Open source large-language-models projects
Every project in the registry tagged large-language-models, ranked by real GitHub adoption.
Visual builder for AI agents and RAG pipelines
[EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation
Open source LLM engineering platform for AI-powered applications
Build and run agents you can see, understand and trust.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with exp
Automated Penetration Testing Agentic Framework Powered by Large Language Models
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
The tensor database for AI data
SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.
Build reliable AI apps with comprehensive observability
Observal is self-hosted registry for your coding agent extensions with a built in insight engine. Setup Observal, define the scope and share your Skills, MCPs
The Ruby-native AI framework. Chats, agents, tools, images, audio, and video through one consistent API, in plain Ruby or Rails.
Optimizing inference proxy for LLMs
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
Get instant answers from your company knowledge
An open-source visual programming environment for battle-testing prompts to LLMs.
Serverless GPU compute with sub-second cold starts
Serverless LLM Serving for Everyone.
A NodeJS RAG framework to easily work with LLMs and embeddings
Deliver safe & effective language models
Related tags
Frequently asked questions
How many open source large-language-models projects are there?
This registry tracks 20 projects tagged large-language-models, with 376,065 GitHub stars between them. The most-adopted is Langflow at 156,266 stars.
Are these large-language-models projects free to use?
Yes — 19 of the 20 carry an explicit open-source licence across 3 distinct licences, so there is no licence fee. Where a project also sells a hosted or enterprise version, the self-hosted path remains free.
Which large-language-models project should I choose?
The list above is ranked by GitHub stars, but stars measure attention rather than fit. Check three things on each card: the licence (permissive versus copyleft), the language it is written in, and the last-push date — a high-star project that has not been pushed in a year is a liability.
Are these large-language-models projects still maintained?
16 of the 20 were pushed in the last 90 days, and every card shows its exact last-push date so you can see the rest. Sort your shortlist by that date before committing to a migration.