Jan is an open source alternative to ChatGPT that runs 100% offline on your computer.

Jan - Open-source ChatGPT replacement

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Jan is bringing the best of open-source AI in an easy-to-use product. Download and run LLMs with full control and privacy.

Installation

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The easiest way to get started is by downloading one of the following versions for your respective operating system:

Platform

Download

Windows

macOS

Linux (deb)

Linux (AppImage)

Linux (Arm64)

Download from jan.ai or GitHub Releases.

Features

Local AI Models: Download and run LLMs (Llama, Gemma, Qwen, GPT-oss etc.) from HuggingFace
Cloud Integration: Connect to GPT models via OpenAI, Claude models via Anthropic, Mistral, Groq, MiniMax, and others
Custom Assistants: Create specialized AI assistants for your tasks
OpenAI-Compatible API: Local server at localhost:1337 for other applications
Model Context Protocol: MCP integration for agentic capabilities
Privacy First: Everything runs locally when you want it to

Build from Source

For those who enjoy the scenic route:

Prerequisites

Node.js ≥ 20.0.0
Yarn ≥ 4.5.3
Make ≥ 3.81
Rust (for Tauri)
(macOS Apple Silicon only) MetalToolchain xcodebuild -downloadComponent MetalToolchain

Run with Make

git clone https://github.com/janhq/jan
cd jan
make dev

This handles everything: installs dependencies, builds core components, and launches the app.

Available make targets:

make dev - Full development setup and launch
make build - Production build
make test - Run tests and linting
make clean - Delete everything and start fresh

Manual Commands

yarn install
yarn build
yarn dev

Building on Windows

Run make dev from Git Bash (installed with Git for Windows) — make dispatches its recipes through sh, so a plain cmd.exe won't work.

You do not need a "Native Tools Command Prompt for VS 2022". The bundled llama.cpp engine builds with Ninja + clang-cl, and clang-cl locates the MSVC toolchain and Windows SDK on its own. What has to be installed (and on PATH for ninja/clang-cl/cmake):

Visual Studio 2022 Build Tools (MSVC x64 workload + Windows SDK)
LLVM (provides clang-cl)
Ninja
CMake
CUDA Toolkit — only for JAN_ENGINE_VARIANT=cuda12/cuda13 builds

Engine variants are picked with JAN_ENGINE_VARIANT (tokens: cpu, vulkan, metal, cuda12, cuda13, hip/rocm, joined by -), e.g.:

make dev JAN_ENGINE_VARIANT=cuda13

"nvcc fatal : Could not open output file ...fattn-...cu.obj.d" during tauri-plugin-llamacpp(build) means the build path crossed Windows' 260-character MAX_PATH limit — nvcc does not honor the long-path opt-in. The build script now detects this and automatically relocates the llama.cpp build tree to a short directory under %LOCALAPPDATA%\jan-engine. If you hit path-length errors anyway, set JAN_ENGINE_BUILD_DIR to a short path (e.g. C:\jb) or move the checkout closer to the drive root.

System Requirements

Minimum specs for a decent experience:

macOS: 13.6+ (8GB RAM for 3B models, 16GB for 7B, 32GB for 13B)
Windows: 10+ with GPU support for NVIDIA/AMD/Intel Arc
Linux: Most distributions work, GPU acceleration available

For detailed compatibility, check our installation guides.

Troubleshooting

If things go sideways:

Check our troubleshooting docs
Copy your error logs and system specs
Ask for help in our Discord #🆘|jan-help channel

Contributing

Contributions welcome. See CONTRIBUTING.md for the full spiel.

Note: Please sign your commits so we can verify your contributions.

Contact

Bugs: GitHub Issues
Business: [email protected]
Jobs: [email protected]
General Discussion: Discord

License

Apache 2.0 - Because sharing is caring.

Acknowledgements

Built on the shoulders of giants:

jan