AnythingLLM

RAG-first local LLM workspace with workspaces and agents.

Open SourceCPU-capableLocal or cloud

Actually FreeNo SignupOpen SourceWatermark-FreeHobbyist-FriendlyAPI

Visit AnythingLLMUpdated 2026-05-14 · Direct link

Hardware requirements

Local or cloud · Entry GPU (6–8 GB)

CPU-capable

Min VRAM

None

Rec. VRAM

12 GB

Min RAM

8 GB

Rec. RAM

16 GB

Disk

10 GB

GPU class

Entry GPU

Apple Silicon ✓CPU-CapableQuant: GGUF

Can run fully local (uses your Ollama / LM Studio) or fully remote.

Screenshot placeholder · AnythingLLM

What is AnythingLLM?

AnythingLLM treats RAG as the primary use case rather than a bolt-on. Documents go into 'workspaces'; each workspace has its own vector store, system prompt, and model. Supports local LLMs (Ollama, LM Studio, GGUF) and remote providers, agentic tool use, and a desktop app or self-hosted Docker deployment.

Pros & cons

Pros

RAG that's genuinely production-quality, not a demo
Workspace model fits team / project use cases naturally
Built-in agents with tool calling

Cons

Heavier setup than Jan / Msty
Some advanced features behind their paid cloud tier

What's actually free?

MIT (desktop + Docker). Mintplex Labs offers a paid cloud variant.

✓ Actually FreeNo SignupOpen SourceWatermark-Free

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