Analysis updated 2026-05-18
Find and compare open-source LLMs you can run locally without paying API fees.
Understand the research foundations of modern AI by reading landmark papers like 'Attention Is All You Need'.
Evaluate which AI provider or model to use for your product by reviewing leaderboards and model comparisons.
Learn how LLMs work through curated tutorials and courses for non-technical founders and developers.
| hannibal046/awesome-llm | airbnb/lottie-ios | bagisto/bagisto | |
|---|---|---|---|
| Stars | 26,742 | 26,736 | 26,733 |
| Language | — | Swift | PHP |
| Setup difficulty | easy | easy | moderate |
| Complexity | 1/5 | 2/5 | 3/5 |
| Audience | pm founder | developer | pm founder |
Figures from each repo's GitHub metadata at analysis time.
Awesome-LLM is a curated reading list and resource directory focused on Large Language Models (LLMs), the AI technology behind ChatGPT, Claude, Gemini, and similar tools. It's not software you install or run, it's more like a well-organized library catalog for anyone who wants to understand or work with AI language models. The collection covers the full landscape: landmark research papers that established how modern AI works (starting from the 2017 "Attention Is All You Need" paper that underpins nearly all current AI), tools for training and running your own AI models, public leaderboards comparing different models, tutorials and courses for learning, and curated lists of both open-source and commercial models you can use. For a non-technical founder or vibe coder, this is essentially the canonical "what's out there" reference for AI language technology. Want to know what DeepSeek, Qwen, or GPT are? Want to find a model you can run locally without paying API fees? Want to understand why everyone's talking about reasoning models? This list links to the key sources. It's particularly useful if you're making technology decisions, choosing which AI provider to use, understanding the competitive landscape, or trying to figure out what the research community is actually working on versus what's been productized. The list is community-maintained and updated regularly as the fast-moving AI field evolves.
A curated reading list and resource directory for Large Language Models, research papers, tools, models, and tutorials covering the full AI language technology landscape.
Released to the public domain. No attribution required.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly pm founder.
This repo across BitVibe Labs
Verify against the repo before relying on details.