AnythingLLM vs Big-AGI

AnythingLLM

Same private RAG workspace runs either as a one-click desktop app or a Docker server — solo or multi-user team.

• MIT open source
• One-click desktop or Docker deploy
• 40+ LLM providers + local models
• Built-in RAG, agents, multi-user workspaces

• RAG quality depends on your setup
• Self-host requires ops effort
• Fewer integrations than enterprise suites
• Hosted tier is paid

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

Pick AnythingLLM if you need Web scraping, Tool / function calling, RAG pipeline, Chat with documents, and 1 more.

• Web scraping (secondary capability)
• Tool / function calling (secondary capability)
• RAG pipeline (primary capability)
• Chat with documents (primary capability)
• Text-to-SQL (secondary capability)

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

• Sandboxed code execution (secondary capability)
• Multi-model access (primary capability)
• Speech synthesis (TTS) (secondary capability)
• Text-to-image (secondary capability)