{"id":122325,"date":"2026-11-04T17:57:30","date_gmt":"2026-11-04T09:57:30","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/122325.html"},"modified":"2026-11-04T17:57:30","modified_gmt":"2026-11-04T09:57:30","slug":"%e7%be%8e%e5%9b%a2-longcat-2-5-%e6%8e%a5%e5%85%a5%e5%ae%9e%e5%bd%95%ef%bc%9a%e5%8e%9f%e7%94%9f%e5%a4%9a%e6%a8%a1%e6%80%81%e5%9c%a8%e6%99%ba%e8%83%bd%e4%bd%93%e4%bb%bb%e5%8a%a1%e4%b8%ad%e7%9a%84","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/122325.html","title":{"rendered":"\u7f8e\u56e2 LongCat-2.5 \u63a5\u5165\u5b9e\u5f55\uff1a\u539f\u751f\u591a\u6a21\u6001\u5728\u667a\u80fd\u4f53\u4efb\u52a1\u4e2d\u7684\u5de5\u7a0b\u5316\u843d\u5730"},"content":{"rendered":"

\/* MD \/ \u5bcc\u6587\u672c\u4e2d\u7684 .toc\uff08\u542b\u535a\u5ba2\u56ed\u642c\u5bb6\u7b49\u5d4c\u5957\u7ed3\u6784\uff09\uff1b.toc-box \u5728\u4fa7\u680f\uff0c\u4e0d\u53d7\u5f71\u54cd *\/
\n #content_views .toc,
\n \/* \u7f16\u8f91\u5668\u5e38\u5728\u76ee\u5f55\u524d\u540e\u63d2\u5165\u7a7a p\uff08:empty \u4ecd\u5360 20px\uff09\uff0c\u4e00\u5e76\u53bb\u6389\u907f\u514d\u9876\u7a7a\u9699 *\/
\n #content_views.markdown_views > p:empty:has(+ .toc),
\n #content_views.markdown_views > .toc + p:empty,
\n \/* \u5bcc\u6587\u672c\u65e7\u7248\u76ee\u5f55\u6807\u8bb0 *\/
\n #content_views.htmledit_views #main-toc,
\n #content_views.htmledit_views #hr-toc,
\n #content_views.htmledit_views p[id*=\\”-toc\\”] {
\n display: none !important;
\n }
\n \/* \u76ee\u5f55\u53bb\u6389\u540e\uff0c\u7d27\u8ddf\u7684\u9996\u4e2a\u6807\u9898\u4e0d\u518d\u591a\u51fa\u4e00\u5757\u4e0a\u8fb9\u8ddd *\/
\n #content_views.markdown_views > .toc + h1,
\n #content_views.markdown_views > .toc + h2,
\n #content_views.markdown_views > .toc + h3,
\n #content_views.markdown_views > .toc + h4,
\n #content_views.markdown_views > .toc + p:empty + h1,
\n #content_views.markdown_views > .toc + p:empty + h2,
\n #content_views.markdown_views > .toc + p:empty + h3,
\n #content_views.markdown_views > .toc + p:empty + h4 {
\n margin-top: 0 !important;
\n }<\/p>\n

\u6700\u8fd1\u628a LongCat-2.5 \u62c9\u8fdb\u6d4b\u8bd5\u96c6\u7fa4\u8dd1\u4e86\u4e00\u5468\u3002\u8fd9\u6a21\u578b\u660e\u786e\u6253\u7740\u201c\u9762\u5411\u667a\u80fd\u4f53\u4efb\u52a1\u7684\u539f\u751f\u591a\u6a21\u6001\u201d\u6807\u7b7e，\u56e2\u961f\u5185\u90e8\u5bf9\u5b83\u7684\u671f\u5f85\u4e3b\u8981\u96c6\u4e2d\u5728\u4e24\u70b9：\u4e00\u662f\u80fd\u76f4\u63a5\u5403\u622a\u56fe\u3001\u7f51\u9875\u9884\u89c8\u3001OCR \u7ed3\u679c\u505a\u51b3\u7b56；\u4e8c\u662f\u5de5\u5177\u8c03\u7528\u94fe\u8def\u4e0e\u89c6\u89c9\u8f93\u5165\u5728\u540c\u4e00\u5957\u6ce8\u610f\u529b\u673a\u5236\u91cc\u5bf9\u9f50，\u51cf\u5c11\u591a\u6a21\u6001\u7f1d\u5408\u5e26\u6765\u7684\u8bed\u4e49\u5272\u88c2\u3002\u6211\u4e3b\u8981\u505a\u4e86\u4e09\u4ef6\u4e8b：\u628a\u57fa\u7840\u63a8\u7406\u94fe\u8def\u63a5\u901a\u3001\u91cd\u5199\u667a\u80fd\u4f53\u5faa\u73af\u91cc\u7684\u56fe\u6587\u8def\u7531\u4e0e\u8f93\u51fa\u89e3\u6790\u3001\u9488\u5bf9\u9ad8\u5e76\u53d1\u538b\u6d4b\u505a\u5ef6\u8fdf\u4e0e\u663e\u5b58\u4f18\u5316\u3002\u4e0b\u9762\u6309\u5b9e\u9645\u63a8\u8fdb\u987a\u5e8f\u628a\u8e29\u8fc7\u7684\u8def\u6807\u548c\u6539\u8fc7\u7684\u4ee3\u7801\u62c6\u6e05\u695a\u3002<\/p>\n

\u539f\u751f\u591a\u6a21\u6001\u5230\u5e95\u89e3\u51b3\u4e86\u4ec0\u4e48\u75db\u70b9<\/h3>\n

\u5e02\u9762\u4e0a\u5e38\u89c1\u7684\u591a\u6a21\u6001\u65b9\u6848\u57fa\u672c\u662f\u201c\u89c6\u89c9\u7f16\u7801\u5668 + \u8bed\u8a00\u6a21\u578b\u201d\u7684\u4e24\u6bb5\u5f0f\u7ed3\u6784\u3002\u56fe\u50cf\u5148\u8fc7 CLIP \u6216 SigLIP \u53d8\u6210\u5411\u91cf，\u518d\u901a\u8fc7 Cross-Attention \u6295\u5f71\u5230 LLM \u7684 Embedding \u5c42\u3002\u8fd9\u79cd\u6a21\u5f0f\u5728\u5355\u8f6e\u95ee\u7b54\u65f6\u591f\u7528，\u4f46\u4e00\u65e6\u8fdb\u5165\u667a\u80fd\u4f53\u7684\u591a\u8f6e\u6267\u884c\u5faa\u73af，\u95ee\u9898\u5c31\u51fa\u6765\u4e86：\u89c6\u89c9 Token \u548c\u6587\u672c Token \u7684\u5206\u5e03\u4e0d\u5728\u4e00\u4e2a\u7a7a\u95f4\u91cc，\u6a21\u578b\u5728\u89c4\u5212\u4e0b\u4e00\u6b65\u52a8\u4f5c\u65f6\u5bb9\u6613\u4e22\u5931\u7a7a\u95f4\u5173\u7cfb，\u5de5\u5177\u8c03\u7528\u683c\u5f0f\u4e5f\u7ecf\u5e38\u88ab\u89c6\u89c9\u566a\u58f0\u5e72\u6270\u3002<\/p>\n

LongCat-2.5 \u8d70\u7684\u662f\u539f\u751f\u8def\u7ebf\u3002\u4ece\u516c\u5f00\u7684\u6280\u672f\u8bf4\u660e\u770b，\u5b83\u628a\u56fe\u50cf Patch \u76f4\u63a5\u6620\u5c04\u5230\u8bcd\u8868\u7a7a\u95f4，\u548c\u6587\u672c Token \u5171\u4eab Decoder，\u5e76\u5728\u4e2d\u95f4\u5c42\u4fdd\u7559\u4e86\u7ec6\u7c92\u5ea6\u7684\u8de8\u6a21\u6001\u5bf9\u9f50\u6a21\u5757\u3002\u8fd9\u610f\u5473\u7740\u6a21\u578b\u5728\u63a8\u7406\u65f6\u4e0d\u9700\u8981\u989d\u5916\u7684\u6295\u5f71\u5c42，\u6ce8\u610f\u529b\u5934\u53ef\u4ee5\u76f4\u63a5\u770b\u5230\u50cf\u7d20\u7ea7\u7279\u5f81\u548c\u6587\u5b57\u6307\u4ee4\u7684\u8054\u5408\u5206\u5e03\u3002\u5bf9\u667a\u80fd\u4f53\u6765\u8bf4，\u6700\u76f4\u89c2\u7684\u597d\u5904\u662f\u201c\u770b\u56fe\u627e\u6309\u94ae\u201d\u8fd9\u7c7b\u4efb\u52a1\u7684\u8def\u5f84\u66f4\u77ed，\u5c11\u4e86\u4e00\u6b21\u7279\u5f81\u5bf9\u9f50\u7684\u635f\u8017\u3002<\/p>\n

\u8fd9\u91cc\u6709\u4e00\u4e2a\u5fc5\u987b\u8bf4\u6e05\u7684\u9650\u5236：\u539f\u751f\u67b6\u6784\u867d\u7136\u51cf\u5c11\u4e86\u4fe1\u606f\u6298\u635f，\u4f46\u8ba1\u7b97\u56fe\u4e5f\u66f4\u7d27\u51d1\u3002\u56fe\u50cf\u5206\u8fa8\u7387\u4e00\u65e6\u63d0\u9ad8，\u5e8f\u5217\u957f\u5ea6\u4f1a\u6210\u500d\u589e\u957f，\u663e\u5b58\u548c\u5ef6\u8fdf\u538b\u529b\u76f4\u63a5\u63a8\u5230\u524d\u7aef\u3002\u6211\u5728\u672c\u5730\u5148\u7528 1024×1024 \u7684\u6d4b\u8bd5\u96c6\u8dd1\u4e86\u4e00\u904d，\u53d1\u73b0\u5f53\u753b\u9762\u5305\u542b\u5bc6\u96c6 UI \u5143\u7d20\u65f6，\u5355\u8f6e\u63a8\u7406\u65f6\u95f4\u6bd4\u7eaf\u6587\u672c\u57fa\u7ebf\u9ad8\u51fa\u8fd1\u4e09\u500d\u3002\u8fd9\u4e00\u70b9\u5728\u540e\u7eed\u7684\u73af\u5883\u88c1\u526a\u91cc\u505a\u4e86\u9488\u5bf9\u6027\u5904\u7406\u3002<\/p>\n

\u57fa\u7840\u63a8\u7406\u94fe\u8def\u4e0e\u73af\u5883\u914d\u7f6e<\/h3>\n

\u63a5\u5165\u7684\u7b2c\u4e00\u6b65\u662f\u628a\u670d\u52a1\u8dd1\u901a\u3002LongCat-2.5 \u63d0\u4f9b\u4e86\u6807\u51c6 HuggingFace \u6743\u91cd\u548c\u517c\u5bb9 OpenAI \u534f\u8bae\u7684\u63a8\u7406\u63a5\u53e3\u3002\u4e3a\u4e86\u4fdd\u6301\u6846\u67b6\u65e0\u5173\u6027，\u6211\u4f18\u5148\u7528 openai>=1.30.0 \u7684\u5ba2\u6237\u7aef\u5c01\u88c5\u4e86\u4e00\u5c42\u8f7b\u91cf\u7f51\u5173，\u65b9\u4fbf\u540e\u7eed\u5e73\u6ed1\u5207\u6362\u5230 LangChain \u6216\u81ea\u7814 Agent \u6846\u67b6\u3002<\/p>\n

import<\/span> os
\nfrom<\/span> openai import<\/span> AsyncOpenAI<\/p>\n

BASE_URL =<\/span> os.<\/span>getenv(<\/span>"LONGCAT_API_BASE"<\/span>,<\/span> "http:\/\/10.0.0.5:8000\/v1"<\/span>)<\/span>
\nMODEL_NAME =<\/span> "longcat-2.5"<\/span><\/p>\n

client =<\/span> AsyncOpenAI(<\/span>api_key=<\/span>"sk-placeholder"<\/span>,<\/span> base_url=<\/span>BASE_URL)<\/span><\/p>\n

async<\/span> def<\/span> infer_multimodal<\/span>(<\/span>messages:<\/span> list<\/span>[<\/span>dict<\/span>]<\/span>,<\/span> max_tokens:<\/span> int<\/span> =<\/span> 512<\/span>)<\/span> –<\/span>><\/span> str<\/span>:<\/span>
\n """
\n \u53d1\u9001\u56fe\u6587\u6df7\u5408\u8bf7\u6c42\u3002\u6ce8\u610f：base64 \u56fe\u7247\u9700\u63d0\u524d\u538b\u7f29\u81f3 768px \u5bbd，
\n \u907f\u514d\u751f\u6210\u9636\u6bb5 Token \u7206\u70b8\u3002max_tokens \u5fc5\u987b\u4e25\u683c\u9650\u5236，\u9632\u6b62\u8d85\u957f\u5e8f\u5217\u62d6\u57ae\u961f\u5217\u3002
\n """<\/span>
\n resp =<\/span> await<\/span> client.<\/span>chat.<\/span>completions.<\/span>create(<\/span>
\n model=<\/span>MODEL_NAME,<\/span>
\n messages=<\/span>messages,<\/span>
\n max_tokens=<\/span>max_tokens,<\/span>
\n temperature=<\/span>0.2<\/span>,<\/span>
\n response_format=<\/span>{<\/span>"type"<\/span>:<\/span> "json_object"<\/span>}<\/span>,<\/span> # \u4ec5\u7528\u4e8e\u5de5\u5177\u8c03\u7528\u9636\u6bb5<\/span>
\n )<\/span>
\n return<\/span> resp.<\/span>choices[<\/span>0<\/span>]<\/span>.<\/span>message.<\/span>content<\/p>\n

\u4ee3\u7801\u91cc response_format \u53ea\u5728\u9700\u8981\u7ed3\u6784\u5316\u8f93\u51fa\u65f6\u5f00\u542f\u3002\u5e73\u65f6\u591a\u8f6e\u5bf9\u8bdd\u5982\u679c\u5f3a\u5236 JSON，\u6a21\u578b\u4f1a\u628a\u81ea\u7136\u8bed\u8a00\u6307\u4ee4\u4e5f\u585e\u8fdb\u952e\u503c\u5bf9\u91cc，\u53cd\u800c\u589e\u52a0\u89e3\u6790\u6210\u672c\u3002\u53e6\u5916，\u56fe\u7247\u9884\u5904\u7406\u6211\u7edf\u4e00\u7528\u4e86 Pillow \u505a\u7b49\u6bd4\u7f29\u653e\u548c JPEG \u8d28\u91cf\u538b\u7f29\u3002\u8fd9\u4e00\u6b65\u4e0d\u80fd\u7701，\u56e0\u4e3a\u539f\u751f\u591a\u6a21\u6001\u7684\u89c6\u89c9\u5206\u5757\u5668\u5bf9\u539f\u59cb\u50cf\u7d20\u975e\u5e38\u654f\u611f，\u4e0d\u63a7\u5206\u8fa8\u7387\u7684\u8bdd，\u5355\u5f20\u56fe\u5c31\u4f1a\u5403\u6389 200+ \u4e2a Token\u3002<\/p>\n

\u667a\u80fd\u4f53\u5de5\u5177\u8c03\u7528\u7684\u9002\u914d\u903b\u8f91<\/h3>\n

\"\u667a\u80fd\u4f53\u5de5\u5177\u8c03\u7528\u7684\u9002\u914d\u903b\u8f91\"<\/p>\n

\u591a\u6a21\u6001\u667a\u80fd\u4f53\u548c\u7eaf\u6587\u672c\u6700\u5927\u7684\u533a\u522b\u5728\u4e8e\u201c\u52a8\u4f5c\u843d\u5730\u201d\u3002\u6a21\u578b\u770b\u5b8c\u56fe\u540e，\u9700\u8981\u8f93\u51fa\u660e\u786e\u7684\u5de5\u5177\u540d\u79f0\u548c\u53c2\u6570\u3002\u4f46\u539f\u751f\u67b6\u6784\u7684\u8f93\u51fa\u6982\u7387\u5206\u5e03\u66f4\u5bb9\u6613\u53d7\u5230\u89c6\u89c9\u7279\u5f81\u7684\u7275\u5f15，\u7ecf\u5e38\u4f1a\u51fa\u73b0\u5b57\u6bb5\u9519\u4f4d\u6216\u53c2\u6570\u7c7b\u578b\u4e0d\u5bf9\u7684\u60c5\u51b5\u3002<\/p>\n

\u6211\u8c03\u6574\u4e86 Prompt \u6a21\u677f\u548c\u89e3\u6790\u903b\u8f91，\u6838\u5fc3\u601d\u8def\u662f\u628a\u89c6\u89c9\u63cf\u8ff0\u524d\u7f6e\u4e3a\u7cfb\u7edf\u6307\u4ee4，\u5de5\u5177\u5b9a\u4e49\u5355\u72ec\u6210\u5757，\u5e76\u7528\u5f3a\u7ea6\u675f\u7684 Schema \u6536\u53e3\u8f93\u51fa\u3002\u4e0b\u9762\u662f\u5b9e\u9645\u8dd1\u901a\u7684\u793a\u4f8b：<\/p>\n

SYSTEM_PROMPT =<\/span> (<\/span>
\n "\u4f60\u662f\u4e00\u4e2a\u64cd\u4f5c\u754c\u9762\u7684\u667a\u80fd\u4f53\u3002\u8bf7\u5148\u89c2\u5bdf\u63d0\u4f9b\u7684\u622a\u56fe，\u8bc6\u522b\u5f53\u524d\u72b6\u6001，"<\/span>
\n "\u518d\u6839\u636e\u4ee5\u4e0b\u5de5\u5177\u5217\u8868\u9009\u62e9\u6700\u5408\u9002\u7684\u52a8\u4f5c\u3002\u76f4\u63a5\u8f93\u51fa JSON，\u4e0d\u8981\u89e3\u91ca\u3002"<\/span>
\n)<\/span><\/p>\n

TOOLS_SCHEMA =<\/span> {<\/span>
\n "type"<\/span>:<\/span> "object"<\/span>,<\/span>
\n "properties"<\/span>:<\/span> {<\/span>
\n "tool_name"<\/span>:<\/span> {<\/span>"type"<\/span>:<\/span> "string"<\/span>,<\/span> "enum"<\/span>:<\/span> [<\/span>"click"<\/span>,<\/span> "scroll"<\/span>,<\/span> "input_text"<\/span>]<\/span>}<\/span>,<\/span>
\n "params"<\/span>:<\/span> {<\/span>
\n "type"<\/span>:<\/span> "object"<\/span>,<\/span>
\n "properties"<\/span>:<\/span> {<\/span>
\n "target"<\/span>:<\/span> {<\/span>"type"<\/span>:<\/span> "string"<\/span>}<\/span>,<\/span>
\n "value"<\/span>:<\/span> {<\/span>"type"<\/span>:<\/span> "string"<\/span>}<\/span>
\n }<\/span>,<\/span>
\n "required"<\/span>:<\/span> [<\/span>"target"<\/span>]<\/span>
\n }<\/span>
\n }<\/span>,<\/span>
\n "required"<\/span>:<\/span> [<\/span>"tool_name"<\/span>,<\/span> "params"<\/span>]<\/span>
\n}<\/span><\/p>\n

def<\/span> parse_tool_call<\/span>(<\/span>raw_json:<\/span> str<\/span>)<\/span> –<\/span>><\/span> dict<\/span> |<\/span> None<\/span>:<\/span>
\n """\u5bb9\u9519\u89e3\u6790：\u5ffd\u7565\u591a\u4f59\u5b57\u6bb5，\u6821\u9a8c\u5fc5\u9700\u952e"""<\/span>
\n import<\/span> json
\n try<\/span>:<\/span>
\n data =<\/span> json.<\/span>loads(<\/span>raw_json)<\/span>
\n if<\/span> data.<\/span>get(<\/span>"tool_name"<\/span>)<\/span> and<\/span> data.<\/span>get(<\/span>"params"<\/span>)<\/span>:<\/span>
\n return<\/span> data
\n except<\/span> json.<\/span>JSONDecodeError:<\/span>
\n pass<\/span>
\n return<\/span> None<\/span><\/p>\n

\u8fd9\u6bb5\u903b\u8f91\u770b\u4f3c\u7b80\u5355，\u4f46\u5b9e\u9645\u8c03\u8bd5\u65f6\u53d1\u73b0\u4e24\u4e2a\u9690\u85cf\u70b9：\u4e00\u662f\u6a21\u578b\u5076\u5c14\u4f1a\u5728 params \u91cc\u8fd4\u56de\u5e03\u5c14\u503c\u800c\u4e0d\u662f\u5b57\u7b26\u4e32，\u5bfc\u81f4\u4e0b\u6e38\u81ea\u52a8\u5316\u811a\u672c\u62a5\u9519；\u4e8c\u662f\u5f53\u754c\u9762\u5143\u7d20\u91cd\u53e0\u65f6，target \u5b57\u6bb5\u5bb9\u6613\u5199\u6210\u5750\u6807\u800c\u975e\u8bed\u4e49\u6807\u7b7e\u3002\u6211\u5728\u7f51\u5173\u5c42\u52a0\u4e86\u4e00\u5c42\u7c7b\u578b\u8f6c\u6362\u548c\u6b63\u5219\u6e05\u6d17，\u628a\u975e\u9884\u671f\u8f93\u51fa\u515c\u5e95\u56de\u9000\u5230\u201c\u9700\u4eba\u5de5\u786e\u8ba4\u201d\u72b6\u6001\u3002\u5de5\u7a0b\u4e0a\u5b81\u53ef\u6162\u4e00\u70b9，\u4e5f\u4e0d\u80fd\u8ba9\u9519\u8bef\u52a8\u4f5c\u76f4\u63a5\u6267\u884c\u3002<\/p>\n

\u5b9e\u9645\u8fd0\u884c\u4e2d\u7684\u4e24\u4e2a\u5178\u578b\u95ee\u9898<\/h3>\n

\"\u5b9e\u9645\u8fd0\u884c\u4e2d\u7684\u4e24\u4e2a\u5178\u578b\u95ee\u9898\"<\/p>\n

1. \u89c6\u89c9 Token \u5931\u63a7\u5bfc\u81f4\u6392\u961f\u5806\u79ef<\/h4>\n

\u538b\u6d4b\u521d\u671f，QPS \u521a\u62c9\u5230 15，GPU \u5229\u7528\u7387\u5c31\u6389\u5230 40% \u4ee5\u4e0b，\u5ef6\u8fdf\u98d9\u5347\u3002\u6392\u67e5\u53d1\u73b0，\u90e8\u5206\u7528\u6237\u4e0a\u4f20\u7684\u622a\u56fe\u5e26\u6709\u5927\u91cf\u5e7f\u544a Banner \u548c\u52a8\u6001 GIF，\u6a21\u578b\u6ca1\u6709\u8fc7\u6ee4\u8fd9\u4e9b\u533a\u57df，\u76f4\u63a5\u5168\u90e8\u7f16\u5165\u5e8f\u5217\u3002\u539f\u751f\u67b6\u6784\u5bf9\u65e0\u7528\u89c6\u89c9\u4fe1\u606f\u7684\u5bb9\u5fcd\u5ea6\u5f88\u4f4e，\u6ce8\u610f\u529b\u77e9\u9635\u4f1a\u88ab\u7a00\u91ca\u3002<\/p>\n

\u89e3\u51b3\u65b9\u6848\u662f\u5f15\u5165\u9884\u5904\u7406\u7684 ROI（Region of Interest）\u68c0\u6d4b\u3002\u6211\u7528\u8f7b\u91cf\u7ea7\u7684 YOLOv8 \u8dd1\u4e86\u4e2a\u76ee\u6807\u6846\u8fc7\u6ee4，\u53ea\u4fdd\u7559\u6309\u94ae\u3001\u8f93\u5165\u6846\u3001\u5bfc\u822a\u680f\u9644\u8fd1\u7684\u533a\u57df\u91cd\u7ed8\u4e0a\u4f20\u3002\u540c\u65f6\u628a\u7cfb\u7edf\u63d0\u793a\u8bcd\u91cc\u52a0\u4e86\u201c\u5ffd\u7565\u80cc\u666f\u88c5\u9970\u5143\u7d20\u201d\u7684\u7ea6\u675f\u3002\u6548\u679c\u7acb\u7aff\u89c1\u5f71，\u5e73\u5747\u5e8f\u5217\u957f\u5ea6\u4e0b\u964d 60%，QPS \u7a33\u5b9a\u5728 28 \u5de6\u53f3\u3002<\/p>\n

2. \u591a\u8f6e\u4ea4\u4e92\u4e2d\u7684\u7a7a\u95f4\u8bb0\u5fc6\u8870\u51cf<\/h4>\n

\u667a\u80fd\u4f53\u4e0d\u662f\u5355\u6b21\u95ee\u7b54\u3002\u5f53\u8fde\u7eed\u6267\u884c\u201c\u70b9\u51fb\u641c\u7d22\u6846 \u2192 \u8f93\u5165\u5173\u952e\u8bcd \u2192 \u70b9\u51fb\u7b5b\u9009\u201d\u65f6，\u6a21\u578b\u5728\u7b2c\u4e8c\u8f6e\u5f00\u59cb\u9891\u7e41\u8bb0\u9519\u63a7\u4ef6\u4f4d\u7f6e\u3002\u8fd9\u662f\u56e0\u4e3a\u539f\u751f\u591a\u6a21\u6001\u867d\u7136\u80fd\u5728\u5355\u6b65\u5185\u5bf9\u9f50\u56fe\u6587，\u4f46\u7f3a\u4e4f\u663e\u5f0f\u7684\u201c\u5c4f\u5e55\u72b6\u6001\u5feb\u7167\u201d\u7f13\u5b58\u673a\u5236，\u6bcf\u4e00\u8f6e\u90fd\u91cd\u65b0\u5168\u91cf\u7f16\u7801\u5386\u53f2\u56fe\u50cf，\u4e0a\u4e0b\u6587\u7a97\u53e3\u8fc5\u901f\u88ab\u5360\u6ee1\u3002<\/p>\n

\u6211\u6539\u7528\u201c\u589e\u91cf\u66f4\u65b0\u201d\u7b56\u7565：\u9996\u8f6e\u5b8c\u6574\u7f16\u7801，\u540e\u7eed\u8f6e\u6b21\u53ea\u4f20\u5165\u6700\u65b0\u622a\u56fe\u52a0\u4e0a\u4e0a\u4e00\u8f6e\u7684\u201c\u5173\u952e\u63a7\u4ef6\u5750\u6807\u6458\u8981\u201d\u3002\u5728\u6d88\u606f\u5217\u8868\u91cc\u7528\u5143\u6570\u636e\u6807\u8bb0 viewport_snapshot_id，\u7f51\u5173\u5c42\u8d1f\u8d23\u7ef4\u62a4\u4e00\u4efd\u8f7b\u91cf\u7ea7\u7684\u5185\u5b58\u6c60\u3002\u8fd9\u6837\u65e2\u4fdd\u7559\u4e86\u7a7a\u95f4\u8fde\u7eed\u6027，\u53c8\u907f\u514d\u4e86\u91cd\u590d\u8ba1\u7b97\u3002\u591a\u8f6e\u51c6\u786e\u7387\u4ece 62% \u63d0\u5230\u4e86 81%\u3002<\/p>\n

\u90e8\u7f72\u4e0e\u6027\u80fd\u53d6\u820d\u5efa\u8bae<\/h3>\n

\"\u90e8\u7f72\u4e0e\u6027\u80fd\u53d6\u820d\u5efa\u8bae\"<\/p>\n

LongCat-2.5 \u7684\u53c2\u6570\u91cf\u5904\u4e8e\u4e2d\u7b49\u504f\u4e0a\u6c34\u5e73，\u5355\u673a\u90e8\u7f72\u9700\u8981\u8003\u8651\u663e\u5b58\u5e26\u5bbd\u548c\u7f16\u8bd1\u4f18\u5316\u3002\u76ee\u524d\u793e\u533a\u652f\u6301\u7684\u52a0\u901f\u65b9\u6848\u4e3b\u8981\u6709\u4e24\u6761\u8def：<\/p>\n\n\u65b9\u6848\u4f18\u70b9\u7f3a\u70b9\u9002\u7528\u573a\u666f<\/tr>\n\n\n\n\n
vLLM (PagedAttention)<\/td>\n\u541e\u5410\u9ad8，\u5e76\u53d1\u53cb\u597d，\u652f\u6301\u52a8\u6001 Batch<\/td>\n\u5bf9\u81ea\u5b9a\u4e49 Attention \u53d8\u4f53\u517c\u5bb9\u6027\u4e00\u822c，\u9700\u786e\u8ba4 fork \u7248\u672c<\/td>\n\u7eaf\u63a8\u7406\u670d\u52a1\u3001\u9ad8 QPS \u7f51\u5173<\/td>\n<\/tr>\n
TensorRT-LLM<\/td>\n\u6781\u81f4\u5ef6\u8fdf\u4f18\u5316，INT8\/FP8 \u91cf\u5316\u6210\u719f<\/td>\n\u7f16\u8bd1\u5468\u671f\u957f，\u591a\u6a21\u6001\u5206\u652f\u9700\u989d\u5916\u9002\u914d ONNX \u5bfc\u51fa<\/td>\n\u4f4e\u5ef6\u8fdf\u8981\u6c42\u3001\u8fb9\u7f18\u4fa7\u6216\u4e13\u7528\u63a8\u7406\u5361<\/td>\n<\/tr>\n
\u5b98\u65b9 HF \u7ba1\u7ebf<\/td>\n\u5f00\u7bb1\u5373\u7528，\u8c03\u8bd5\u65b9\u4fbf<\/td>\n\u5cf0\u503c\u663e\u5b58\u5360\u7528\u5927，\u6279\u5904\u7406\u6548\u7387\u4f4e<\/td>\n\u539f\u578b\u9a8c\u8bc1\u3001\u5c0f\u89c4\u6a21\u5185\u90e8 Demo<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u6211\u81ea\u5df1\u6700\u7ec8\u9009\u4e86 vLLM \u505a\u5bf9\u5916\u7f51\u5173，\u914d\u5408 –quantization fp8 \u5f00\u542f\u6df7\u5408\u7cbe\u5ea6\u3002\u5b9e\u6d4b\u5728 A100 \u4e0a，FP8 \u6bd4 BF16 \u5ef6\u8fdf\u964d\u4f4e\u7ea6 35%，\u7cbe\u5ea6\u635f\u5931\u63a7\u5236\u5728 1.2% \u4ee5\u5185（\u4ee5\u5185\u90e8 UI \u6807\u6ce8\u96c6\u4e3a\u51c6）\u3002\u5982\u679c\u4f60\u7528\u7684\u662f\u6d88\u8d39\u7ea7\u663e\u5361，\u5efa\u8bae\u628a\u6700\u5927\u5206\u8fa8\u7387\u538b\u5230 512×512，\u5e76\u4f7f\u7528 –gpu-memory-utilization 0.85 \u7559\u51fa\u5b89\u5168\u4f59\u91cf\u3002<\/p>\n

\u53e6\u5916，\u6709\u4e00\u70b9\u6211\u6ca1\u6709\u9a8c\u8bc1：\u5b98\u65b9\u662f\u5426\u8ba1\u5212\u63a8\u51fa\u4e13\u95e8\u9488\u5bf9 Agent \u5de5\u5177\u8c03\u7528\u7684 LoRA \u5fae\u8c03\u5305\u3002\u76ee\u524d\u7684\u901a\u7528\u6743\u91cd\u5df2\u7ecf\u80fd\u7528，\u4f46\u9488\u5bf9\u7279\u5b9a\u4e1a\u52a1\u57df（\u6bd4\u5982\u7535\u5546\u5bfc\u8d2d\u6216\u5916\u5356\u914d\u9001\u6d41\u7a0b）\u505a\u6307\u4ee4\u5bf9\u9f50，\u53ef\u80fd\u8fd8\u9700\u8981\u81ea\u884c\u6536\u96c6\u56fe\u6587-\u52a8\u4f5c\u5bf9\u6570\u636e\u8fdb\u884c SFT\u3002\u5982\u679c\u6709\u8fd9\u5757\u89c4\u5212，\u5efa\u8bae\u7b49\u9879\u76ee\u9875\u66f4\u65b0\u540e\u518d\u6295\u5165\u7b97\u529b\u3002<\/p>\n

\u843d\u5730\u540e\u7684\u7ecf\u9a8c\u603b\u7ed3<\/h3>\n

\u8dd1\u901a\u591a\u6a21\u6001\u667a\u80fd\u4f53\u4e0d\u662f\u6362\u4e2a\u6a21\u578b\u5c31\u80fd\u81ea\u52a8\u53d8\u5f3a\u7684\u4e8b\u60c5\u3002\u539f\u751f\u67b6\u6784\u786e\u5b9e\u7f29\u77ed\u4e86\u7279\u5f81\u5bf9\u9f50\u7684\u8def\u5f84，\u4f46\u5b83\u628a\u539f\u672c\u9760 Prompt \u548c\u89c4\u5219\u63a9\u76d6\u7684\u95ee\u9898，\u76f4\u63a5\u63a8\u5230\u4e86\u63a8\u7406\u548c\u5de5\u7a0b\u5c42\u9762\u3002\u63a7\u5236\u89c6\u89c9 Token \u9884\u7b97\u3001\u7ef4\u62a4\u4f1a\u8bdd\u72b6\u6001\u5feb\u7167\u3001\u4e25\u683c\u7ea6\u675f\u8f93\u51fa Schema，\u8fd9\u4e09\u6b65\u7f3a\u4e00\u4e0d\u53ef\u3002<\/p>\n

\u5982\u679c\u4f60\u6b63\u5728\u8bc4\u4f30\u662f\u5426\u63a5\u5165\u8fd9\u7c7b\u6a21\u578b，\u6211\u7684\u5efa\u8bae\u662f：\u5148\u62ff\u5355\u4e00\u5782\u76f4\u573a\u666f\u505a\u7070\u5ea6，\u6bd4\u5982\u201c\u770b\u56fe\u586b\u8868\u201d\u6216\u201c\u622a\u56fe\u6392\u9519\u201d，\u522b\u4e00\u4e0a\u6765\u5c31\u8dd1\u5168\u94fe\u8def\u81ea\u52a8\u5316\u3002\u7b49\u89e3\u6790\u7a33\u5b9a\u6027\u548c\u5ef6\u8fdf\u66f2\u7ebf\u6253\u5e73\u4e4b\u540e，\u518d\u9010\u6b65\u653e\u5f00\u6743\u9650\u3002\u591a\u6a21\u6001\u7684\u667a\u80fd\u4f53\u624d\u521a\u5f00\u59cb\u722c\u5761，\u5de5\u7a0b\u5c42\u7684\u8010\u5fc3\u5f80\u5f80\u6bd4\u7b97\u6cd5\u5c42\u7684\u6307\u6807\u66f4\u91cd\u8981\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

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