[{"data":1,"prerenderedAt":982},["ShallowReactive",2],{"header-counts":3,"footer-counts":6,"compare-cherry-studio-vs-jan":8,"compare-a-cherry-studio":9,"compare-b-jan":539},{"tools":4,"reviews":5},98,27,{"tools":4,"reviews":5,"playbooks":7,"news":5},22,null,{"id":10,"title":11,"alternatives":12,"api_compatible":8,"body":17,"category":469,"chinese_friendly":470,"cover":471,"description":472,"domestic":473,"extension":474,"faq":475,"free":473,"github":8,"languages":488,"lastVerified":8,"meta":491,"models":8,"navigation":492,"notSuitable":8,"opensource":492,"path":493,"pillar":494,"platforms":495,"priceTable":500,"pricing":509,"published":510,"relatedPlaybooks":511,"relatedReviews":8,"score":514,"self_host":492,"seo":516,"seoTitle":517,"slug":518,"sources":519,"stem":527,"suitable":8,"tagline":528,"tags":529,"updated":522,"verdict":536,"website":537,"__hash__":538},"tools\u002Ftools\u002Fcoding\u002Flocal\u002Fcherry-studio.md","Cherry Studio",[13,14,15,16],"coding\u002Flocal\u002Flobe-chat","coding\u002Flocal\u002Flm-studio","coding\u002Flocal\u002Follama","coding\u002Flocal\u002Fopen-webui",{"type":18,"value":19,"toc":454},"minimark",[20,25,29,32,35,82,85,99,105,109,114,131,136,153,156,183,186,337,340,372,376,399,402,428,431],[21,22,24],"h2",{"id":23},"tldr","TL;DR",[26,27,28],"p",{},"Cherry Studio 是一款开源、跨平台（Windows \u002F macOS \u002F Linux \u002F Android）的桌面 AI 客户端，定位『全能 AI 工作台』：把 OpenAI \u002F Anthropic \u002F Google \u002F DeepSeek 等云端模型，以及 Ollama \u002F LM Studio 本地模型，全部聚合到同一个桌面应用里管理。内置 300+ 助手模板、本地 RAG 知识库、Markdown + Mermaid 渲染、MCP 协议支持，所有对话数据本地存储 + WebDAV 备份。AGPL-3.0 开源、GitHub 60k+ stars，企业版可联系商务做私有化部署。",[26,30,31],{},"适合：中文 AI 重度用户、想统一管理多家模型、需要本地知识库 RAG、关注数据本地存储的开发者 \u002F 研究者。不适合：要 Web 端访问 \u002F Docker 自托管 \u002F 团队多人共享 \u002F iOS 端使用。",[21,33,34],{"id":34},"核心能力",[36,37,38,46,52,58,64,70,76],"ul",{},[39,40,41,45],"li",{},[42,43,44],"strong",{},"多模型聚合","：OpenAI \u002F Claude \u002F Gemini \u002F DeepSeek \u002F Qwen \u002F Kimi \u002F Moonshot 等云端 + Ollama \u002F LM Studio 本地",[39,47,48,51],{},[42,49,50],{},"本地 RAG 知识库","：拖拽 PDF \u002F Word \u002F Excel \u002F PPT \u002F 网址 \u002F sitemap → 自动向量化 → 检索增强问答 + 来源追溯",[39,53,54,57],{},[42,55,56],{},"300+ 助手模板","：编程 \u002F 写作 \u002F 翻译 \u002F 学习 \u002F 角色扮演开箱即用，可自定义 System Prompt",[39,59,60,63],{},[42,61,62],{},"MCP 协议","：扩展工具调用 \u002F 联网搜索 \u002F 文件操作",[39,65,66,69],{},[42,67,68],{},"数据本地优先","：对话历史本地存储，WebDAV 同步，不上传第三方",[39,71,72,75],{},[42,73,74],{},"多模态","：图片识别 \u002F PDF 阅读 \u002F Markdown + Mermaid + 代码高亮",[39,77,78,81],{},[42,79,80],{},"AI 绘画 + 翻译","：内置主流 SD \u002F DALL·E \u002F 翻译 API 集成",[21,83,84],{"id":84},"价格",[36,86,87,93],{},[39,88,89,92],{},[42,90,91],{},"开源版","：完全免费，AGPL-3.0",[39,94,95,98],{},[42,96,97],{},"Enterprise","：私有化部署 + 团队协作 + 资源管控，联系销售",[100,101,102],"blockquote",{},[26,103,104],{},"模型 API 费用按你自己绑定的供应商计费；本地 Ollama \u002F LM Studio 零成本。",[21,106,108],{"id":107},"实测mac-m2-中型知识库","实测（Mac M2 + 中型知识库）",[26,110,111],{},[42,112,113],{},"亮点：",[36,115,116,119,122,125,128],{},[39,117,118],{},"中文 UI \u002F 文档 \u002F 社区都顶级，零门槛上手",[39,120,121],{},"本地 RAG 拖入 30+ PDF 后向量化 \u003C 2 分钟（用 bge-m3）",[39,123,124],{},"多模型并排回答：让 Claude \u002F GPT \u002F DeepSeek 同回一个问题做比较",[39,126,127],{},"MCP 接 Brave Search + 自定义工具流畅",[39,129,130],{},"WebDAV 同步坚果云 \u002F 阿里云盘，桌面 + 移动设备数据互通",[26,132,133],{},[42,134,135],{},"踩坑：",[36,137,138,141,144,147,150],{},[39,139,140],{},"没有 Web 端 \u002F Docker 自托管（要这个用 LobeChat）",[39,142,143],{},"iOS 版尚未发布（roadmap 中）",[39,145,146],{},"大型 PDF（>100 MB）向量化偶有失败，要切小",[39,148,149],{},"助手市场质量参差，要自筛",[39,151,152],{},"模型 API 调用全靠你自己付费，新手要先理解 API Key 概念",[21,154,155],{"id":155},"上手",[157,158,159,162,165,174,177,180],"ol",{},[39,160,161],{},"cherry-ai.com 下载客户端（或 GitHub releases）",[39,163,164],{},"设置 → 模型服务 → 填 OpenAI \u002F Claude \u002F DeepSeek API Key",[39,166,167,168],{},"（可选）本地：装 Ollama → Cherry Studio 自动识别 endpoint ",[169,170,171],"a",{"href":171,"rel":172},"http:\u002F\u002Flocalhost:11434",[173],"nofollow",[39,175,176],{},"新建知识库 → 拖文件 \u002F 加网址 → 等向量化",[39,178,179],{},"新对话 → 选模型 → 勾知识库 → 提问",[39,181,182],{},"进阶：自定义助手（System Prompt）+ MCP 扩展工具",[21,184,185],{"id":185},"对比",[187,188,189,210],"table",{},[190,191,192],"thead",{},[193,194,195,199,201,204,207],"tr",{},[196,197,198],"th",{},"维度",[196,200,11],{},[196,202,203],{},"LobeChat",[196,205,206],{},"LM Studio",[196,208,209],{},"Open WebUI",[211,212,213,230,244,260,273,289,304,320],"tbody",{},[193,214,215,219,222,225,227],{},[216,217,218],"td",{},"形态",[216,220,221],{},"桌面",[216,223,224],{},"Web + 桌面",[216,226,221],{},[216,228,229],{},"Docker \u002F 桌面",[193,231,232,234,237,239,242],{},[216,233,44],{},[216,235,236],{},"✅ 云 + 本地",[216,238,236],{},[216,240,241],{},"本地为主",[216,243,236],{},[193,245,246,249,252,254,257],{},[216,247,248],{},"知识库 RAG",[216,250,251],{},"✅ 强",[216,253,251],{},[216,255,256],{},"弱",[216,258,259],{},"✅",[193,261,262,265,267,269,271],{},[216,263,264],{},"MCP",[216,266,259],{},[216,268,259],{},[216,270,256],{},[216,272,259],{},[193,274,275,278,281,284,287],{},[216,276,277],{},"自托管 \u002F Web",[216,279,280],{},"无 Web",[216,282,283],{},"✅ Docker",[216,285,286],{},"无",[216,288,283],{},[193,290,291,294,297,299,302],{},[216,292,293],{},"中文",[216,295,296],{},"5\u002F5",[216,298,296],{},[216,300,301],{},"4\u002F5",[216,303,301],{},[193,305,306,309,312,315,318],{},[216,307,308],{},"开源协议",[216,310,311],{},"AGPL-3.0",[216,313,314],{},"MIT",[216,316,317],{},"闭源（免费）",[216,319,314],{},[193,321,322,325,328,331,334],{},[216,323,324],{},"GitHub Stars",[216,326,327],{},"60k+",[216,329,330],{},"72k+",[216,332,333],{},"–",[216,335,336],{},"126k+",[21,338,339],{"id":339},"避坑",[36,341,342,348,354,360,366],{},[39,343,344,347],{},[42,345,346],{},"API Key 别明文外泄","：客户端配置文件以明文存 Key，机器借出前先清；团队共享用企业版 \u002F 自建中转",[39,349,350,353],{},[42,351,352],{},"知识库别一次塞太多","：单库 1000+ 文档检索质量明显下降，按主题切分多个知识库",[39,355,356,359],{},[42,357,358],{},"嵌入模型选择","：免费 bge-m3 够用；专业用付费 Pro\u002FBAAI\u002Fbge-m3 或 OpenAI text-embedding-3",[39,361,362,365],{},[42,363,364],{},"WebDAV 同步先小范围测","：知识库向量数据较大，先备份对话再开同步",[39,367,368,371],{},[42,369,370],{},"MCP 工具来源要可控","：MCP 是给 AI 真实工具能力，第三方插件审一遍代码",[21,373,375],{"id":374},"适合-不适合","适合 \u002F 不适合",[36,377,378,381,384,387,390,393,396],{},[39,379,380],{},"✅ 中文用户、AI 重度使用 \u002F 多模型管理",[39,382,383],{},"✅ 需要本地 RAG 知识库",[39,385,386],{},"✅ 关注数据隐私 \u002F 本地存储",[39,388,389],{},"✅ 想用 Ollama \u002F LM Studio 本地模型",[39,391,392],{},"❌ 需要 Web 端 \u002F Docker 自托管",[39,394,395],{},"❌ 团队多人共享 \u002F SSO",[39,397,398],{},"❌ iOS 主力用户",[21,400,401],{"id":401},"相关阅读",[36,403,404,410,416,422],{},[39,405,406],{},[169,407,409],{"href":408},"\u002Ftools\u002Fcoding\u002Flocal\u002Flobe-chat","LobeChat 评测",[39,411,412],{},[169,413,415],{"href":414},"\u002Ftools\u002Fcoding\u002Flocal\u002Flm-studio","LM Studio 评测",[39,417,418],{},[169,419,421],{"href":420},"\u002Ftools\u002Fcoding\u002Flocal\u002Follama","Ollama 评测",[39,423,424],{},[169,425,427],{"href":426},"\u002Fplaybook\u002Fonboarding\u002Frag-pipeline-build","RAG Pipeline 搭建 Playbook",[21,429,430],{"id":430},"来源",[157,432,433,440,447],{},[39,434,435,436],{},"Cherry Studio 官网（功能 + 下载）",[169,437,438],{"href":438,"rel":439},"https:\u002F\u002Fwww.cherry-ai.com\u002F",[173],[39,441,442,443],{},"MBLUO Studio — Cherry Studio 评测 2026 ",[169,444,445],{"href":445,"rel":446},"https:\u002F\u002Fmbluostudio.com\u002Ftools\u002Fcherry-studio",[173],[39,448,449,450],{},"Cursor IDE 博客 — Cherry Studio 完全指南（2025-03）",[169,451,452],{"href":452,"rel":453},"https:\u002F\u002Fwww.cursor-ide.com\u002Fblog\u002Fcherry-studio-guide",[173],{"title":455,"searchDepth":456,"depth":456,"links":457},"",3,[458,460,461,462,463,464,465,466,467,468],{"id":23,"depth":459,"text":24},2,{"id":34,"depth":459,"text":34},{"id":84,"depth":459,"text":84},{"id":107,"depth":459,"text":108},{"id":155,"depth":459,"text":155},{"id":185,"depth":459,"text":185},{"id":339,"depth":459,"text":339},{"id":374,"depth":459,"text":375},{"id":401,"depth":459,"text":401},{"id":430,"depth":459,"text":430},"local",5,"\u002Fimg\u002Ftools\u002Fcherry-studio.webp","Cherry Studio 真实评测：开源跨平台桌面 AI 客户端，集成 OpenAI \u002F Claude \u002F Gemini \u002F DeepSeek + Ollama \u002F LM Studio 本地模型，内置 300+ 助手模板 + 本地 RAG 知识库。AGPL-3.0 开源、GitHub 60k+ stars，企业版另询。",false,"md",[476,479,482,485],{"q":477,"a":478},"Cherry Studio 真的免费吗？","是。客户端完全免费、AGPL-3.0 开源，模型调用走你自己的 API Key（OpenAI \u002F Claude \u002F Gemini \u002F DeepSeek 等付费）或本地 Ollama \u002F LM Studio（零成本）。",{"q":480,"a":481},"本地知识库怎么用？","在『知识库』面板新建，拖文件 \u002F 加网址 \u002F 填 sitemap，系统自动向量化（默认 BAAI\u002Fbge-m3 或硅基流动的 Pro 版）；提问时勾选要检索的知识库，AI 会基于检索片段答题并标出来源。",{"q":483,"a":484},"和 LobeChat 怎么选？","都开源、多模型、有 RAG。LobeChat 是 Web + 桌面双形态，可自托管 Docker，72k stars；Cherry Studio 是纯桌面（Win\u002FMac\u002FLinux\u002FAndroid），不支持 Web 部署但桌面体验更精细，60k+ stars。要 Web 访问 \u002F 公司多人共享选 LobeChat；个人重度选 Cherry Studio。",{"q":486,"a":487},"支持 MCP \u002F 插件吗？","支持 MCP（Model Context Protocol）扩展，配合自定义助手（System Prompt）可扩展工具调用、联网搜索等能力。",[489,490],"zh","en",{},true,"\u002Ftools\u002Fcoding\u002Flocal\u002Fcherry-studio","coding",[496,497,498,499],"windows","macos","linux","android",[501,505],{"plan":91,"price":502,"features":503,"notes":504},"免费","300+ 助手模板 \u002F 云端 + 本地模型 \u002F 知识库 \u002F MCP \u002F WebDAV 备份","AGPL-3.0 开源",{"plan":97,"price":506,"features":507,"notes":508},"联系销售","私有化部署 \u002F 团队协作 \u002F AI 资源管控 \u002F 知识库管理","面向企业团队","开源免费 \u002F 企业版联系销售","2026-06-19",[512,513],"onboarding\u002Frag-pipeline-build","onboarding\u002Fcursor-mcp-deep-integration",{"power":515,"ux":470,"price":470,"cn_support":470,"stability":515},4,{"title":11,"description":472},"Cherry Studio 评测 2026：AI 客户端工具，多模型桌面助手，开源免费","coding\u002Flocal\u002Fcherry-studio",[520,523,525],{"name":521,"url":438,"accessed":522},"Cherry Studio 官网","2026-06-24",{"name":524,"url":445,"accessed":522},"MBLUO Studio — Cherry Studio 评测",{"name":526,"url":452,"accessed":522},"Cursor IDE 博客 — Cherry Studio 指南","tools\u002Fcoding\u002Flocal\u002Fcherry-studio","全能 AI 客户端：多模型聚合 + 本地知识库 + 300+ 助手模板，跨平台桌面应用",[469,530,531,532,533,534,535],"desktop","multi-model","knowledge-base","rag","open-source","china","国产 AI 桌面客户端第一梯队，多模型聚合 + 本地 RAG + 中文体验顶级。需要 Web 部署 \u002F 自托管选 LobeChat；只要桌面体验完整选 Cherry Studio。","https:\u002F\u002Fcherry-ai.com","CVmnny2iirvdFz56djfCs7oCOn1Mjv6hZCZ5SNO0U0Q",{"id":540,"title":541,"alternatives":542,"api_compatible":8,"body":543,"category":469,"chinese_friendly":456,"cover":958,"description":959,"domestic":473,"extension":474,"faq":8,"free":473,"github":942,"languages":960,"lastVerified":961,"meta":962,"models":8,"navigation":492,"notSuitable":8,"opensource":492,"path":963,"pillar":494,"platforms":964,"priceTable":8,"pricing":965,"published":966,"relatedPlaybooks":8,"relatedReviews":8,"score":967,"self_host":473,"seo":968,"seoTitle":969,"slug":970,"sources":971,"stem":974,"suitable":8,"tagline":975,"tags":976,"updated":961,"verdict":980,"website":935,"__hash__":981},"tools\u002Ftools\u002Fcoding\u002Flocal\u002Fjan.md","Jan",[14,518,15],{"type":18,"value":544,"toc":945},[545,547,554,557,559,609,611,616,642,645,649,656,673,677,694,696,716,718,824,826,858,860,883,887,893,899,905,907,922,924,929],[21,546,24],{"id":23},[26,548,549,550,553],{},"Jan 是开源的本地 LLM 桌面客户端，定位是",[42,551,552],{},"ChatGPT 的离线替代品","。界面设计精美，操作体验接近 ChatGPT，支持 GGUF 模型一键下载、本地推理、多模型切换、插件扩展。AGPL 开源，完全免费。适合想要一个好看好用的本地 AI 聊天工具、隐私优先的用户。",[26,555,556],{},"适合：想要 ChatGPT 颜值和体验的本地替代、个人离线聊天、隐私敏感场景、非技术用户（GUI 友好）。不适合：需要 OpenAI 兼容 API 给应用接入（用 Ollama）、需要模型调参 \u002F 量化选择（用 LM Studio）、企业商用（AGPL 限制）。",[21,558,34],{"id":34},[36,560,561,567,573,579,585,591,597,603],{},[39,562,563,566],{},[42,564,565],{},"ChatGPT 式界面","：聊天 UI 设计精美，多会话管理、Markdown 渲染、代码高亮",[39,568,569,572],{},[42,570,571],{},"一键下载模型","：内置模型市场，搜索 GGUF 模型点击下载，自动配置",[39,574,575,578],{},[42,576,577],{},"本地推理","：基于 llama.cpp，支持 CPU \u002F GPU 加速，完全离线运行",[39,580,581,584],{},[42,582,583],{},"多模型切换","：一个会话可切换不同模型对比输出，方便评估",[39,586,587,590],{},[42,588,589],{},"插件系统","：支持扩展功能，如网页搜索、文档分析、API 代理等",[39,592,593,596],{},[42,594,595],{},"远程 API 接入","：除了本地模型，也支持接 OpenAI \u002F Anthropic 等云端 API",[39,598,599,602],{},[42,600,601],{},"跨平台桌面 App","：Win \u002F Mac \u002F Linux 原生安装包，Electron 构建",[39,604,605,608],{},[42,606,607],{},"隐私优先","：所有数据本地存储，无遥测，无云端调用（本地模型模式）",[21,610,84],{"id":84},[100,612,613],{},[26,614,615],{},"以下信息为 2026-07-30 核实。",[187,617,618,630],{},[190,619,620],{},[193,621,622,625,627],{},[196,623,624],{},"方案",[196,626,84],{},[196,628,629],{},"说明",[211,631,632],{},[193,633,634,636,639],{},[216,635,91],{},[216,637,638],{},"$0",[216,640,641],{},"完整功能，AGPL 协议",[26,643,644],{},"完全免费。注意 AGPL 协议：个人使用无限制，但二次开发 \u002F 商用需遵守开源传染条款。",[21,646,648],{"id":647},"体验与评测资料整理","体验与评测（资料整理）",[100,650,651],{},[26,652,653,654],{},"说明：本节基于官方文档与公开评测整理，非本站独立实测环境，具体数据请以官方为准。\n",[42,655,113],{},[36,657,658,661,664,667,670],{},[39,659,660],{},"界面设计是同类最佳：比 LM Studio \u002F GPT4All 好看很多，接近 ChatGPT 体验",[39,662,663],{},"模型下载体验顺滑：搜索 → 下载 → 使用，全程 GUI，零命令行",[39,665,666],{},"多模型对比实用：同一问题切换模型看不同回答，选模型很方便",[39,668,669],{},"插件系统有潜力：网页搜索插件让本地模型也能联网",[39,671,672],{},"支持云端 API 混用：本地模型 + GPT-4o 切换，一个客户端搞定",[26,674,675],{},[42,676,135],{},[36,678,679,682,685,688,691],{},[39,680,681],{},"Electron 应用内存占用偏高，老设备偶有卡顿",[39,683,684],{},"模型管理不如 LM Studio：量化版本选择少，调参选项有限",[39,686,687],{},"API Server 功能弱：有 OpenAI 兼容端点但不如 Ollama 灵活",[39,689,690],{},"插件生态尚不成熟，可用插件不多",[39,692,693],{},"AGPL 协议对企业不友好，商用需注意合规",[21,695,155],{"id":155},[157,697,698,701,704,707,710,713],{},[39,699,700],{},"从 jan.ai 下载对应平台安装包",[39,702,703],{},"安装后打开 Jan，界面类似 ChatGPT",[39,705,706],{},"点击模型市场（Hub）→ 搜索推荐模型（Qwen2.5-7B \u002F Llama3.1-8B）",[39,708,709],{},"下载模型后，新建会话 → 选择模型 → 开始聊天",[39,711,712],{},"多模型对比：同一会话切换模型或开多个会话",[39,714,715],{},"接云端 API：Settings → API Keys → 填入 OpenAI Key 即可混用",[21,717,185],{"id":185},[187,719,720,735],{},[190,721,722],{},[193,723,724,726,728,730,733],{},[196,725,198],{},[196,727,541],{},[196,729,206],{},[196,731,732],{},"Ollama",[196,734,11],{},[211,736,737,753,767,781,795,809],{},[193,738,739,742,745,748,751],{},[216,740,741],{},"界面颜值",[216,743,744],{},"高",[216,746,747],{},"中",[216,749,750],{},"无 GUI",[216,752,744],{},[193,754,755,758,760,763,765],{},[216,756,757],{},"模型管理",[216,759,747],{},[216,761,762],{},"强",[216,764,762],{},[216,766,747],{},[193,768,769,772,775,777,779],{},[216,770,771],{},"API 接入",[216,773,774],{},"基础",[216,776,259],{},[216,778,762],{},[216,780,259],{},[193,782,783,786,788,791,793],{},[216,784,785],{},"插件扩展",[216,787,259],{},[216,789,790],{},"❌",[216,792,790],{},[216,794,259],{},[193,796,797,800,802,804,807],{},[216,798,799],{},"云端 API 混用",[216,801,259],{},[216,803,259],{},[216,805,806],{},"需配",[216,808,259],{},[193,810,811,813,816,819,821],{},[216,812,308],{},[216,814,815],{},"AGPL",[216,817,818],{},"闭源",[216,820,314],{},[216,822,823],{},"Apache",[21,825,339],{"id":339},[36,827,828,834,840,846,852],{},[39,829,830,833],{},[42,831,832],{},"别指望它做 API 服务器","：Jan 的 API Server 功能基础，给应用接入用 Ollama",[39,835,836,839],{},[42,837,838],{},"模型选对量化","：默认下载的可能不是最优量化，手动选 Q4_K_M 平衡速度质量",[39,841,842,845],{},[42,843,844],{},"Electron 吃内存","：8GB RAM 设备跑大模型 + Jan 本身会卡，关其他应用",[39,847,848,851],{},[42,849,850],{},"AGPL 商用注意","：企业内部署需法务确认 AGPL 合规",[39,853,854,857],{},[42,855,856],{},"插件别装太多","：部分插件质量参差，可能影响稳定性",[21,859,375],{"id":374},[36,861,862,865,868,871,874,877,880],{},[39,863,864],{},"✅ 想要 ChatGPT 颜值和体验的本地替代",[39,866,867],{},"✅ 个人离线聊天 \u002F 隐私优先场景",[39,869,870],{},"✅ 非技术用户（GUI 友好，零命令行）",[39,872,873],{},"✅ 本地 + 云端 API 混用需求",[39,875,876],{},"❌ 需要给应用 \u002F IDE 接入 API（用 Ollama）",[39,878,879],{},"❌ 需要精细模型调参 \u002F 量化管理（用 LM Studio）",[39,881,882],{},"❌ 企业商用（AGPL 限制）",[21,884,886],{"id":885},"faq","FAQ",[26,888,889,892],{},[42,890,891],{},"Q: Jan 和 LM Studio 怎么选？","\nA: 颜值和聊天体验选 Jan，模型管理和调参选 LM Studio。Jan 更像 ChatGPT，LM Studio 更像模型工具箱。两者都免费，可以都装。",[26,894,895,898],{},[42,896,897],{},"Q: 能给 Cursor \u002F Cline 接入吗？","\nA: Jan 有 OpenAI 兼容 API Server（默认端口 1337），理论上可以。但不如 Ollama 稳定灵活，推荐用 Ollama 做 API 服务器。",[26,900,901,904],{},[42,902,903],{},"Q: AGPL 协议影响个人使用吗？","\nA: 不影响。AGPL 主要约束网络服务分发场景。个人本地使用完全无限制。只有你把 Jan 改造后对外提供 SaaS 服务才需开源你的修改。",[21,906,401],{"id":401},[26,908,909,913,914,913,918],{},[169,910,912],{"href":911},"\u002Fcoding\u002Flocal\u002Fgpt4all.html","GPT4All"," · ",[169,915,917],{"href":916},"\u002Fcoding\u002Flocal\u002Fvllm.html","vLLM",[169,919,921],{"href":920},"\u002Fagent\u002Fdesktop\u002Fopen-interpreter.html","Open Interpreter",[21,923,430],{"id":430},[100,925,926],{},[26,927,928],{},"本文的价格、版本号与性能数据均参考以下官方渠道整理，可能随时间变动，请以官方实时信息为准。",[36,930,931,938],{},[39,932,933],{},[169,934,937],{"href":935,"rel":936},"https:\u002F\u002Fjan.ai",[173],"官网",[39,939,940],{},[169,941,944],{"href":942,"rel":943},"https:\u002F\u002Fgithub.com\u002Fjanhq\u002Fjan",[173],"GitHub",{"title":455,"searchDepth":456,"depth":456,"links":946},[947,948,949,950,951,952,953,954,955,956,957],{"id":23,"depth":459,"text":24},{"id":34,"depth":459,"text":34},{"id":84,"depth":459,"text":84},{"id":647,"depth":459,"text":648},{"id":155,"depth":459,"text":155},{"id":185,"depth":459,"text":185},{"id":339,"depth":459,"text":339},{"id":374,"depth":459,"text":375},{"id":885,"depth":459,"text":886},{"id":401,"depth":459,"text":401},{"id":430,"depth":459,"text":430},"\u002Fimg\u002Ftools\u002Fjan.webp","Jan 真实评测：开源本地 LLM 桌面客户端（AGPL 协议），定位 ChatGPT 的离线替代，支持 GGUF 模型一键下载 + 本地推理 + 插件扩展。跨平台桌面 app，适合需要完全离线、隐私优先的本地 AI 聊天场景。",[490],"2026-07-30",{},"\u002Ftools\u002Fcoding\u002Flocal\u002Fjan",[496,497,498],"Free \u002F 开源（AGPL）","2026-07-05",{"power":456,"ux":515,"price":470,"cn_support":456,"stability":456},{"title":541,"description":959},"Jan - 开源本地 LLM 桌面客户端评测 | AIHO","coding\u002Flocal\u002Fjan",[972,973],{"title":937,"url":935},{"title":944,"url":942},"tools\u002Fcoding\u002Flocal\u002Fjan","开源本地 LLM 桌面客户端，定位 ChatGPT 的离线替代",[469,530,977,978,979],"opensource","gguf","offline","颜值最高、最像 ChatGPT 的开源本地 LLM 客户端，离线聊天体验好；但 API 能力和模型管理不如 Ollama\u002FLM Studio，定位偏轻量个人使用。","SYftPw58WAWIAEA4qHpFo2Ki3Z1H9q97Rp4jQR560KE",1785428443707]