AnythingLLM vs LibreChat
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
Private AI chat app for your documents, with agents, runs locally or with cloud models.
Open source · MIT
Self-hosted, open-source chat interface for many AI models, with agents, tools, and multi-user login.
The short answer
Choose AnythingLLM if you need…
- People who want a private ChatGPT-style assistant over their own PDFs and text files
- Teams that need several users with separate access on one instance (Docker version)
- Developers who want to try many LLM providers from one interface
- Anyone who wants to run local models on their own CPU or GPU without much setup
Choose LibreChat if you need…
- Teams that want one shared chat interface across several AI providers
- People who want to self-host a ChatGPT-style interface and keep their data on their own server
- Developers who want to connect custom OpenAI-compatible endpoints or local models
- Organizations that need multi-user login and role-based access
Side-by-side
| AnythingLLM | LibreChat | |
|---|---|---|
| Type | App | App |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 67.8k | 46.6k |
| Setup difficulty | Beginner | Intermediate |
| How you get it | Download the app | Clone and build from source |
| Main language | JavaScript | TypeScript |
| Last code update | 6 days ago | 4 days ago |
What each one is
AnythingLLM
AnythingLLM is an all-in-one AI application that lets you chat with your own documents and use AI agents. You can connect a local model that runs on your own computer or a cloud model from a provider such as OpenAI or Anthropic. The README says it includes built-in agents, multi-user support, vector databases, and document pipelines, and is available as a desktop app for Mac, Windows, and Linux.
LibreChat
LibreChat is a free, open-source web app that looks like ChatGPT but lets you connect to many AI providers, such as OpenAI, Anthropic (Claude), Google, Azure, and local models through compatible APIs. You run it on your own server, so conversations and accounts stay under your control. It also includes agents, tool integrations via MCP, file handling, and code execution.
Best for
AnythingLLM
- People who want a private ChatGPT-style assistant over their own PDFs and text files
- Teams that need several users with separate access on one instance (Docker version)
- Developers who want to try many LLM providers from one interface
- Anyone who wants to run local models on their own CPU or GPU without much setup
LibreChat
- Teams that want one shared chat interface across several AI providers
- People who want to self-host a ChatGPT-style interface and keep their data on their own server
- Developers who want to connect custom OpenAI-compatible endpoints or local models
- Organizations that need multi-user login and role-based access
Strengths
AnythingLLM
- Works with many LLM providers, both local and cloud, as listed in the README
- Desktop installers are provided for Mac, Windows, and Linux
- Released under the MIT license with a large community on GitHub
LibreChat
- Supports many AI providers and any OpenAI-compatible API in one interface
- Open source under the MIT license and self-hostable
- Has a large user base, with over 46,000 GitHub stars
Not ideal for
AnythingLLM
- People who only want a simple hosted chatbot and do not want to install or manage anything; a hosted instance exists but is a paid option
- Users needing multi-user permissions or the embeddable website widget, which the README marks as Docker version only
- Anyone expecting a guaranteed result from local models, since output quality depends on the model you choose
LibreChat
- People who just want to chat with AI and do not want to run a server; a hosted service is simpler
- Users with no hosting or Docker experience, since setup involves configuring a server and API keys
- Those who need features the README marks as experimental, such as attached code workspaces, to be stable
Trade-offs
AnythingLLM
- Several features, including multi-user support and the website widget, are limited to the Docker version
- The README is long and lists many options, so setup choices take some reading
- Local model performance depends on your hardware and the model you pick
LibreChat
- Self-hosting requires technical setup and ongoing maintenance
- Some newer features, such as attached workspaces, are labeled highly experimental
- The README is truncated here, so detailed install steps could not be verified from this excerpt
Getting started
LibreChat
Clone the repository
git clone https://github.com/LibreChat-AI/LibreChatFrequently asked questions
What is the difference between AnythingLLM and LibreChat?
AnythingLLM: Private AI chat app for your documents, with agents, runs locally or with cloud models. LibreChat: Self-hosted, open-source chat interface for many AI models, with agents, tools, and multi-user login. AnythingLLM suits people who want a private chatgpt-style assistant over their own pdfs and text files, while LibreChat suits teams that want one shared chat interface across several ai providers.
Are AnythingLLM and LibreChat free?
AnythingLLM: Free and open source. LibreChat: Free and open source.
Which is easier to set up, AnythingLLM or LibreChat?
AnythingLLM is easier to get started with (rated beginner); LibreChat is rated intermediate and usually needs more setup.
Is AnythingLLM or LibreChat more popular?
AnythingLLM has more GitHub stars (67.8k) than LibreChat (46.6k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to AnythingLLM and LibreChat?
Other options people compare them with include Vane, LlamaGPT, serviette, Paperclip, Octop.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.