LibreChat vs Open WebUI
LibreChat
librechat.aiOpen WebUI
openwebui.comSide by side
| Figure | LibreChat | Open WebUI |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Byok System | 8.5 (#6) | 8.2 (#12) |
| Spec score · AI chatbots and assistants | 8.6 (#22) | 8.7 (#16) |
| Audience | The project describes itself as built for developers, teams, and enterprises that need control. | The enterprise page describes Open WebUI as designed for organizations from startups to Fortune 500 companies and offers enterprise licensing to registered entities and organizations. |
| File uploads | Yes | Yes |
| Free plan | Yes | Yes |
| Image generation | Yes | Yes |
| Integrations | LibreChat supports Model Context Protocol for connecting AI models to external tools and services. | Yes |
| Mobile apps | No | Yes |
| Product | LibreChat is a free, open-source AI platform that combines language models from major providers in one customizable interface. | Open WebUI is a self-hosted AI interface for local and cloud models, built to run entirely offline. |
| Setup | The documentation says the Docker quick start takes about five minutes and also lists npm, Helm Chart, and remote hosting guides. | The docs provide Docker, pip, uv, and desktop installation options, and recommend Docker or Python for production deployments. |
| Support | The project directs users to GitHub Discussions and Discord for questions and community help. | Enterprise support can include a dedicated account manager, core-engineer office hours, dedicated support channels, and consulting; the page says guidance is provided rather than implementation services. |
| Team workspace | Yes | Yes |
| Web search | Yes | Yes |
Plans
In their own words
Open WebUI
Open WebUI is a self-hosted interface for local and cloud AI models, designed to run entirely offline. It connects to Ollama and OpenAI-compatible APIs. Installation options include Docker, pip, uv, and desktop setup; the documentation recommends Docker or Python for production deployments. Listed capabilities include voice, vision, retrieval, generation, search, Python extensions, file uploads, image generation, app integrations, and team workspaces. Its extension system supports Filters, Actions, Pipes, Tools, and Skills, and can connect through MCP, MCPO, and OpenAPI tool servers. Knowledge retrieval includes local RAG with nine vector databases, multiple content-extraction engines, hybrid search, reranking, and full-context mode. Organizations can deploy it on-premises, in a private cloud, or in an air-gapped environment. The operator configures where chats and other data are stored; data can be routed externally when external providers, tools, model endpoints, or integrations are configured. The software is free to use as-is with original branding intact. Deployments with more than 50 users must keep Open WebUI branding visible unless an exception applies.