Jan is an open-source desktop application built around running large models offline on your own computer, maintained by the Menlo Research team, and aimed at people who do not want their conversations sent to the cloud but also do not want to touch a command line. It has gathered more than forty thousand stars on GitHub and uses the Apache-2.0 licence, which is permissive for both personal and commercial use. The problem it solves is concrete: it folds downloading a model, loading it and starting to chat into one graphical interface, making local models feel like ordinary installable software for the first time.
Official repository information
Platform: GitHub. Organisation: janhq. Project: jan. The app runs on Windows, macOS and Linux. After installation you can download open models such as Llama, Gemma, Qwen and gpt-oss directly from Hugging Face and run them locally, entirely offline if you wish. It also leaves a door open to the cloud: you can add your own keys for providers such as OpenAI and Anthropic, and it offers a local service compatible with the OpenAI interface on port 1337 of your own machine, plus MCP support, so other local programs can call the same model.
The real cost is hardware, not installation
Installing Jan is not hard; the actual threshold is your computer. The official guidance is roughly 8 GB of memory for a small model around 3B parameters, 16 GB for 7B and 32 GB for 13B, and the model files themselves take several to tens of gigabytes of disk. It runs without a dedicated graphics card, only noticeably slower, so long answers take patience. In short, what you save is subscription fees and worries about data leaving your machine; what you pay is disk space, memory and waiting time, and that bill should be understood before downloading the first model.
Three honest pitfalls
First, offline chat does not mean cloud flagship ability. What runs smoothly locally is mostly small and mid-sized models, and complex reasoning, long-form writing and subtle multilingual work still trail the big cloud models, so expectations should follow the model you pick. Second, you choose the model yourself. The app can hold many models, and beginners easily get lost in the download list; starting with one general model around 7B is far more practical than grabbing five or six at once. Third, it is a single-user desktop app with no team accounts, permission management or central operations, so teams that need shared, governed use should look at server options instead of forcing Jan into that role. Jan suits people whose computer is reasonably capable, whose chats often contain material that should not go to the cloud, and who accept trading speed for privacy. With only 8 GB of memory and a priority on answer quality, a cloud service remains the easier choice.
