AnythingLLM vs Vane
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
A self-hosted AI answering engine that searches the web and cites its sources.
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 Vane if you need…
- People who want AI-written answers with links to sources
- Users who prefer to run their own search setup instead of a hosted service
- People who want to use local models through Ollama
- Developers who want a self-hosted starting point for AI search
Side-by-side
| AnythingLLM | Vane | |
|---|---|---|
| Type | App | App |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 67.8k | 38k |
| Setup difficulty | Beginner | Intermediate |
| How you get it | Download the app | Run with Docker |
| Main language | JavaScript | TypeScript |
| Last code update | 6 days ago | 2 months 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.
Vane
Vane is an AI answering engine you run on your own machine. You ask a question, it searches the web through SearxNG and uses a language model you choose to write an answer with cited sources. It can use local models through Ollama or cloud providers such as OpenAI, Claude, and Groq.
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
Vane
- People who want AI-written answers with links to sources
- Users who prefer to run their own search setup instead of a hosted service
- People who want to use local models through Ollama
- Developers who want a self-hosted starting point for AI search
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
Vane
- Can run with local models so queries stay on your hardware
- Supports many AI providers and lets you mix models
- Includes a bundled SearxNG so setup can be a single Docker command
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
Vane
- People who want a zero-setup hosted service, since the README centers on running it yourself with Docker or Node.js
- Users who need features the README lists as coming soon, such as Tavily and Exa search support
- People without a model provider or local LLM, since Vane needs one to produce answers
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
Vane
- Answer quality depends on the model and provider you connect, and the README does not compare them
- Some listed features, such as Tavily and Exa support, are described as coming soon
- Connecting local models like Ollama can require network and firewall changes on Linux
Getting started
Vane
Run with Docker (includes SearxNG)
docker run -d -p 3000:3000 -v vane-data:/home/vane/data --name vane itzcrazykns1337/vane:latestClone the repository
git clone https://github.com/ItzCrazyKns/Vane.gitFrequently asked questions
What is the difference between AnythingLLM and Vane?
AnythingLLM: Private AI chat app for your documents, with agents, runs locally or with cloud models. Vane: A self-hosted AI answering engine that searches the web and cites its sources. AnythingLLM suits people who want a private chatgpt-style assistant over their own pdfs and text files, while Vane suits people who want ai-written answers with links to sources.
Are AnythingLLM and Vane free?
AnythingLLM: Free and open source. Vane: Free and open source.
Which is easier to set up, AnythingLLM or Vane?
AnythingLLM is easier to get started with (rated beginner); Vane is rated intermediate and usually needs more setup.
Is AnythingLLM or Vane more popular?
AnythingLLM has more GitHub stars (67.8k) than Vane (38k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to AnythingLLM and Vane?
Other options people compare them with include LlamaGPT, serviette, Paperclip, Octop, Hermes WebUI.
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.