[{"data":1,"prerenderedAt":1030},["ShallowReactive",2],{"header-counts":3,"footer-counts":6,"compare-cherry-studio-vs-lobe-chat":9,"compare-a-cherry-studio":10,"compare-b-lobe-chat":539},{"tools":4,"reviews":5},78,26,{"tools":4,"reviews":5,"playbooks":7,"news":8},22,21,null,{"id":11,"title":12,"alternatives":13,"api_compatible":9,"body":18,"category":470,"chinese_friendly":471,"cover":472,"description":473,"domestic":474,"extension":475,"faq":476,"free":474,"github":9,"languages":489,"lastVerified":9,"meta":492,"models":9,"navigation":493,"notSuitable":9,"opensource":493,"path":494,"pillar":495,"platforms":496,"priceTable":501,"pricing":510,"published":511,"relatedPlaybooks":512,"relatedReviews":9,"score":515,"self_host":493,"seo":517,"seoTitle":9,"slug":518,"sources":519,"stem":527,"suitable":9,"tagline":528,"tags":529,"updated":522,"verdict":536,"website":537,"__hash__":538},"tools\u002Ftools\u002Fcoding\u002Flocal\u002Fcherry-studio.md","Cherry Studio",[14,15,16,17],"coding\u002Flocal\u002Flobe-chat","coding\u002Flocal\u002Flm-studio","coding\u002Flocal\u002Follama","coding\u002Flocal\u002Fopen-webui",{"type":19,"value":20,"toc":455},"minimark",[21,26,30,33,36,83,86,100,106,110,115,132,137,154,157,184,187,338,341,373,377,400,403,429,432],[22,23,25],"h2",{"id":24},"tldr","TL;DR",[27,28,29],"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。",[27,31,32],{},"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。",[22,34,35],{"id":35},"核心能力",[37,38,39,47,53,59,65,71,77],"ul",{},[40,41,42,46],"li",{},[43,44,45],"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",[40,48,49,52],{},[43,50,51],{},"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",[40,54,55,58],{},[43,56,57],{},"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",[40,60,61,64],{},[43,62,63],{},"MCP 协议","：扩展工具调用 \u002F 联网搜索 \u002F 文件操作",[40,66,67,70],{},[43,68,69],{},"数据本地优先","：对话历史本地存储，WebDAV 同步，不上传第三方",[40,72,73,76],{},[43,74,75],{},"多模态","：图片识别 \u002F PDF 阅读 \u002F Markdown + Mermaid + 代码高亮",[40,78,79,82],{},[43,80,81],{},"AI 绘画 + 翻译","：内置主流 SD \u002F DALL·E \u002F 翻译 API 集成",[22,84,85],{"id":85},"价格",[37,87,88,94],{},[40,89,90,93],{},[43,91,92],{},"开源版","：完全免费，AGPL-3.0",[40,95,96,99],{},[43,97,98],{},"Enterprise","：私有化部署 + 团队协作 + 资源管控，联系销售",[101,102,103],"blockquote",{},[27,104,105],{},"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。",[22,107,109],{"id":108},"实测mac-m2-中型知识库","实测（Mac M2 + 中型知识库）",[27,111,112],{},[43,113,114],{},"亮点：",[37,116,117,120,123,126,129],{},[40,118,119],{},"中文 UI \u002F 文档 \u002F 社区都顶级，零门槛上手",[40,121,122],{},"本地 RAG 拖入 30+ PDF 后向量化 \u003C 2 分钟（用 bge-m3）",[40,124,125],{},"多模型并排回答：让 Claude \u002F GPT \u002F DeepSeek 同回一个问题做比较",[40,127,128],{},"MCP 接 Brave Search + 自定义工具流畅",[40,130,131],{},"WebDAV 同步坚果云 \u002F 阿里云盘，桌面 + 移动设备数据互通",[27,133,134],{},[43,135,136],{},"踩坑：",[37,138,139,142,145,148,151],{},[40,140,141],{},"没有 Web 端 \u002F Docker 自托管（要这个用 LobeChat）",[40,143,144],{},"iOS 版尚未发布（roadmap 中）",[40,146,147],{},"大型 PDF（>100 MB）向量化偶有失败，要切小",[40,149,150],{},"助手市场质量参差，要自筛",[40,152,153],{},"模型 API 调用全靠你自己付费，新手要先理解 API Key 概念",[22,155,156],{"id":156},"上手",[158,159,160,163,166,175,178,181],"ol",{},[40,161,162],{},"cherry-ai.com 下载客户端（或 GitHub releases）",[40,164,165],{},"设置 → 模型服务 → 填 OpenAI \u002F Claude \u002F DeepSeek API Key",[40,167,168,169],{},"（可选）本地：装 Ollama → Cherry Studio 自动识别 endpoint ",[170,171,172],"a",{"href":172,"rel":173},"http:\u002F\u002Flocalhost:11434",[174],"nofollow",[40,176,177],{},"新建知识库 → 拖文件 \u002F 加网址 → 等向量化",[40,179,180],{},"新对话 → 选模型 → 勾知识库 → 提问",[40,182,183],{},"进阶：自定义助手（System Prompt）+ MCP 扩展工具",[22,185,186],{"id":186},"对比",[188,189,190,211],"table",{},[191,192,193],"thead",{},[194,195,196,200,202,205,208],"tr",{},[197,198,199],"th",{},"维度",[197,201,12],{},[197,203,204],{},"LobeChat",[197,206,207],{},"LM Studio",[197,209,210],{},"Open WebUI",[212,213,214,231,245,261,274,290,305,321],"tbody",{},[194,215,216,220,223,226,228],{},[217,218,219],"td",{},"形态",[217,221,222],{},"桌面",[217,224,225],{},"Web + 桌面",[217,227,222],{},[217,229,230],{},"Docker \u002F 桌面",[194,232,233,235,238,240,243],{},[217,234,45],{},[217,236,237],{},"✅ 云 + 本地",[217,239,237],{},[217,241,242],{},"本地为主",[217,244,237],{},[194,246,247,250,253,255,258],{},[217,248,249],{},"知识库 RAG",[217,251,252],{},"✅ 强",[217,254,252],{},[217,256,257],{},"弱",[217,259,260],{},"✅",[194,262,263,266,268,270,272],{},[217,264,265],{},"MCP",[217,267,260],{},[217,269,260],{},[217,271,257],{},[217,273,260],{},[194,275,276,279,282,285,288],{},[217,277,278],{},"自托管 \u002F Web",[217,280,281],{},"无 Web",[217,283,284],{},"✅ Docker",[217,286,287],{},"无",[217,289,284],{},[194,291,292,295,298,300,303],{},[217,293,294],{},"中文",[217,296,297],{},"5\u002F5",[217,299,297],{},[217,301,302],{},"4\u002F5",[217,304,302],{},[194,306,307,310,313,316,319],{},[217,308,309],{},"开源协议",[217,311,312],{},"AGPL-3.0",[217,314,315],{},"MIT",[217,317,318],{},"闭源（免费）",[217,320,315],{},[194,322,323,326,329,332,335],{},[217,324,325],{},"GitHub Stars",[217,327,328],{},"60k+",[217,330,331],{},"72k+",[217,333,334],{},"–",[217,336,337],{},"126k+",[22,339,340],{"id":340},"避坑",[37,342,343,349,355,361,367],{},[40,344,345,348],{},[43,346,347],{},"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",[40,350,351,354],{},[43,352,353],{},"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",[40,356,357,360],{},[43,358,359],{},"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",[40,362,363,366],{},[43,364,365],{},"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",[40,368,369,372],{},[43,370,371],{},"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",[22,374,376],{"id":375},"适合-不适合","适合 \u002F 不适合",[37,378,379,382,385,388,391,394,397],{},[40,380,381],{},"✅ 中文用户、AI 重度使用 \u002F 多模型管理",[40,383,384],{},"✅ 需要本地 RAG 知识库",[40,386,387],{},"✅ 关注数据隐私 \u002F 本地存储",[40,389,390],{},"✅ 想用 Ollama \u002F LM Studio 本地模型",[40,392,393],{},"❌ 需要 Web 端 \u002F Docker 自托管",[40,395,396],{},"❌ 团队多人共享 \u002F SSO",[40,398,399],{},"❌ iOS 主力用户",[22,401,402],{"id":402},"相关阅读",[37,404,405,411,417,423],{},[40,406,407],{},[170,408,410],{"href":409},"\u002Ftools\u002Fcoding\u002Flocal\u002Flobe-chat","LobeChat 评测",[40,412,413],{},[170,414,416],{"href":415},"\u002Ftools\u002Fcoding\u002Flocal\u002Flm-studio","LM Studio 评测",[40,418,419],{},[170,420,422],{"href":421},"\u002Ftools\u002Fcoding\u002Flocal\u002Follama","Ollama 评测",[40,424,425],{},[170,426,428],{"href":427},"\u002Fplaybook\u002Fonboarding\u002Frag-pipeline-build","RAG Pipeline 搭建 Playbook",[22,430,431],{"id":431},"来源",[158,433,434,441,448],{},[40,435,436,437],{},"Cherry Studio 官网（功能 + 下载）",[170,438,439],{"href":439,"rel":440},"https:\u002F\u002Fwww.cherry-ai.com\u002F",[174],[40,442,443,444],{},"MBLUO Studio — Cherry Studio 评测 2026 ",[170,445,446],{"href":446,"rel":447},"https:\u002F\u002Fmbluostudio.com\u002Ftools\u002Fcherry-studio",[174],[40,449,450,451],{},"Cursor IDE 博客 — Cherry Studio 完全指南（2025-03）",[170,452,453],{"href":453,"rel":454},"https:\u002F\u002Fwww.cursor-ide.com\u002Fblog\u002Fcherry-studio-guide",[174],{"title":456,"searchDepth":457,"depth":457,"links":458},"",3,[459,461,462,463,464,465,466,467,468,469],{"id":24,"depth":460,"text":25},2,{"id":35,"depth":460,"text":35},{"id":85,"depth":460,"text":85},{"id":108,"depth":460,"text":109},{"id":156,"depth":460,"text":156},{"id":186,"depth":460,"text":186},{"id":340,"depth":460,"text":340},{"id":375,"depth":460,"text":376},{"id":402,"depth":460,"text":402},{"id":431,"depth":460,"text":431},"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",[477,480,483,486],{"q":478,"a":479},"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":481,"a":482},"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":484,"a":485},"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":487,"a":488},"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。",[490,491],"zh","en",{},true,"\u002Ftools\u002Fcoding\u002Flocal\u002Fcherry-studio","coding",[497,498,499,500],"windows","macos","linux","android",[502,506],{"plan":92,"price":503,"features":504,"notes":505},"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":98,"price":507,"features":508,"notes":509},"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",[513,514],"onboarding\u002Frag-pipeline-build","onboarding\u002Fcursor-mcp-deep-integration",{"power":516,"ux":471,"price":471,"cn_support":471,"stability":516},4,{"title":12,"description":473},"coding\u002Flocal\u002Fcherry-studio",[520,523,525],{"name":521,"url":439,"accessed":522},"Cherry Studio 官网","2026-06-24",{"name":524,"url":446,"accessed":522},"MBLUO Studio — Cherry Studio 评测",{"name":526,"url":453,"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",[470,530,531,532,533,534,535],"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","LAkkQWZMoqlr7XC7II0hPyN5bwRJkF6rbuSjkfZz2eA",{"id":540,"title":204,"alternatives":541,"api_compatible":9,"body":542,"category":470,"chinese_friendly":471,"cover":982,"description":983,"domestic":474,"extension":475,"faq":984,"free":474,"github":9,"languages":997,"lastVerified":9,"meta":998,"models":9,"navigation":493,"notSuitable":9,"opensource":493,"path":409,"pillar":495,"platforms":999,"priceTable":1002,"pricing":1010,"published":511,"relatedPlaybooks":1011,"relatedReviews":9,"score":1013,"self_host":493,"seo":1014,"seoTitle":9,"slug":14,"sources":1015,"stem":1022,"suitable":9,"tagline":1023,"tags":1024,"updated":522,"verdict":1027,"website":1028,"__hash__":1029},"tools\u002Ftools\u002Fcoding\u002Flocal\u002Flobe-chat.md",[518,17,16,15],{"type":19,"value":543,"toc":970},[544,546,553,556,558,621,623,636,639,643,647,667,671,688,690,716,718,854,856,894,896,922,924,945,947],[22,545,25],{"id":24},[27,547,548,549,552],{},"LobeChat 是 LobeHub 团队的开源 AI 聊天框架，2023 年发布、GitHub 72k+ stars、MIT 协议。",[43,550,551],{},"Web + 桌面 + Docker 自托管三形态","，把 OpenAI \u002F Claude \u002F Gemini \u002F DeepSeek \u002F Qwen \u002F Kimi \u002F Ollama \u002F LM Studio 等 80+ 模型聚合到一个现代设计的客户端里。内置 RAG 知识库 + 插件市场 + 助手市场 + 多模型对比 + MCP，是当下综合最强的多模型 AI 客户端之一。",[27,554,555],{},"适合：需要 Web 端访问、Docker 自托管、多模型对比、丰富助手市场的用户；中文重度用户；想给团队 \u002F 家庭部署一个共享 AI 工作台。不适合：只用桌面 + 不需要 Web（Cherry Studio 同样优秀且更精细）、强企业 RBAC + 多租户（Open WebUI 多用户更完善）。",[22,557,35],{"id":35},[37,559,560,565,571,576,582,588,593,598,604,610],{},[40,561,562,564],{},[43,563,45],{},"：OpenAI \u002F Claude \u002F Gemini \u002F DeepSeek \u002F Qwen \u002F Kimi \u002F 豆包 \u002F Groq \u002F Together \u002F OpenRouter \u002F Ollama \u002F LM Studio",[40,566,567,570],{},[43,568,569],{},"多模型对比","：同 prompt 给多模型并排回答",[40,572,573,575],{},[43,574,51],{},"：上传 PDF \u002F Word \u002F 网页 → 向量化 → 检索引用",[40,577,578,581],{},[43,579,580],{},"插件市场","：联网搜索 \u002F 代码执行 \u002F 图像生成 \u002F 翻译等几十款官方插件",[40,583,584,587],{},[43,585,586],{},"助手市场","：几百个预设 AI 角色，一键导入",[40,589,590,592],{},[43,591,63],{},"：扩展任意工具能力",[40,594,595],{},[43,596,597],{},"代码解释器 \u002F 文件上传 \u002F TTS \u002F 多模态",[40,599,600,603],{},[43,601,602],{},"Web + 桌面 + Docker","：三形态，数据可完全本地",[40,605,606,609],{},[43,607,608],{},"LobeHub Cloud","：官方云托管，免部署",[40,611,612,615,616,620],{},[43,613,614],{},"快捷指令 \u002F 工作流","：自定义 prompt 模板，",[617,618,619],"code",{},"\u002Fpodcast-summary"," 类用法",[22,622,85],{"id":85},[37,624,625,631],{},[40,626,627,630],{},[43,628,629],{},"自托管 \u002F 桌面","：完全免费、MIT 开源",[40,632,633,635],{},[43,634,608],{},"：订阅制，云端托管 + 团队协作 + 同步",[27,637,638],{},"模型 API 费用按你自己的供应商付费；本地 Ollama \u002F LM Studio 零成本。",[22,640,642],{"id":641},"实测m2-自托管-docker连-openai-deepseek-本地-ollama","实测（M2 + 自托管 Docker，连 OpenAI + DeepSeek + 本地 Ollama）",[27,644,645],{},[43,646,114],{},[37,648,649,652,655,658,661,664],{},[40,650,651],{},"界面颜值是这一类工具里第一档（深色 \u002F 透明 \u002F 现代感）",[40,653,654],{},"多模型并排对比对选型极其有用：写一道复杂题，Claude \u002F GPT \u002F DeepSeek 直接对比答案",[40,656,657],{},"知识库 RAG 上传 50+ PDF 后检索准确，引用片段可视化",[40,659,660],{},"助手市场拿来即用——「Code Reviewer」「Translation Polish」节省 prompt 编写",[40,662,663],{},"Docker 一键部署，团队 5 人共享流畅",[40,665,666],{},"多平台数据同步（Cloud \u002F WebDAV）",[27,668,669],{},[43,670,136],{},[37,672,673,676,679,682,685],{},[40,674,675],{},"自托管要熟悉 Docker + 反代 + HTTPS",[40,677,678],{},"国内连 OpenAI \u002F Claude 需自带网络方案",[40,680,681],{},"Web 版数据存 LobeHub，隐私敏感场景走桌面 \u002F Docker",[40,683,684],{},"插件市场质量参差，要自筛",[40,686,687],{},"团队多人共享需配 LobeHub Cloud 或自建数据库（Postgres + S3）",[22,689,156],{"id":156},[158,691,692,695,701,704,707,710,713],{},[40,693,694],{},"选形态：Web（chat.lobehub.com 注册即用） \u002F 桌面（GitHub Releases 下载） \u002F Docker",[40,696,697,698],{},"Docker：",[617,699,700],{},"docker run -d -p 3210:3210 -e OPENAI_API_KEY=sk-xxx --name lobe-chat lobehub\u002Flobe-chat",[40,702,703],{},"设置 → AI 服务商 → 添加 OpenAI \u002F Claude \u002F DeepSeek \u002F Ollama",[40,705,706],{},"模型选择器测试对话",[40,708,709],{},"知识库：拖文件 → 等向量化 → 对话引用",[40,711,712],{},"助手市场拉「Code Reviewer」「论文翻译润色」试用",[40,714,715],{},"进阶：插件市场启用联网搜索 \u002F 代码执行；MCP 自定义工具",[22,717,186],{"id":186},[188,719,720,734],{},[191,721,722],{},[194,723,724,726,728,730,732],{},[197,725,199],{},[197,727,204],{},[197,729,12],{},[197,731,210],{},[197,733,207],{},[212,735,736,748,761,774,787,803,816,830,842],{},[194,737,738,740,742,744,746],{},[217,739,219],{},[217,741,602],{},[217,743,222],{},[217,745,230],{},[217,747,222],{},[194,749,750,752,755,757,759],{},[217,751,45],{},[217,753,754],{},"✅ 80+",[217,756,260],{},[217,758,260],{},[217,760,242],{},[194,762,763,765,768,770,772],{},[217,764,569],{},[217,766,767],{},"✅ 一等",[217,769,260],{},[217,771,257],{},[217,773,257],{},[194,775,776,778,780,782,785],{},[217,777,249],{},[217,779,260],{},[217,781,260],{},[217,783,784],{},"✅ + oikb",[217,786,257],{},[194,788,789,792,795,798,801],{},[217,790,791],{},"插件 \u002F 助手市场",[217,793,794],{},"✅ 丰富",[217,796,797],{},"300+ 助手",[217,799,800],{},"Tools",[217,802,257],{},[194,804,805,807,809,811,814],{},[217,806,265],{},[217,808,260],{},[217,810,260],{},[217,812,813],{},"✅ mcpo",[217,815,257],{},[194,817,818,821,824,826,828],{},[217,819,820],{},"多用户",[217,822,823],{},"配 Cloud \u002F 自建",[217,825,287],{},[217,827,767],{},[217,829,287],{},[194,831,832,834,836,838,840],{},[217,833,325],{},[217,835,331],{},[217,837,328],{},[217,839,337],{},[217,841,334],{},[194,843,844,846,848,850,852],{},[217,845,309],{},[217,847,315],{},[217,849,312],{},[217,851,315],{},[217,853,318],{},[22,855,340],{"id":340},[37,857,858,864,870,876,882,888],{},[40,859,860,863],{},[43,861,862],{},"Web 版数据不本地","：隐私敏感选桌面或 Docker 自托管",[40,865,866,869],{},[43,867,868],{},"国内连海外模型走中转","：直连 OpenAI \u002F Claude 不稳，配 OpenRouter \u002F Ofox \u002F 国内中转",[40,871,872,875],{},[43,873,874],{},"Docker 自托管暴露公网","：上反代 + HTTPS + Auth + 备份数据库",[40,877,878,881],{},[43,879,880],{},"嵌入模型中文优化","：默认嵌入对中文一般，配 bge-m3 \u002F 硅基流动 Pro 版",[40,883,884,887],{},[43,885,886],{},"插件市场审一遍","：第三方插件可执行代码，团队部署谨慎启用",[40,889,890,893],{},[43,891,892],{},"同步选 Cloud vs WebDAV","：团队多端走 LobeHub Cloud；个人多设备 WebDAV 即可",[22,895,376],{"id":375},[37,897,898,901,904,907,910,913,916,919],{},[40,899,900],{},"✅ Web + 桌面双形态需求",[40,902,903],{},"✅ Docker 自托管 \u002F 团队共享",[40,905,906],{},"✅ 多模型对比 \u002F 选型",[40,908,909],{},"✅ 中文重度用户",[40,911,912],{},"✅ 助手市场 \u002F 插件生态用户",[40,914,915],{},"❌ 强企业 RBAC + 多租户（Open WebUI 更完善）",[40,917,918],{},"❌ 只要桌面 + 数据完全本地（Cherry Studio 同样优秀）",[40,920,921],{},"❌ 完全不会碰 Docker",[22,923,402],{"id":402},[37,925,926,931,937,941],{},[40,927,928],{},[170,929,930],{"href":494},"Cherry Studio 评测",[40,932,933],{},[170,934,936],{"href":935},"\u002Ftools\u002Fcoding\u002Flocal\u002Fopen-webui","Open WebUI 评测",[40,938,939],{},[170,940,422],{"href":421},[40,942,943],{},[170,944,428],{"href":427},[22,946,431],{"id":431},[158,948,949,956,963],{},[40,950,951,952],{},"LobeChat GitHub 仓库（72k+ stars，MIT）",[170,953,954],{"href":954,"rel":955},"https:\u002F\u002Fgithub.com\u002Flobehub\u002Flobe-chat",[174],[40,957,958,959],{},"腾讯云开发者社区 — Lobe Chat 本地化 AI 聊天终极桌面客户端（2026-01）",[170,960,961],{"href":961,"rel":962},"https:\u002F\u002Fcloud.tencent.com\u002Fdeveloper\u002Farticle\u002F2622150",[174],[40,964,965,966],{},"Ofox.ai — LobeChat 完全配置指南 2026（2026-04-17）",[170,967,968],{"href":968,"rel":969},"https:\u002F\u002Fofox.ai\u002Fzh\u002Fblog\u002Flobechat-api-configuration-guide-2026",[174],{"title":456,"searchDepth":457,"depth":457,"links":971},[972,973,974,975,976,977,978,979,980,981],{"id":24,"depth":460,"text":25},{"id":35,"depth":460,"text":35},{"id":85,"depth":460,"text":85},{"id":641,"depth":460,"text":642},{"id":156,"depth":460,"text":156},{"id":186,"depth":460,"text":186},{"id":340,"depth":460,"text":340},{"id":375,"depth":460,"text":376},{"id":402,"depth":460,"text":402},{"id":431,"depth":460,"text":431},"\u002Fimg\u002Ftools\u002Flobe-chat.webp","LobeChat 真实评测：LobeHub 团队开源 AI 聊天框架，GitHub 72k+ stars、MIT 协议。Web + 桌面（Win\u002FMac\u002FLinux\u002FDocker）双形态，支持 OpenAI \u002F Claude \u002F Gemini \u002F DeepSeek \u002F Qwen \u002F Ollama 等 80+ 模型，内置 RAG 知识库 + 插件市场 + 助手市场 + 多模型对比。",[985,988,991,994],{"q":986,"a":987},"Web 版 vs 桌面版 vs Docker 自托管，怎么选？","Web 版（chat.lobehub.com）最快上手但数据存 LobeHub 服务器；桌面版数据本地存、隐私好；Docker 自托管对团队 \u002F 公司部署最优，完全掌控数据。",{"q":989,"a":990},"支持哪些模型？","80+ 模型：OpenAI 全系列、Anthropic Claude、Google Gemini、DeepSeek、Qwen、Kimi、Moonshot、字节豆包、Groq、Together、OpenRouter、Ollama \u002F LM Studio 本地模型，以及任何 OpenAI 兼容 API。",{"q":992,"a":993},"多模型对比怎么用？","同一对话窗口里把消息广播给多个模型并排回答，选型 \u002F 评估特别有用——直接看 Claude 和 GPT 在同一 prompt 下的回答差异。",{"q":995,"a":996},"助手市场是什么？","LobeHub 维护的预设 AI 角色市场（代码审查 \u002F 翻译 \u002F 写作 \u002F 角色扮演等几百个），一键拉到本地用，省去自己写 System Prompt。",[490,491],{},[1000,497,498,499,1001],"web","docker",[1003,1006],{"plan":629,"price":503,"features":1004,"notes":1005},"全功能 \u002F 80+ 模型 \u002F 知识库 \u002F 插件 \u002F 助手市场","MIT 协议",{"plan":608,"price":1007,"features":1008,"notes":1009},"订阅制","云端托管 \u002F 免部署 \u002F 团队协作 \u002F 同步","chat.lobehub.com 注册即用","完全免费（MIT 开源） \u002F LobeHub Cloud 订阅",[513,1012],"onboarding\u002Fclaude-code-getting-started",{"power":471,"ux":471,"price":471,"cn_support":471,"stability":516},{"title":204,"description":983},[1016,1018,1020],{"name":1017,"url":954,"accessed":522},"LobeChat GitHub",{"name":1019,"url":961,"accessed":522},"腾讯云开发者社区 — Lobe Chat 终极桌面客户端",{"name":1021,"url":968,"accessed":522},"Ofox.ai — LobeChat 完全配置指南 2026","tools\u002Fcoding\u002Flocal\u002Flobe-chat","现代设计的开源 AI 聊天框架——Web + 桌面双形态、72k+ stars、多模型 + 知识库 + 插件市场",[470,1000,530,531,533,1025,1026,534],"plugin","mcp","颜值与功能双优的多模型 AI 聊天客户端。要 Web + 桌面双形态、自托管 Docker、多模型对比、丰富助手市场——LobeChat 是综合最强；纯桌面体验 Cherry Studio 同样优秀。","https:\u002F\u002Flobehub.com","pm20AeqHCiMi5MF0JALNWKY72MAdrs-uWEpbDmfEKbY",1784565442319]