AnythingLLM vs Open Notebook
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, privacy-focused open-source alternative to Google's NotebookLM for research notes and AI chat.
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 Open Notebook if you need…
- People who want NotebookLM-style research tools without sending their material only to Google
- Users who want to choose or switch between several AI providers
- People comfortable running Docker on a personal computer or home server
- Anyone who wants to run AI models locally with Ollama
Side-by-side
| AnythingLLM | Open Notebook | |
|---|---|---|
| Type | App | App |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 67.8k | 41.3k |
| Setup difficulty | Beginner | Intermediate |
| How you get it | Download the app | Run with Docker |
| 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.
Open Notebook
Open Notebook is a self-hosted app for organizing research material such as PDFs, videos, audio, and web pages into notebooks, then searching and chatting with an AI about that content. It is an open-source take on Google's NotebookLM. You connect your own AI provider, such as OpenAI, Anthropic, Google, or a local model through Ollama, so you control where your data and API calls go.
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
Open Notebook
- People who want NotebookLM-style research tools without sending their material only to Google
- Users who want to choose or switch between several AI providers
- People comfortable running Docker on a personal computer or home server
- Anyone who wants to run AI models locally with Ollama
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
Open Notebook
- Self-hosted, so your research stays on hardware you control
- Supports many AI providers and any OpenAI-compatible server, per the README
- MIT licensed, so the code can be inspected, modified, and reused
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
Open Notebook
- People who want a zero-setup hosted service, since the README describes running it yourself with Docker Compose
- Users who are not comfortable managing an API key or a local model server
- Anyone exposing the app to a shared network without changing the default port settings and adding a password, since the README says there is no password by default
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
Open Notebook
- Requires Docker and a separately obtained AI provider key or local model server
- The README's default setup has no password and publishes ports on all network interfaces unless changed
- Quality and cost depend on the AI provider you choose, which the README does not evaluate
Getting started
Open Notebook
Create a folder and download docker-compose.yml
mkdir open-notebook && cd open-notebookDownload the official compose file
curl -o docker-compose.yml https://raw.githubusercontent.com/lfnovo/open-notebook/main/docker-compose.ymlFrequently asked questions
What is the difference between AnythingLLM and Open Notebook?
AnythingLLM: Private AI chat app for your documents, with agents, runs locally or with cloud models. Open Notebook: Self-hosted, privacy-focused open-source alternative to Google's NotebookLM for research notes and AI chat. AnythingLLM suits people who want a private chatgpt-style assistant over their own pdfs and text files, while Open Notebook suits people who want notebooklm-style research tools without sending their material only to google.
Are AnythingLLM and Open Notebook free?
AnythingLLM: Free and open source. Open Notebook: Free and open source.
Which is easier to set up, AnythingLLM or Open Notebook?
AnythingLLM is easier to get started with (rated beginner); Open Notebook is rated intermediate and usually needs more setup.
Is AnythingLLM or Open Notebook more popular?
AnythingLLM has more GitHub stars (67.8k) than Open Notebook (41.3k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to AnythingLLM and Open Notebook?
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.