jan

Jan addresses the challenge of running large language models (LLMs) fully offline on personal computers, offering privacy and control that cloud-based services cannot provide. It supports local execution of popular open models like Llama and GPT-oss from HuggingFace, while also enabling optional cloud integration with OpenAI, Anthropic, and others, making it flexible for hybrid use cases. Its architecture includes a local server compatible with OpenAI's API, easing integration with existing tools. The project is actively maintained with a recent commit in March 2026 and has attracted over 41,000 stars, indicating significant interest, though it lacks notable growth momentum recently. It is best suited for ML/AI engineers who need private, offline-capable AI assistants or want to experiment with multiple model backends. Jan is not ideal if your priority is a fully managed cloud service or if you require a mature ecosystem with extensive third-party plugins, where alternatives like LangChain or OpenAI's hosted APIs might be preferable.

Choose Jan when you need a desktop-friendly, privacy-first LLM interface that can run entirely offline or combine local and cloud models with a unified API. If you want a fully managed cloud-based chatbot or more extensive integration frameworks, consider OpenAI's API or LangChain instead, as they offer broader ecosystem support and less local setup complexity.

Jan typically fits teams building internal AI assistants for sensitive data environments, such as offline knowledge bases or private RAG (retrieval-augmented generation) systems. It also suits experimental setups where developers want to test multiple LLMs locally or create custom AI assistants without sending data to external servers.

Latest commit: 2026-03-24. Activity data is based on daily RepoPi snapshots of the GitHub repository.