What is the difference between Open WebUI, AnythingLLM and LibreChat?

All three are open-source, Docker-deployable chat front ends that connect to Ollama, vLLM, LM Studio and any OpenAI-compatible or cloud API. They differ in center of gravity. Open WebUI (v0.11.x as of September 2026) is the feature-richest ChatGPT-style all-rounder with the largest plugin ecosystem. AnythingLLM (v1.16.x) is RAG-first — workspaces of documents you chat with, plus a desktop app and no-code agent builder. LibreChat (v0.8.x, Node/React) is the most multi-provider, team-oriented UI with an agents framework, MCP support and a sandboxed code interpreter.

Which self-hosted chat UI is best for chatting with my own documents?

AnythingLLM. It was built around retrieval-augmented generation: drag-and-drop PDFs, DOCX, XLSX, PPTX and 50+ code formats into isolated workspaces, pull from GitHub repos, YouTube transcripts and Confluence, and choose a vector store from built-in LanceDB, Chroma, Milvus, Pinecone, Qdrant, Weaviate or pgvector. Open WebUI has a solid built-in knowledge-base RAG that is fine for most home and small-team use; LibreChat's RAG API works but is the least central of the three.

Is Open WebUI still open source after its license change?

Yes, with one condition. From v0.6.6 (2025) Open WebUI moved off pure MIT to its own license that adds a branding-protection clause: deployments with more than 50 users (aggregate) must keep Open WebUI branding unless they hold an enterprise license; self-hosted internal deployments with 50 or fewer users may fully rebrand. Anyone can fork from v0.6.5 under the original permissive terms. AnythingLLM and LibreChat remain under MIT-style licenses as of September 2026.

Which is best for a team or company deployment in 2026?

LibreChat or Open WebUI, depending on priorities. LibreChat is designed as a shared team UI across many providers with agents, MCP tools, an agent marketplace, shared conversations and search, and its 2026 roadmap adds a GUI admin panel for roles and groups. Open WebUI has mature multi-user roles, SSO options and the biggest community, but branding rules apply above 50 users. AnythingLLM's multi-user mode works at the workspace level but its enterprise auth and admin controls are the least mature of the three.

Quick Answer

Open WebUI vs AnythingLLM vs LibreChat 2026: Which UI?

Published: September 14, 2026

The short answer

If you run local or API-backed models and want a ChatGPT-like interface you control, these are the three projects worth evaluating in 2026:

	Open WebUI	AnythingLLM	LibreChat
Current line (Sep 2026)	v0.11.x (v0.11.1 in late August 2026)	v1.16.x (v1.16.1, August 27, 2026)	v0.8.x (v0.8.8 release candidates, August–September 2026)
Stack	Python (FastAPI) + Svelte	Node.js + React; Electron desktop app	Node.js + React; MongoDB
Maintainer	Open WebUI, Inc. (small independent team)	Mintplex Labs	Danny Avila + community
License	Open WebUI License (branding clause for 50+ users)	MIT	MIT
Center of gravity	Feature-rich all-rounder, plugins (“Pipelines”, tools, filters)	RAG workspaces + on-device desktop assistant	Multi-provider team chat + agents + code interpreter
RAG	Built-in knowledge bases, per-chat uploads, web search	Best-in-class: workspaces, 50+ file types, 7 vector DBs, connectors	RAG API for file chat; least central
Agents / tools	Tools, function calling, Pipelines, MCP, community plugin registry	No-code agent builder, agent skills, MCP with per-sub-skill tool control	Agents framework, MCP, marketplace, sandboxed code interpreter, OpenAPI actions
Multi-user	Mature roles (admin/user/pending), groups, SSO options	Workspace-level permissions; simpler admin	Team-first: shared convos, search, roles; GUI admin panel on 2026 roadmap
Desktop / mobile	PWA; community-built native mobile client	Native desktop app (macOS/Windows/Linux) with system-wide “Magic” features; Telegram bot	Web app; PWA
Best for	Households, home labs, small teams wanting everything in one box	Individuals and teams whose main job is chatting with documents	Teams that want one polished UI across OpenAI, Anthropic, Google, Azure, Bedrock and local models

Pick Open WebUI as the default if you have no strong constraint. Pick AnythingLLM if documents are the point or you want a desktop app that also works offline. Pick LibreChat if you are standing up a shared, multi-provider chat for a team and want agents and a code sandbox without plugins.

Open WebUI: the all-rounder with the biggest ecosystem

Open WebUI is the most-installed self-hosted LLM UI and the closest thing to a drop-in ChatGPT replacement. It talks to Ollama natively and to anything OpenAI-compatible (vLLM, LM Studio, llama.cpp, LiteLLM, cloud APIs). What sets it apart in 2026:

Plugin depth. “Pipelines” and the tools/filters framework let the community ship live-charting visualizers, approval gates that hold every tool call until you confirm, task-list planners, 3D model viewers and more; the August 25, 2026 community newsletter reviewed five of them, each tested on a live instance.
Knowledge bases. Upload PDFs, Word files and web pages per chat or into persistent collections; hybrid search and reranking are built in.
Multi-user administration. Roles, groups, per-model permissions, and a clean onboarding flow for shared servers.
Mobile. Installable as a PWA; the community has also built a native mobile client.

Watch-outs: the license. Since v0.6.6, deployments above 50 users must keep Open WebUI branding unless they license it; ≤50-user internal deployments may rebrand freely, and v0.6.5 remains forkable under the original terms. Some plugins also need the iframe Sandbox Allow Same Origin permission, which widens the trust boundary — read each plugin’s note.

AnythingLLM: RAG workspaces, plus a desktop assistant

AnythingLLM’s design principle is the workspace: an isolated container of documents with its own system prompt, model and vector store, that you chat with. It ingests PDF, DOCX, TXT, MD, CSV, XLSX, PPTX and 50+ code formats, and pulls from GitHub, GitLab, YouTube transcripts, Confluence and scraped web pages. Vector stores include built-in LanceDB, Chroma, Milvus, Pinecone, Qdrant, Weaviate and pgvector. Model providers span Ollama, LM Studio, OpenAI, Anthropic, Azure, Bedrock, Gemini, Cerebras and AMD’s Lemonade runtime, with mid-conversation switching.

2026 additions worth knowing:

Desktop app as an OS-wide agent (v1.15): “Magic” features — dictation, highlight-and-ask, autocomplete — run inside any app on-device; an optional AnythingLLM Pro subscription lifts daily limits while every feature keeps a free tier.
v1.16 line: image generation via /img, whole-folder uploads, toggling tools mid-session, a collapsible chain-of-thought/activity block for long agentic tasks, embedded Microsoft Foundry Local inference (v1.16.1).
Telegram bot and a no-code agent builder with granular MCP sub-skill control.

Watch-outs: security patching is on you. Mintplex fixed a critical XSS-to-RCE issue (CVE-2026-32626) affecting v1.11.1 and earlier and a 2025 cross-prompt-injection flaw; keep Docker images current. Admin and enterprise-auth controls are the thinnest of the three.

LibreChat: the team UI across every provider

LibreChat describes itself as an “enhanced ChatGPT clone” and the description is accurate: one interface, every provider — OpenAI (including the Responses API and GPT-6 Astra), Anthropic, Google/Vertex, Azure, AWS Bedrock, Groq, Mistral, OpenRouter, DeepSeek, plus Ollama and custom endpoints. Its strengths:

Agents framework. No-code custom assistants, an in-app agent marketplace, MCP tool integrations, OpenAPI actions, and a sandboxed code interpreter with file upload/download across languages.
Team features. Secure multi-user auth, shared conversations, full-text message search, presets, multilingual UI.
2026 roadmap (published February 18, 2026): a v1 GUI Admin Panel for roles, groups and access control instead of editing librechat.yaml; resumable chats; dynamic context; multimodal (video) understanding; image generation and editing; user memories.

Watch-outs: RAG is functional but not the focus; the v0.8.8 line was still in release candidates as of early September 2026; MongoDB is a required dependency; Azure-hosted GPT-6 Astra tool calls need the Responses API enabled manually (open issue, September 2026).

Decision guide by scenario

Scenario	Pick	Why
Home lab on Ollama, one or two users	Open WebUI	Fastest setup, most features, PWA on the phone
”Chat with my contracts / research papers”	AnythingLLM	Purpose-built RAG workspaces and connectors
Offline laptop assistant with local models	AnythingLLM desktop	Native app, on-device Magic features, Foundry Local embedded
20-person team, mixed OpenAI + Claude + local	LibreChat	Multi-provider, shared convos, agents, code sandbox
200-person company, SSO, rebranded portal	Open WebUI with enterprise license, or LibreChat	Open WebUI needs a license above 50 users to rebrand; LibreChat is MIT
Heavy tool/plugin experimentation	Open WebUI	Largest community plugin registry

Setup notes common to all three

All three ship Docker Compose files; a single VPS with 4 GB RAM runs any of them if inference is elsewhere.
Put them behind a reverse proxy with TLS and enable multi-user auth before exposing to the internet — every one of them has had at least one serious CVE.
Point them at one inference backend (Ollama for simplicity, vLLM for throughput) and add cloud keys per provider; the UI is not where your model choice lives.

Last verified: September 14, 2026. Version lines change monthly — check each project’s releases page before deploying.