1f1605bdf9
* feat: Add support for overriding tensor buffer type This commit introduces a new configuration option, `override_tensor_buffer_t`, which allows users to specify a regex for matching tensor names to override their buffer type. This is an advanced setting primarily useful for optimizing the performance of large models, particularly Mixture of Experts (MoE) models. By overriding the tensor buffer type, users can keep critical parts of the model, like the attention layers, on the GPU while offloading other parts, such as the expert feed-forward networks, to the CPU. This can lead to significant speed improvements for massive models. Additionally, this change refines the error message to be more specific when a model fails to load. The previous message "Failed to load llama-server" has been updated to "Failed to load model" to be more accurate. * chore: update FE to suppoer override-tensor --------- Co-authored-by: Faisal Amir <urmauur@gmail.com>
Jan - Local AI Assistant
Getting Started - Docs - Changelog - Bug reports - Discord
Jan is an AI assistant that can run 100% offline on your device. Download and run LLMs with full control and privacy.
Installation
The easiest way to get started is by downloading one of the following versions for your respective operating system:
| Platform | Stable | Nightly |
| Windows | jan.exe | jan.exe |
| macOS | jan.dmg | jan.dmg |
| Linux (deb) | jan.deb | jan.deb |
| Linux (AppImage) | jan.AppImage | jan.AppImage |
Download from jan.ai or GitHub Releases.
Features
- Local AI Models: Download and run LLMs (Llama, Gemma, Qwen, etc.) from HuggingFace
- Cloud Integration: Connect to OpenAI, Anthropic, Mistral, Groq, and others
- Custom Assistants: Create specialized AI assistants for your tasks
- OpenAI-Compatible API: Local server at
localhost:1337for other applications - Model Context Protocol: MCP integration for enhanced 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 ≥ 1.22.0
- Make ≥ 3.81
- Rust (for Tauri)
Run with Make
git clone https://github.com/menloresearch/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 launchmake build- Production buildmake test- Run tests and lintingmake clean- Delete everything and start fresh
Run with Mise (easier)
You can also run with mise, which is a bit easier as it ensures Node.js, Rust, and other dependency versions are automatically managed:
git clone https://github.com/menloresearch/jan
cd jan
# Install mise (if not already installed)
curl https://mise.run | sh
# Install tools and start development
mise install # installs Node.js, Rust, and other tools
mise dev # runs the full development setup
Available mise commands:
mise dev- Full development setup and launchmise build- Production buildmise test- Run tests and lintingmise clean- Delete everything and start freshmise tasks- List all available tasks
Manual Commands
yarn install
yarn build:core
yarn build:extensions
yarn dev
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-helpchannel
Contributing
Contributions welcome. See CONTRIBUTING.md for the full spiel.
Links
- Documentation - The manual you should read
- API Reference - For the technically inclined
- Changelog - What we broke and fixed
- Discord - Where the community lives
Contact
- Bugs: GitHub Issues
- Business: hello@jan.ai
- Jobs: hr@jan.ai
- General Discussion: Discord
License
Apache 2.0 - Because sharing is caring.
Acknowledgements
Built on the shoulders of giants: