In February 2024, I published awesome-local-llms, a list of tools for running LLMs locally. People shared it on r/LocalLLaMA and Medium, and it soon found an audience.
A Markdown list was fine at first, but keeping it current became a chore. You couldn’t sort or filter it, and it told you nothing about which projects were growing. I moved the data into Airtable for a while. That made the list easier to browse, but updates were still manual and I wasn’t storing the historical data needed to calculate trends.
So I built LLMRepos.com.
What it is
It tracks 10,000+ open-source LLM repositories and refreshes their data every day. I also widened the scope beyond local LLMs. It now includes the tools people use to build with open models:
- Inference engines - run models locally or in the cloud
- AI agents and coding agents - carry out tasks and write code
- RAG and retrieval tools - connect LLMs to your data
- Eval frameworks - test model and application behaviour
- AI developer tools - build, debug, and monitor LLM applications
For each project, you can see its stars, forks, contributors, primary language, and star growth over the past 7 and 30 days. The growth numbers are the useful bit. Total stars tend to favour older projects, while recent growth shows which repositories are getting attention now.
Why I rebuilt it
LLM tooling changes too quickly for a list that only records the current state. A popular framework can lose ground within months, but its total star count may hide that shift for much longer.
I use the dashboard to keep up with new projects and learn how other people are approaching inference, agents, retrieval, and evals. When I need a tool for one of my own projects, I can filter the list and compare repositories instead of starting with a broad GitHub search.
I wanted to filter projects by category and sort them by recent growth without maintaining another spreadsheet. More than anything, I wanted to see which repositories might be worth trying before their names appeared everywhere.
Who it’s for
I built it for anyone choosing an inference engine, agent framework, or other open-source LLM tool. It should also save some GitHub trawling if you just want to know what is picking up steam.
What’s next
Next on my list are better filters, dedicated category views, and more repositories. If I’ve missed a project you use, open an issue on the original repo.
You can try it at llmrepos.com.