简体中文

最佳本地 AI 智能体：在你自己的硬件上运行 AI 助手

七款本地 AI 智能体排名，依据是它们配合 Ollama、vLLM、LM Studio 或 llama.cpp 的运行效果，以及有多少数据留在你自己的机器上。

概览

概览
机器人许可证聊天应用
Agent ZeroMIT2万是是Telegram, WhatsApp免费
QwenPawApache-2.03.7万是否Telegram, iMessage, Discord, Slack免费
ZeroClawMIT OR Apache-2.03.3万是是Telegram, WhatsApp, Discord免费
nanobotMIT5万是否Telegram, WhatsApp, Discord, Slack免费
KhojAGPL-3.03.8万是是无免费
RakazoApache-2.07538是是Telegram, WhatsApp, iMessage, SlackUS$10/月起
OpenClawMIT39.4万是否Telegram, WhatsApp, iMessage, Discord, Slack免费
截至 2026年11月8日 的 GitHub stars

检查清单

检查清单
Agent ZeroQwenPawZeroClawnanobotKhojRakazoOpenClaw
开源许可证是是是是是是是
支持本地模型是是是是是是是
默认沙箱隔离是否是否是是否
默认无遥测否否是是否是否
接入你的聊天应用是是是是否是是
你离开时也能工作是是是是是是是

我们列出的每个智能体都能对接本地模型。但这并不等于它就是一个好的本地 AI 智能体。使用托管模型时，你的提示词、文件和记忆片段在每一轮对话中都会离开你的机器。完全本地化意味着模型、搜索、语音和记忆全部运行在你自己拥有的硬件上，而能让你真正做到这一点的智能体寥寥无几。

我们如何排名

本榜单把本地运行能力放在首位：

  • 支持的本地运行时。 Ollama、vLLM、LM Studio、llama.cpp。选项越多，越能适配你现有的硬件。
  • 还有哪些部分留在本地。 网页搜索、语音转文字、文字转语音和嵌入向量。一个在本地运行模型、却把每次搜索都发给云端 API 的智能体，仍然会泄露你在做什么。
  • 无遥测且有沙箱，依据上方表格中的清单，因为本地优先的用户通常两者都在意。
  • 部署难度与成熟度。

关于硬件的说明：智能体本身很轻量。需要内存和 GPU 的是模型，一个能力足够的本地模型对硬件的要求远高于本榜单中的任何智能体。先确认你的机器能运行哪个模型，再挑选智能体。

1. Agent Zero

Agent Zero 在完全本地化的方向上走得最远。它支持 Ollama、LM Studio、llama.cpp、vLLM 和 oMLX（安装文档），网页搜索通过内置的 SearXNG 实例完成而不是调用搜索 API，语音转文字和文字转语音可以通过内置的 Whisper 和 Kokoro 插件在本地运行（插件）。智能体在自己的 Docker 容器中工作，除非你授予访问权限，否则与你的电脑隔离。

它唯一的遥测是一个更新检查，会发送你的版本号和一个哈希后的实例 ID；你可以在设置中关闭。Agent Zero 本身就需要至少 2 GB 内存，这还不算模型。

Agent Zero web UI showing a request to write a kickoff plan, the agent's collapsed steps for writing and verifying the file in the terminal, and a summary table of the plan
Agent Zero completing a first task in its web UIgithub.com

2. QwenPaw

QwenPaw 来自阿里巴巴的 AgentScope 团队，自带 llama.cpp 运行时，因此无需 API 密钥、也无需单独安装 Ollama 就能完全离线运行（模型文档）。该团队还发布了专为智能体任务训练的小型 QwenPaw-Flash 模型。Ollama 和 LM Studio 同样可用。

它在安全默认设置上排在 Agent Zero 之后：命令沙箱默认关闭，而文档中的快速开始命令 qwenpaw init --defaults 会自动同意匿名安装遥测。改用交互式的 qwenpaw init 即可选择退出。

QwenPaw web console with a new chat, model picker set to qwen3.5-plus, and a sidebar listing Channels, Sessions, Cron Jobs, Heartbeat, Files, Skills, Tools, MCP and Agent Management
QwenPaw's web consolegithub.com

3. ZeroClaw

如果你已经在运行 Ollama 或其他 OpenAI 兼容的模型服务器，ZeroClaw 是最干净的选择。它没有遥测，默认开启操作系统沙箱，并支持提供商回退链，因此可以让本地模型排在第一位、后面跟一个托管模型，或者后面什么都不跟。作为单个 Rust 二进制文件，它能在树莓派这样的小型开发板上运行，再连接到另一台更强机器上的模型服务器。

ZeroClaw homepage headline: The personal AI agent you actually own, one lightweight Rust binary on your machine with your keys or your local models
ZeroClaw's homepagezeroclaw.com

4. nanobot

nanobot 开箱即支持 Ollama、vLLM 和 LM Studio（提供商），不发送遥测，并把记忆以纯 Markdown 文件形式保存在 ~/.nanobot 中，便于查看和备份。它的 WebUI 让本地部署用起来很舒服。在让本地模型运行 shell 命令之前，请先开启它的 bubblewrap 或 Seatbelt 沙箱；默认是关闭的。

nanobot WebUI new-topic screen with Apps, Skills, Automations and Channels in the sidebar, project-grouped topics, and a composer with permission and microphone controls
nanobot's bundled browser WebUIgithub.com

5. Khoj

Khoj 是专才：一个会索引你的笔记和文档并据此回答问题的 AI 第二大脑。它可以完全离线运行，通过 llama.cpp 使用 GGUF 模型，并在你的机器上生成嵌入向量；它也支持 Ollama、LM Studio 和 vLLM（部署）。有 GPU（CUDA、ROCm、Vulkan 或 Apple Metal）会更好。

它排在第五，是因为开发已放缓（自 2026 年 3 月以来没有新版本）、没有聊天应用渠道，并且会发送匿名使用遥测，直到你设置 KHOJ_TELEMETRY_DISABLE=True。

Khoj web app home with a greeting, agent shortcuts for Khoj, Legal, Simplify and Professor, a message box with attach and microphone buttons, and suggestion cards for Paint, Finance and Automation
The Khoj web app's start screendocs.khoj.dev

6. Rakazo

Rakazo（我们开发的产品）通过 Ollama 或 LM Studio 运行本地模型（自托管模型），自托管安装不发送产品分析数据，并为每个机器人提供一台沙箱电脑。它排在这里，是因为它的本地支持比 Agent Zero 或 QwenPaw 窄：只有两种本地运行时，且没有内置运行时。它也仍处于 beta 阶段。请看 Rakazo 评测。

Rakazo web app with a chat with a bot called Chief and a side panel showing the bot's live browser screen, a Take control button and routines
A Rakazo bot chat with its computer screen beside itgithub.com

7. OpenClaw

OpenClaw 支持 Ollama、LM Studio 和 vLLM（Ollama 提供商），所以理应出现在任何本地榜单上，而它庞大的插件生态也是选择它的理由。但对本地优先的用户来说，它的默认设置方向不对：每日更新检查是开启的（update.checkOnStart: false 可以关闭），并且在你开启沙箱之前，命令都在宿主机上运行。如果你想要带本地推理和严格沙箱的 OpenClaw，NemoClaw 会用 Ollama、vLLM 或 NVIDIA NIM 路由来封装它，代价是 8 GB 内存和 alpha 标签。

WhatsApp chat with an OpenClaw assistant giving casual travel advice to a user in Marrakech
Chatting with OpenClaw in WhatsAppdocs.openclaw.ai

在不同机器上运行智能体和模型

PicoClaw 展示了一种实用的模式。它的智能体只需 10 MB 可用内存，能在 10 美元的开发板和旧手机上运行，但仍需要网络连接才能访问模型（硬件文档）。把它或 ZeroClaw 指向一台带 GPU 的台式机上的 Ollama 或 vLLM 服务器，你就能在一台微型设备上拥有一个常驻智能体，而所有推理都在你自己的网络内完成。PicoClaw 没有进入排名，因为该项目表示在 v1.0 之前不要用于生产环境。

想了解更全面的情况，请看最佳自托管 AI 智能体。

精选推荐

  1. Agent Zero

    免费

    Free, MIT-licensed AI agent that runs in its own Docker Linux workspace with a terminal, browser and desktop apps, and chats on Telegram and WhatsApp.

    Runs in its own Docker container with local models, but sends telemetry by default.

    优点

    • Free and MIT licensed, with frequent releases (v2.11 to v2.15 between late August and early November 2026)
    • The agent works in its own Linux workspace with a terminal, browser, desktop apps and LibreOffice, isolated from your computer unless you grant host access
    • Web search runs through a local SearXNG instance, and speech-to-text and text-to-speech can run locally
    • Projects keep memory, files, secrets, instructions and model choices separate per job, with workspace snapshots you can roll back
    • Built-in Telegram, WhatsApp and email channels, a scheduler, MCP and a community Plugin Hub with 200+ plugins

    缺点

    • Needs Docker, and the container image is a full Linux desktop environment rather than a small service
    • No built-in image generation; the docs show teaching it an image API yourself
    • By default it checks for updates with Agent Zero's server, sending your version and a hashed instance ID
    • Code runs in the same container as Agent Zero itself today; per-task sandboxes are only a v3 prototype
    • WhatsApp works by linking a phone account through a Baileys bridge, which needs Node.js, rather than the official WhatsApp Business API
    访问 Agent Zero

  2. QwenPaw

    免费

    Free, Apache-licensed personal AI agent from Alibaba's AgentScope team, formerly CoPaw, with a web console, memory, multiple agents and many chat apps.

    Many chat apps and local models, but no sandbox and telemetry on by default.

    优点

    • Runs fully offline with a built-in llama.cpp runtime and purpose-trained QwenPaw-Flash models, no API key needed
    • Several independent agents, each with its own memory, skills and heartbeat, that can work together
    • Layered security: Tool Guard, File Guard, skill scanning, access policies and an optional kernel-level sandbox
    • Broad chat coverage, especially for Chinese platforms such as DingTalk, Feishu, WeChat and QQ, alongside Telegram, Discord, Slack and iMessage
    • Well-documented web console for channels, cron jobs, heartbeat, skills, MCP and files

    缺点

    • The command sandbox is off by default, and inside Docker it falls back to no isolation
    • The recommended setup command accepts anonymous install telemetry automatically
    • No WhatsApp channel, and iMessage works only on a Mac with a third-party helper and Full Disk Access
    • Desktop apps are still in beta, and the project moves fast, with frequent beta releases
    访问 QwenPaw

  3. ZeroClaw

    免费

    Personal AI agent in one Rust binary, MIT or Apache-2.0, with local or cloud models, 30+ channels, approval gates and an OS sandbox on by default.

    Meets every check: one Rust binary, approval gates and an OS sandbox on by default, no telemetry, local models.

    优点

    • Safe defaults: the recommended profile asks before medium-risk actions, blocks high-risk ones, keeps files in the workspace and runs tools in an OS sandbox
    • One small Rust binary with one config file, running on macOS, Linux, Windows and boards like a Raspberry Pi
    • More than 30 channels, plus a web dashboard for chat, memory, config and cron
    • Provider fallback chains, local models through Ollama, and cryptographic receipts for tool calls
    • States plainly that it sends no telemetry and needs no cloud account or license server

    缺点

    • Slack, iMessage, Signal and several other channels are not in the standard release; you build from source with extra features to get them
    • `zeroclaw quickstart` only sets up the model provider; channels and risk profiles mean editing the TOML config file
    • The Docker sandbox backend isn't picked automatically under the default native runtime
    • Model costs are on you
    访问 ZeroClaw

  4. nanobot

    免费

    Free, MIT-licensed personal AI agent in Python with a browser UI and terminal app, scheduled tasks, memory, and chat on Telegram, Discord, Slack and more.

    Small, readable Python with a good web UI and no telemetry, but shell commands aren't sandboxed by default.

    优点

    • Free and MIT licensed, with a small Python core that is meant to be read and modified
    • Polished bundled WebUI with projects, file diffs, an MCP app catalog and an automations calendar, plus a terminal UI
    • Many chat channels, including Telegram, Discord, Slack, WhatsApp, WeChat, Feishu, Teams, Matrix and email
    • Scheduled automations, long-running goals and a heartbeat that reports only useful results to your last chat
    • Works with local models through Ollama, vLLM or LM Studio

    缺点

    • Shell commands are not sandboxed by default; the bubblewrap or macOS Seatbelt sandbox must be turned on, and Windows has none
    • Model costs are on you, and voice messages need a separate transcription provider such as Groq or OpenAI
    • No native mobile or desktop app; on a phone you use the WebUI in a browser or a chat app
    • Missed scheduled runs are not replayed and interrupted subagent tasks are not relaunched after a restart
    访问 nanobot

  5. Khoj

    免费

    AGPL-licensed, self-hosted AI second brain that chats over your notes and documents with web search, custom agents and scheduled research emails.

    Good at chatting over your own notes and documents, but development has slowed, it has no chat-app channels and telemetry is on by default.

    优点

    • Searches and chats over your own notes and documents, including Markdown, Org-mode, PDF, Word, Notion and GitHub
    • Works with local models through Ollama, LM Studio, vLLM or offline llama.cpp, and generates embeddings on your machine
    • Custom agents with their own persona, knowledge, chat model and tools
    • Automations run a query on a schedule and email you the result
    • Generated code runs in a local Terrarium sandbox that the Docker Compose setup starts for you

    缺点

    • Development has slowed: no release since March 26, 2026, the last commit was on August 2, 2026, and the team now focuses on other products
    • The hosted Khoj Cloud, and with it the WhatsApp bot, shut down on April 15, 2026, so self-hosting is the only way to use it
    • AGPL-3.0 requires you to share your changes if you offer a modified version to others over a network
    • Sends anonymized usage telemetry by default until you set KHOJ_TELEMETRY_DISABLE
    • Scheduled emails need Resend and authentication set up when self-hosting, and no chat apps such as Telegram or Slack are supported
    访问 Khoj

  6. Rakazo

    US$10/月起

    Open-source, self-hostable platform for persistent AI bots that each get a job, a computer, memory and routines, using the model you choose.

    Our own product. Meets every check: Apache-2.0, sandboxed bot computers, no telemetry by default, any model you connect.

    优点

    • Open source (Apache-2.0) and fully self-hostable, including with local models
    • Choice of model per bot, including existing Claude or ChatGPT subscriptions
    • Bots keep working on schedules and triggers with their own cloud computer
    • Approval controls over which actions a bot may take on its own

    缺点

    • Still in beta, with frequent releases
    • You supply and pay for the model on the hosted plans, unless you buy Rakazo credits
    • Telegram, WhatsApp and iMessage/SMS are only available when self-hosted
    • More setup than a single chat app
    访问 Rakazo

  7. OpenClaw

    免费

    Free, MIT-licensed personal AI agent that runs on your own computer and takes orders from WhatsApp, Telegram, iMessage, Slack and 20+ other chat apps.

    The biggest ecosystem and every chat app, but sandboxing is off and telemetry is on by default.

    优点

    • Free and MIT licensed, with no paid tier
    • Runs on your own hardware, and state, memory and credentials stay there
    • Works in 29 chat channels, including WhatsApp, Telegram, iMessage, Slack, Discord and Microsoft Teams
    • Model-agnostic: 64 model and media providers, plus local models
    • Large ecosystem of skills and 142 official plugins, and very active development

    缺点

    • Model costs are on you and can run high: testers and users have reported spending over $100 in a day with expensive models
    • Sandboxing is off by default and the agent can run commands on the host unless you turn on approvals
    • Setup and upkeep expect comfort with the command line; maintainers warn it is risky for non-technical users
    • Broad access to email, messages and the system makes prompt injection and malicious third-party skills a real risk
    访问 OpenClaw

功能

功能
Agent ZeroQwenPawZeroClawnanobotKhojRakazoOpenClaw
联网搜索是是是是是是是
图像生成否是是是是是是
语音模式是是是是是是是
文件上传是是是是是是是
记忆是是是是是是是
代你执行操作是是是是是是是
应用集成是是是是是是是
自主运行是是是是是是是
主动给你发消息是是是是是是是
可运行多个机器人是是是是是是是

来源

Agent Zero

  1. agent0ai/agent-zero on GitHub (MIT, README, safety model)
  2. Agent Zero releases (v0.2 in June 2024 to v2.15 on November 1, 2026)
  3. Agent Zero homepage
  4. Agent Zero docs: Installation (Launcher, A0 Install, Docker, local models)
  5. Agent Zero docs: VPS deployment (hardware requirements)
  6. Agent Zero model provider list
  7. Agent Zero update check code (version and hashed ID sent to api.agent-zero.ai)
  8. Agent Zero built-in Telegram integration plugin
  9. Agent Zero built-in WhatsApp integration plugin
  10. Agent Zero built-in plugins (scheduler, notify user, email, SearXNG search, Whisper STT, Kokoro TTS)
  11. Agent Zero docs: Memory guide
  12. Agent Zero docs: Agent Profiles
  13. Agent Zero docs: API integration (adding image generation yourself)
  14. Agent Zero v3: A Sneak Peek Inside the Sandbox (August 17, 2026)
  15. Agent Zero LLM API (Venice.ai proxy for A0T token stakers)

QwenPaw

  1. agentscope-ai/QwenPaw on GitHub (Apache-2.0, README with install options and telemetry)
  2. QwenPaw documentation
  3. QwenPaw v1.1.0 release notes: CoPaw rebrands to QwenPaw
  4. copaw on PyPI (first release February 2026)
  5. QwenPaw docs: Channels
  6. QwenPaw docs: Models (cloud providers, llama.cpp, Ollama, LM Studio)
  7. QwenPaw docs: Security (Tool Guard, File Guard, sandbox)
  8. QwenPaw source: security.sandbox_enabled defaults to off
  9. QwenPaw docs: Heartbeat
  10. QwenPaw docs: Multi-agent
  11. QwenPaw docs: Comparison (voice and video interaction)
  12. QwenPaw docs: Desktop application (beta)
  13. QwenPaw docs: Plugins (GPT Image 2 image generation plugin)
  14. QwenPaw Qwen-Image tool plugin (image generation and editing)

ZeroClaw

  1. zeroclaw-labs/zeroclaw on GitHub (MIT OR Apache-2.0, v0.8.7, README)
  2. ZeroClaw website
  3. ZeroClaw docs: Sandboxing
  4. ZeroClaw source: risk presets (Balanced, recommended, has the sandbox on)
  5. ZeroClaw docs: Channels overview (default and standard release bundles)
  6. ZeroClaw docs: You own it (no telemetry)
  7. ZeroClaw docs: Docker and containers
  8. ZeroClaw source: tools (image generation, screenshot, web)

nanobot

  1. HKUDS/nanobot on GitHub (MIT, v0.4.1, README)
  2. nanobot documentation
  3. nanobot release archive (officially launched February 2, 2026)
  4. nanobot docs: Chat apps
  5. nanobot docs: Providers and models (Ollama, vLLM, LM Studio)
  6. nanobot docs: Configuration (security, exec sandbox off by default, transcription, Langfuse)
  7. nanobot docs: Automations and heartbeat
  8. nanobot docs: Concepts (heartbeat delivery, subagent recovery)
  9. nanobot docs: Memory and Dream
  10. nanobot docs: Multiple instances
  11. nanobot docs: Deployment (Docker, services, Render)
  12. nanobot source: skills installer runs with DISABLE_TELEMETRY

Khoj

  1. khoj-ai/khoj on GitHub (AGPL-3.0, README)
  2. Khoj releases (latest 2.0.0-beta.28, March 26, 2026)
  3. Khoj commit history (last commit August 2, 2026)
  4. Khoj Cloud Has Been Sunset (April 15, 2026)
  5. Khoj homepage (Open Paper, Pipali and the Khoj app)
  6. khoj-assistant on PyPI (first release 0.1.0, August 2, 2022)
  7. Khoj docs: Self-host setup (Docker, pip, model providers)
  8. Khoj docs: Ollama
  9. Khoj docs: Telemetry
  10. Khoj docs: Privacy
  11. Stop sending client IP in telemetry so it matches the privacy docs (#1382)
  12. Khoj docs: Automations
  13. Khoj docs: Code execution (Terrarium sandbox)
  14. Khoj docs: Agents
  15. Khoj docs: Image generation
  16. Khoj docs: Voice
  17. Khoj docs: WhatsApp (bot tied to Khoj Cloud)
  18. Khoj server settings (memory feature enabled and on by default)

Rakazo

  1. Rakazo homepage
  2. Rakazo pricing
  3. Rakazo privacy policy
  4. Rakazo on GitHub (README and license)
  5. Rakazo changelog
  6. Rakazo releases
  7. Rakazo docs: Image and video generation
  8. Rakazo docs: Memory
  9. Rakazo docs: Connect apps
  10. Rakazo docs: Routines
  11. Rakazo docs: Chat apps
  12. Rakazo docs: Messaging apps (self-hosting)
  13. Rakazo docs: Bots and chats (add another bot, bot templates)
  14. Rakazo docs: Groups (several bots in one chat)
  15. Rakazo docs: Mobile app (notifications)
  16. Rakazo privacy policy (updated Sep 14, 2026)
  17. Rakazo privacy policy source on GitHub
  18. Rakazo docs: Logs and monitoring (product analytics off by default)
  19. Rakazo docs: Desktop app (run locally in Docker, updates)
  20. Rakazo docs: Docker computers
  21. Rakazo docs: Self-hosted models (Ollama, LM Studio)
  22. Rakazo Railway template setup guide

OpenClaw

  1. OpenClaw homepage and Foundation section
  2. OpenClaw integrations: channels, providers and plugins
  3. openclaw/openclaw on GitHub (MIT, v2026.11.1)
  4. OpenClaw docs: Sandboxing (off by default)
  5. Wikipedia: OpenClaw
  6. Notebookcheck: OpenClaw can burn through hundreds of dollars per day
  7. OpenClaw docs: Memory overview
  8. OpenClaw docs: Automations
  9. OpenClaw docs: Chat channels
  10. OpenClaw docs: iMessage
  11. OpenClaw docs: Heartbeat, now a default Proactive check job
  12. OpenClaw docs: Multi-agent routing
  13. OpenClaw docs: Platforms (macOS, Windows, Linux, iOS and Android apps)
  14. OpenClaw docs: Tools (exec, browser, web search)
  15. OpenClaw docs: Audio and voice notes (inbound transcription)
  16. OpenClaw docs: Image and media support (inbound media)
  17. OpenClaw docs: Install (system requirements, installer script, npm, desktop apps, Docker)
  18. OpenClaw docs: One-click deploy on Railway
  19. OpenClaw docs: Usage telemetry and update checks (on by default, feature statistics opt-in)
  20. OpenClaw docs: Ollama provider (local models)