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Jan

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Open-source, offline-first AI assistant that runs LLMs locally on Mac, Windows, or Linux - 22K+ GitHub stars and fully privacy-preserving.

Jan is an open-source desktop application for running large language models entirely locally, developed by Homebrew - a Singapore-based company focused on privacy-first AI. Launched in late 2023, Jan reached 22,000+ GitHub stars within its first year and is available for macOS, Windows, and Linux. It includes a built-in model hub for browsing and downloading GGUF-format models from Hugging Face, a clean chat interface, and an OpenAI-compatible local API server on port 1337. Jan supports GPU acceleration via Metal on Apple Silicon and CUDA on NVIDIA cards, enabling near-cloud performance on capable consumer hardware without any data leaving the device.

#open-source
#privacy
#local-llm
#ai-assistant
#offline
#developer-tools
Free

Completely free to use

Update Tool
jan.ai
Free
Pricing Model
Chatbots & Assistants
Category
2023
Since
Free Plan
Access

Key Features

  • Run 50+ local LLMs including Llama 3, Mistral, Gemma, and Phi-3 with one-click model download
  • Fully offline operation - zero data sent to external servers after initial model download
  • Built-in model hub for browsing and downloading GGUF-format models from Hugging Face
  • OpenAI-compatible API server at port 1337 - drop-in local replacement for OpenAI API calls
  • Extensions system for optionally connecting to remote APIs including OpenAI, Groq, and Anthropic
  • Cross-platform desktop app with GPU acceleration via Metal (Apple Silicon) and CUDA (NVIDIA)

Use Cases

  • Privacy-conscious professionals running AI assistants without sending any data to cloud providers
  • Developers building and testing apps against a local OpenAI-compatible endpoint at zero API cost
  • Researchers in air-gapped or restricted environments needing AI assistance without internet access
  • Hobbyists experimenting with open-source language models without complex CLI setup or configuration

Pros

  • 100% offline operation ensures complete data privacy - no telemetry, logging, or cloud dependencies
  • OpenAI-compatible local API makes it a zero-cost replacement for development and integration testing
  • 22K+ GitHub stars with active community contributions and frequent model compatibility updates

Cons

  • Performance is hardware-dependent - significantly slower than cloud APIs on consumer-grade machines
  • Large model files (4–70GB) require substantial disk space - not practical on small-SSD laptops
  • Setup and troubleshooting requires more technical comfort than cloud-based chat interfaces

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