Big-AGI vs Jan

Big-AGI

Its 'beam' runs one prompt across many models side-by-side to compare, with one-click self-host on Vercel or Docker.

• Beam compares many models at once
• One-click self-host on Vercel or Docker
• Connects to local engines (Ollama, LM Studio)
• Voice, image gen, web search, code exec

• Bring-your-own API keys required
• Single-maintainer project
• No managed hosting or support tier

Jan

Bundles its own model runner so it works offline out of the box — no account, no telemetry, and no paid tier.

• Local-first; data stays on your machine
• Open source (Apache-2.0), no paid tier
• Bundled model runner + model hub
• BYO cloud keys when wanted
• Local OpenAI-compatible server

• More setup friction than LM Studio
• Limited tool-calling vs full agent stacks
• Local model speed bound by your hardware
• Smaller ecosystem than Ollama

Pick Big-AGI if you need Sandboxed code execution, Speech synthesis (TTS), and Text-to-image.

• Sandboxed code execution (secondary capability)
• Speech synthesis (TTS) (secondary capability)
• Text-to-image (secondary capability)

Pick Jan if you need Tool / function calling and Model inference / serving.

• Tool / function calling (secondary capability)
• Model inference / serving (primary capability)