/ul>\n \u516b\u3001\u62d3\u5c55\u5e94\u7528：\u4f60\u7684\u7535\u8111 = AI \u57fa\u7840\u8bbe\u65bd<\/h3>\n\u8dd1\u8d77\u6765\u4e4b\u540e，\u4f60\u7684\u7535\u8111\u5c31\u53d8\u6210\u4e86\u4e00\u53f0\u5b8c\u6574\u7684 AI \u670d\u52a1\u5668，\u8fdc\u8d85"\u804a\u5929"\u7684\u8303\u7574：<\/p>\n 8.1 \u5f53 OpenAI API \u7684\u5e73\u66ff<\/h4>\n\u4efb\u4f55\u652f\u6301 OpenAI SDK \u7684\u5de5\u5177，\u53ea\u8981\u628a base_url \u6539\u6210 http:\/\/localhost:8080\/v1，\u5c31\u80fd\u76f4\u63a5\u4f7f\u7528\u672c\u5730\u6a21\u578b\u3002\u4e3e\u4f8b：<\/p>\n from openai import OpenAI
\nclient = OpenAI(
\nbase_url="http:\/\/localhost:8080\/v1",
\napi_key="not-needed"
\n)
\nresponse = client.chat.completions.create(
\nmodel="not-needed", # llama.cpp \u4f1a\u81ea\u52a8\u4f7f\u7528\u5df2\u52a0\u8f7d\u7684\u6a21\u578b
\nmessages=[
\n{"role": "system", "content": "\u4f60\u662f\u4e00\u4e2aAI\u7f16\u7a0b\u52a9\u624b"},
\n{"role": "user", "content": "\u7528Python\u5199\u4e00\u4e2a\u5192\u6ce1\u6392\u5e8f"}
\n],
\nmax_tokens=2048,
\ntemperature=0.7
\n)
\nprint(response.choices[0].message.content)<\/p>\n 8.2 \u63a5\u5165\u672c\u5730\u77e5\u8bc6\u5e93<\/h4>\n\u7ed3\u5408 LangChain \u6216 LlamaIndex，\u5582\u5165\u4f60\u7684\u79c1\u6709\u6587\u6863，\u6784\u5efa\u5b8c\u5168\u672c\u5730\u8fd0\u884c\u7684 RAG \u7cfb\u7edf：<\/p>\n pip install langchain langchain-community chromadb
\n# \u793a\u4f8b：\u7528\u672c\u5730\u6a21\u578b\u505a\u6587\u6863\u95ee\u7b54
\nfrom langchain_community.llms import LlamaCpp
\nfrom langchain.chains import RetrievalQA
\nfrom langchain_community.vectorstores import Chroma
\n# … \u4f60\u7684\u6587\u6863\u5168\u90e8\u672c\u5730\u5904\u7406，\u6570\u636e\u4e0d\u51fa\u672c\u673a<\/p>\n 8.3 \u4f5c\u4e3a IDE \u7684 AI \u63d2\u4ef6\u540e\u7aef<\/h4>\n\u5728 Continue.dev \u6216 Tabby \u7b49\u4ee3\u7801\u8865\u5168\u5de5\u5177\u4e2d，\u5c06 API \u7aef\u70b9\u6307\u5411\u672c\u673a，\u8ba9 AI \u8f85\u52a9\u7f16\u7a0b：<\/p>\n \n- Continue.dev \u914d\u7f6e "apiBase": "http:\/\/localhost:8080"<\/li>\n
- \u4ee3\u7801\u5ba1\u67e5\u3001\u91cd\u6784\u5efa\u8bae\u3001\u6d4b\u8bd5\u751f\u6210\u2014\u2014\u5168\u90e8\u672c\u5730\u5b8c\u6210<\/li>\n<\/ul>\n
\u4e5d\u3001\u5e38\u89c1\u5751\u4e0e\u6392\u67e5\u6307\u5357<\/h3>\n\n\u75c7\u72b6\u539f\u56e0\u89e3\u51b3\u65b9\u6848<\/tr>\n \n\n| \u542f\u52a8\u62a5\u9519 file not found<\/td>\n | \u8def\u5f84\u6709\u4e2d\u6587\u6216\u6a21\u578b\u6587\u4ef6\u540d\u4e0d\u5bf9<\/td>\n | \u68c0\u67e5\u8def\u5f84\u7eaf\u82f1\u6587，\u786e\u8ba4\u6587\u4ef6\u786e\u5b9e\u5728 models \u76ee\u5f55\u4e0b<\/td>\n<\/tr>\n | \n| error loading model<\/td>\n | GGUF \u6587\u4ef6\u635f\u574f\u6216\u672a\u4e0b\u8f7d\u5b8c\u6574<\/td>\n | \u91cd\u65b0\u4e0b\u8f7d，\u68c0\u67e5\u6587\u4ef6\u5927\u5c0f\u662f\u5426\u4e0e HuggingFace \u6807\u6ce8\u4e00\u81f4<\/td>\n<\/tr>\n | \n| \u56de\u590d\u5f02\u5e38\u3001\u65e0\u9650\u91cd\u590d<\/td>\n | \u542f\u52a8\u65f6\u6ca1\u52a0 –jinja<\/td>\n | \u52a0\u4e0a –jinja \u53c2\u6570\u91cd\u542f<\/td>\n<\/tr>\n | \n| \u4e0a\u4f20\u56fe\u7247\u6309\u94ae\u7070\u8272<\/td>\n | \u6ca1\u4e0b\u8f7d mmproj \u6587\u4ef6<\/td>\n | \u4e0b\u8f7d mmproj \u6587\u4ef6，\u542f\u52a8\u65f6\u52a0 –mmproj \u53c2\u6570<\/td>\n<\/tr>\n | \n| missing DLL \u9519\u8bef<\/td>\n | CUDA DLL \u7f3a\u5931<\/td>\n | \u4e0b\u8f7d cudart \u5305，DLL \u653e\u5230\u540c\u4e00\u76ee\u5f55<\/td>\n<\/tr>\n | \n| \u663e\u5b58\u7206\u4e86(OOM)<\/td>\n | Context \u592a\u5927\u6216\u91cf\u5316\u7b49\u7ea7\u592a\u9ad8<\/td>\n | \u51cf\u5c0f -c \u6216\u6362\u66f4\u4f4e\u7684\u91cf\u5316（Q3\u2192IQ2）<\/td>\n<\/tr>\n | \n| \u6a21\u578b\u6587\u4ef6\u53ea\u6709\u51e0\u5341KB<\/td>\n | HuggingFace \u4e0b\u8f7d\u53d7\u9650<\/td>\n | \u7528 curl -I URL \u9a8c\u8bc1\u94fe\u63a5，\u6216\u6362\u955c\u50cf\u6e90<\/td>\n<\/tr>\n | \n| \u901f\u5ea6\u6781\u6162（< 2 tok\/s）<\/td>\n | \u6ca1\u6709 GPU \u52a0\u901f\u6216 -ngl \u592a\u5c0f<\/td>\n | \u786e\u8ba4 -ngl 999 \u53c2\u6570\u5f00\u542f，\u68c0\u67e5\u662f\u5426\u4f7f\u7528 CUDA \u7248\u672c<\/td>\n<\/tr>\n | \n| Hermes Agent \u8fde\u4e0d\u4e0a<\/td>\n | Base URL \u914d\u7f6e\u9519\u8bef<\/td>\n | \u786e\u8ba4 llama-server \u5df2\u542f\u52a8\u4e14\u7aef\u53e3\u6b63\u786e<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\u5341\u3001\u6027\u80fd\u8c03\u4f18：\u8ba9\u4f60\u7684\u6a21\u578b\u8dd1\u5f97\u66f4\u5feb<\/h3>\n10.1 \u5173\u952e\u53c2\u6570\u8c03\u4f18\u5efa\u8bae<\/h4>\n\n- \n
-ngl \u8c03\u4f18：<\/p>\n \u5bf9\u4e8e 6G \u663e\u5b58，-ngl 20 \u5230 -ngl 30 \u53ef\u80fd\u6bd4 -ngl 999 \u66f4\u5feb，\u56e0\u4e3a\u51cf\u5c11\u4e86\u663e\u5b58-\u5185\u5b58\u4e4b\u95f4\u7684\u9891\u7e41\u6570\u636e\u4ea4\u6362\u3002\u5efa\u8bae\u4ece -ngl 999 \u5f00\u59cb，\u7136\u540e\u9010\u6b65\u8c03\u4f4e，\u627e\u5230\u6700\u4f73\u541e\u5410\u91cf\u70b9\u3002<\/p>\n<\/li>\n - \n
Thread \u6570：<\/p>\n \u52a0 -t 6 \u5230 -t 8 \u6307\u5b9a CPU \u7ebf\u7a0b\u6570，\u5145\u5206\u53d1\u6325\u591a\u6838\u6027\u80fd\u3002<\/p>\n<\/li>\n - \n
Batch size：-ub 1024<\/p>\n \u53ef\u4ee5\u5145\u5206\u5229\u7528 GPU \u5e76\u884c\u8ba1\u7b97\u80fd\u529b\u3002<\/p>\n<\/li>\n - \n
Flash Attention：<\/p>\n \u52a0 –flash-attn \u53ef\u4ee5\u663e\u8457\u964d\u4f4e\u663e\u5b58\u5360\u7528，\u7279\u522b\u662f\u957f\u4e0a\u4e0b\u6587\u573a\u666f\u3002<\/p>\n<\/li>\n<\/ul>\n \u4f18\u5316\u7248\u542f\u52a8\u547d\u4ee4：<\/p>\n .\\\\llama-server.exe -m "models\\\\Qwen3.6-35B-A3B-IQ2_M.gguf" –mmproj "models\\\\mmproj-Qwen3.6-35B-A3B-f16.gguf" -ngl 28 -c 8192 -n 4096 -t 8 -ub 1024 –flash-attn –jinja –port 8080<\/p>\n 10.2 \u4e0d\u540c\u914d\u7f6e\u7684\u9884\u671f\u6027\u80fd<\/h4>\n\n\u914d\u7f6e\u7ec4\u5408\u91cf\u5316\u63a8\u7406\u901f\u5ea6\u9996 token \u5ef6\u8fdf\u4f53\u9a8c\u8bc4\u5206<\/tr>\n \n\n| RTX 4090 + 64GB \u5185\u5b58<\/td>\n | Q4_K_M<\/td>\n | ~130 tok\/s<\/td>\n | < 0.5s<\/td>\n | \u2b50\u2b50\u2b50\u2b50\u2b50<\/td>\n<\/tr>\n | \n| RTX 3060 12GB + 32GB<\/td>\n | IQ4_XS<\/td>\n | ~40-60 tok\/s<\/td>\n | ~1s<\/td>\n | \u2b50\u2b50\u2b50\u2b50<\/td>\n<\/tr>\n | \n| RTX 2060 6GB + 32GB<\/td>\n | IQ2_M<\/td>\n | ~8-15 tok\/s<\/td>\n | ~2-3s<\/td>\n | \u2b50\u2b50\u2b50<\/td>\n<\/tr>\n | \n| \u7eaf CPU (i7-13700 + 32GB)<\/td>\n | IQ2_M<\/td>\n | ~1-3 tok\/s<\/td>\n | ~5-10s<\/td>\n | \u2b50\u2b50<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n **💡 \u4f53\u9a8c\u5efa\u8bae：**\u5982\u679c\u80fd\u8fbe\u5230 10 tok\/s \u4ee5\u4e0a，\u666e\u901a\u5bf9\u8bdd\u5df2\u7ecf\u8db3\u591f\u6d41\u7545\u30026-8 tok\/s \u53ef\u4ee5\u63a5\u53d7\u4f46\u7a0d\u6709\u7b49\u5f85\u611f\u3002\u4f4e\u4e8e 5 tok\/s \u66f4\u9002\u5408\u505a\u6279\u91cf\u5904\u7406\u800c\u975e\u5b9e\u65f6\u5bf9\u8bdd\u3002<\/p>\n \u5341\u4e00\u3001MoE \u67b6\u6784\u7684\u6df1\u5c42\u7406\u89e3<\/h3>\n\u6700\u540e，\u8ba9\u6211\u4eec\u6df1\u5165\u7406\u89e3\u4e00\u4e0b MoE \u5230\u5e95\u662f\u600e\u4e48\u56de\u4e8b\u3002\u6bd5\u7adf，\u4f60\u6b63\u5728\u4f7f\u7528\u7684\u8fd9\u4e2a\u6a21\u578b，\u5c31\u662f\u9760\u8fd9\u79cd\u67b6\u6784\u624d\u5f97\u4ee5\u5728 6G \u663e\u5b58\u4e0a\u8fd0\u884c\u7684\u3002<\/p>\n 11.1 MoE \u7684\u5de5\u4f5c\u6d41\u7a0b<\/h4>\n\u6bcf\u4e2a MoE \u5c42\u5305\u542b\u4e09\u90e8\u5206：<\/p>\n - \n
\u5171\u4eab\u4e13\u5bb6（Shared Expert）：<\/p>\n \u6240\u6709 token \u90fd\u5fc5\u987b\u7ecf\u8fc7，\u5904\u7406\u901a\u7528\u77e5\u8bc6<\/p>\n<\/li>\n - \n
\u8def\u7531\u4e13\u5bb6（Routed Experts）：<\/p>\n 256 \u4e2a\u4e13\u5bb6，\u5404\u6709\u4e13\u957f<\/p>\n<\/li>\n - \n
\u8def\u7531\u5668（Router）：<\/p>\n \u4e00\u4e2a\u8f7b\u91cf\u7ea7\u7f51\u7edc，\u51b3\u5b9a\u6bcf\u4e2a token \u5e94\u8be5\u7531\u54ea\u4e9b\u4e13\u5bb6\u5904\u7406<\/p>\n<\/li>\n \u5f53\u4e00\u4e2a token \u8fdb\u5165 MoE \u5c42：<\/p>\n \n- \u8def\u7531\u5668\u7ed9 256 \u4e2a\u4e13\u5bb6\u6253\u5206<\/li>\n
- \u9009\u62e9\u5f97\u5206\u6700\u9ad8\u7684 9 \u4e2a\u4e13\u5bb6（top-9 routing）<\/li>\n
- \u53ea\u6709\u8fd9 9 \u4e2a\u4e13\u5bb6 + 1 \u4e2a\u5171\u4eab\u4e13\u5bb6\u53c2\u4e0e\u8ba1\u7b97<\/li>\n
- \u8f93\u51fa\u52a0\u6743\u5408\u5e76<\/li>\n<\/ul>\n
\u8fd9\u5c31\u662f"35B \u603b\u53c2，3B \u6fc0\u6d3b"\u7684\u6765\u6e90：256 \u4e2a\u4e13\u5bb6\u4e2d\u53ea\u6fc0\u6d3b 9 \u4e2a，\u52a0\u4e0a\u5171\u4eab\u4e13\u5bb6\u7684\u53c2\u6570，\u5b9e\u9645\u6bcf token \u53ea\u8dd1\u7ea6 3B \u53c2\u6570\u3002<\/p>\n 11.2 MoE \u7684\u8d1f\u8f7d\u5747\u8861<\/h4>\nMoE \u9762\u4e34\u7684\u4e00\u4e2a\u6838\u5fc3\u6311\u6218\u662f\u8d1f\u8f7d\u5747\u8861：\u5982\u679c\u8def\u7531\u5668\u603b\u662f\u6d3e\u4efb\u52a1\u7ed9\u540c\u4e00\u4e2a\u4e13\u5bb6，\u5176\u4ed6\u4e13\u5bb6\u5c31"\u997f\u6b7b"\u4e86\u3002\u8fd9\u4f1a\u5bfc\u81f4\u6a21\u578b\u90e8\u5206\u53c2\u6570\u4ece\u672a\u88ab\u8bad\u7ec3，\u635f\u5bb3\u5bb9\u91cf\u3002<\/p>\n Qwen3.6 \u7684\u89e3\u51b3\u65b9\u6848\u5305\u62ec：<\/p>\n \n- \n
\u8f85\u52a9\u635f\u5931（Auxiliary Loss）：<\/p>\n \u5728\u8bad\u7ec3\u65f6\u60e9\u7f5a\u4e0d\u5747\u8861\u7684\u8def\u7531\u5206\u914d<\/p>\n<\/li>\n - \n
\u4e13\u5bb6\u5bb9\u91cf\u9650\u5236：<\/p>\n \u6bcf\u4e2a\u4e13\u5bb6\u7684 token \u5904\u7406\u6570\u6709\u4e0a\u9650<\/p>\n<\/li>\n - \n
\u8def\u7531\u5668\u6b63\u5219\u5316：<\/p>\n \u9f13\u52b1\u66f4\u5747\u5300\u7684\u4e13\u5bb6\u9009\u62e9<\/p>\n<\/li>\n<\/ul>\n \u8fd9\u4e5f\u662f\u4e3a\u4ec0\u4e48 MoE \u6a21\u578b\u5728\u63a8\u7406\u65f6\u867d\u7136\u6548\u7387\u6781\u9ad8，\u4f46\u8bad\u7ec3\u65f6\u9700\u8981\u66f4\u591a\u6280\u5de7\u3002\u597d\u5728\u2014\u2014\u6211\u4eec\u53ea\u7528\u63a8\u7406，\u4e0d\u7528\u8bad\u7ec3\u3002<\/p>\n 11.3 MoE \u4e0e\u91cf\u5316：\u53cc\u91cd\u538b\u7f29\u7684\u827a\u672f<\/h4>\nQwen3.6-35B-A3B \u80fd\u5728 6G \u663e\u5b58\u4e0a\u8fd0\u884c，\u5176\u5b9e\u7528\u5230\u4e86\u4e24\u5c42\u538b\u7f29：<\/p>\n - \n
MoE \u5c42<\/p>\n ：\u63a8\u7406\u65f6\u53ea\u6fc0\u6d3b ~9% \u7684\u53c2\u6570（35B \u2192 3B）<\/p>\n<\/li>\n - \n
\u91cf\u5316<\/p>\n ：\u518d\u5c06\u6bcf\u4e2a\u53c2\u6570\u4ece 16-bit \u538b\u7f29\u5230 2-bit（3B \u00d7 2 bytes \u2192 3B \u00d7 0.25 bytes = 0.75GB）<\/p>\n<\/li>\n \u5b9e\u9645\u663e\u5b58\u5360\u7528\u8fd8\u5305\u62ec KV Cache（\u7ea6 2-4GB）\u3001\u4e2d\u95f4\u6fc0\u6d3b\u503c\u3001mmproj \u7b49 overhead，\u6240\u4ee5\u6700\u7ec8 6G \u663e\u5b58\u521a\u597d\u80fd\u8dd1\u8d77\u6765\u3002\u5982\u679c\u4f60\u4ed4\u7ec6\u7b97\u5c31\u4f1a\u53d1\u73b0：\u4e0d\u662f MoE \u6a21\u578b\u592a\u5c0f，\u800c\u662f\u538b\u7f29\u6280\u672f\u592a\u5f3a\u3002<\/p>\n \u5341\u4e8c\u3001\u672c\u5730 AI \u65f6\u4ee3\u7684\u610f\u4e49<\/h3>\nQwen3.6-35B-A3B \u7684\u51fa\u73b0，\u52a0\u4e0a llama.cpp + Hermes Agent \u7684\u5de5\u5177\u94fe，\u610f\u5473\u7740：<\/p>\n \n- \n
AI \u4e0d\u518d\u662f\u4e91\u7aef\u7279\u6743\u3002<\/p>\n \u4e00\u53f0\u666e\u901a\u7535\u8111\u5c31\u80fd\u8dd1\u8d77\u80fd\u6253\u7684\u5927\u6a21\u578b<\/p>\n<\/li>\n - \n
\u6570\u636e\u4e3b\u6743\u56de\u5f52\u7528\u6237\u3002<\/p>\n \u654f\u611f\u6570\u636e\u4e0d\u5fc5\u4e0a\u4f20\u7b2c\u4e09\u65b9 API<\/p>\n<\/li>\n - \n
\u96f6\u8fb9\u9645\u6210\u672c\u3002<\/p>\n \u6ca1\u6709 token \u8ba1\u8d39，\u6ca1\u6709\u6708\u8d39，\u60f3\u7528\u591a\u5c11\u7528\u591a\u5c11<\/p>\n<\/li>\n - \n
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2025\u5e74\u524d10\u4e2a\u6708，\u65b0\u53d1AI\u5c97\u4f4d\u91cf\u540c\u6bd4\u589e\u957f543%，9\u6708\u5355\u6708\u540c\u6bd4\u589e\u5e45\u8d8511\u500d\u3002\u540c\u65f6，\u5728\u85aa\u8d44\u65b9\u9762，AI\u9886\u57df\u4e5f\u663e\u8457\u9886\u5148\u3002\u5176\u4e2d，\u6708\u85aa\u6392\u540d\u524d20\u7684\u9ad8\u85aa\u5c97\u4f4d\u5e73\u5747\u6708\u85aa\u5747\u8d85\u8fc76\u4e07\u5143，\u800c\u8fd9\u4e9b\u5e2d\u4f4d\u5927\u90e8\u5206\u88abAI\u7814\u53d1\u5c97\u5360\u636e\u3002<\/p>\n \u4e0e\u6b64\u76f8\u5bf9\u5e94，\u5e02\u573a\u4e3aAI\u4eba\u624d\u652f\u4ed8\u4e86\u663e\u8457\u7684\u6ea2\u4ef7：\u7b97\u6cd5\u5de5\u7a0b\u5e08\u4e2d，\u4e13\u653bAIGC\u65b9\u5411\u7684\u5c97\u4f4d\u5e73\u5747\u85aa\u8d44\u8f83\u666e\u901a\u7b97\u6cd5\u5de5\u7a0b\u5e08\u9ad8\u51fa\u8fd118%；\u4ea7\u54c1\u7ecf\u7406\u5c97\u4f4d\u4e2d，AI\u65b9\u5411\u7684\u4ea7\u54c1\u7ecf\u7406\u85aa\u8d44\u4e5f\u9886\u5148\u7ea620%\u3002<\/p>\n \u5f53\u4f60\u610f\u8bc6\u5230\u201c\u6280\u672f+AI\u201d\u662f\u4e2a\u4eba\u7a81\u56f4\u7684\u6700\u4f73\u8def\u5f84\u65f6，\u6574\u4e2a\u5c31\u4e1a\u5e02\u573a\u7684\u6570\u636e\u4e5f\u5370\u8bc1\u4e86\u540c\u4e00\u4e2a\u4e8b\u5b9e：AI\u5927\u6a21\u578b\u6b63\u6210\u4e3a\u9ad8\u85aa\u673a\u4f1a\u7684\u6700\u5927\u6e90\u5934\u3002<\/p>\n \u6700\u540e<\/h4>\n\u6211\u5728\u4e00\u7ebf\u79d1\u6280\u4f01\u4e1a\u6df1\u8015\u5341\u4e8c\u8f7d，\u89c1\u8bc1\u8fc7\u592a\u591a\u56e0\u6280\u672f\u5361\u4f4d\u800c\u8dc3\u8fc1\u7684\u6848\u4f8b\u3002\u90a3\u4e9b\u7387\u5148\u62e5\u62b1 AI \u7684\u540c\u4e8b，\u65e9\u5df2\u5728\u6548\u7387\u4e0e\u85aa\u8d44\u4e0a\u5f62\u6210\u4ee3\u9645\u4f18\u52bf，\u6211\u610f\u8bc6\u5230\u6709\u5f88\u591a\u7ecf\u9a8c\u548c\u77e5\u8bc6\u503c\u5f97\u5206\u4eab\u7ed9\u5927\u5bb6，\u4e5f\u53ef\u4ee5\u901a\u8fc7\u6211\u4eec\u7684\u80fd\u529b\u548c\u7ecf\u9a8c\u89e3\u7b54\u5927\u5bb6\u5728\u5927\u6a21\u578b\u7684\u5b66\u4e60\u4e2d\u7684\u5f88\u591a\u56f0\u60d1\u3002<\/p>\n \u6211\u6574\u7406\u51fa\u8fd9\u5957 AI \u5927\u6a21\u578b\u7a81\u56f4\u8d44\u6599\u5305\u3010\u5141\u8bb8\u767d\u5ad6\u3011：<\/p>\n \n- \u2705\u4ece\u5165\u95e8\u5230\u7cbe\u901a\u7684\u5168\u5957\u89c6\u9891\u6559\u7a0b<\/li>\n
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👉\u83b7\u53d6\u65b9\u5f0f：
\n\u6709\u9700\u8981\u7684\u5c0f\u4f19\u4f34，\u53ef\u4ee5\u4fdd\u5b58\u56fe\u7247\u5230wx\u626b\u63cf\u4e8cv\u7801\u514d\u8d39\u9886\u53d6\u3010\u4fdd\u8bc1100%\u514d\u8d39\u3011🆓<\/p>\n ![\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\"](\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260826030920-6a8e58e0b44b8.jpg\") <\/p>\n","protected":false},"excerpt":{"rendered":"
\u4e00\u3001\u5148\u770b\u6700\u7ec8\u6548\u679c：\u4f60\u7684\u4e2a\u4eba AI \u57fa\u7840\u8bbe\u65bd
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