Jan vs Ollama
| Tagline | Offline-first, privacy-focused desktop app to run LLMs locally on any hardware | Run large language models locally with a simple CLI and REST API |
| Category | AI & LLM Tools | AI & LLM Tools |
| Replaces | ChatGPT, OpenAI API | OpenAI API, ChatGPT |
| GitHub stars | 24k | 175k |
| Language | TypeScript | Docker |
| License | AGPL-3.0 | MIT |
| Self-host difficulty | 1/5 Effortless | 2/5 Easy |
| Deploy options | Manual | Docker Manual |
| Managed hosting | ||
| Last updated | 1 month ago | 5 days ago |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Jan
- Desktop-only; no headless server deployment mode
- Multi-user collaboration not supported
- Limited to llama.cpp-compatible model formats
Ollama
- No built-in chat UI; requires a separate front-end like Open-WebUI
- Fine-tuning and model training are not supported; inference only
- Multi-GPU distributed inference is limited compared to commercial inference APIs
- No built-in authentication, rate-limiting, or multi-tenant access control
Bottom line
Choose Jan if you want the lower-effort setup; choose Ollama for the larger community and ecosystem. Ollama has seen more recent development. Open each guide below for deploy steps and the full feature gap.
Jan
Offline-first, privacy-focused desktop app to run LLMs locally on any hardware