The self-hosted AI landscape in 2026 is dominated by two open-source projects that approach the same problem from different angles. AnythingLLM by Mintplex Labs (54,000+ stars, MIT licensed) aims to be a complete all-in-one AI platform — document ingestion, vector storage, RAG, agents, and team management in a single deployable package. Open WebUI (56,000+ stars, MIT licensed) focuses on being the best possible chat interface that connects to any backend, with a plugin architecture that makes it infinitely extensible.
Setup experience differs significantly. AnythingLLM offers a desktop app for Mac, Windows, and Linux that runs with zero configuration — download, launch, and start chatting. No Docker, no terminal, no API keys required for local model usage. It auto-downloads and configures Ollama models through its built-in model manager. Open WebUI requires Docker deployment (docker run -d -p 3000:8080 ghcr.io/open-webui/open-webui:main) and assumes you already have Ollama or another model server running. The trade-off: AnythingLLM is easier to start; Open WebUI is more flexible to configure.
RAG capabilities are AnythingLLM's defining strength. It handles the entire pipeline internally: drag-and-drop document ingestion for PDFs, Word files, text, and more; automatic text chunking with configurable overlap; built-in vector storage via LanceDB (or connect external Pinecone, Qdrant, ChromaDB); and retrieval-augmented generation that references your documents in conversations. Open WebUI added document upload and RAG support, but the implementation is less mature — it relies on external pipelines or its built-in simple RAG that works for basic use cases but lacks AnythingLLM's depth in chunking strategy and vector store flexibility.
The chat interface is where Open WebUI excels. It replicates the ChatGPT experience with remarkable fidelity: conversation history, model switching, message editing and regeneration, system prompts, keyboard shortcuts, and a clean responsive design that works on mobile. The interface supports markdown rendering, code highlighting, LaTeX, and artifact-like rich content display. AnythingLLM's chat UI is functional but more utilitarian — it prioritizes workspace-based organization (each workspace has its own documents and chat history) over conversational polish.
Model provider support is broadly equivalent. Both platforms connect to OpenAI, Anthropic, Google, Ollama, LM Studio, and dozens of other providers through OpenAI-compatible API endpoints. Open WebUI's model management interface is particularly well-designed, with a model library, one-click switching, and custom model configurations. AnythingLLM supports 30+ providers with a unified configuration panel and the ability to set different models per workspace — useful for teams where different use cases need different models.
AI agents and tool calling differ in architecture. AnythingLLM ships with built-in agents that can browse the web, execute code, search documents, and interact with external tools. The agent system includes an Agent Skills marketplace for extending capabilities. Open WebUI takes an extensibility-first approach with its Functions/Pipelines system — you can write custom Python functions that act as middleware, tools, or entire backends. This is more powerful for developers but requires coding, unlike AnythingLLM's ready-to-use agents.