hannibal046/awesome-llm

★ 26,822Audience · pm founderComplexity · 1/5QuietLicenseSetup · easy

Mindmap

mindmap
  root((awesome-llm))
    What it covers
      Landmark papers
      Training tools
      Model leaderboards
      Tutorials and courses
    Resource types
      Open-source models
      Commercial models
      Research papers
      Learning guides
    Use cases
      Understand AI tech
      Choose AI providers
      Run models locally
      Track research trends
    Audience
      Founders
      Vibe coders
      Researchers
      Decision makers

mindmap root((awesome-llm)) What it covers Landmark papers Training tools Model leaderboards Tutorials and courses Resource types Open-source models Commercial models Research papers Learning guides Use cases Understand AI tech Choose AI providers Run models locally Track research trends Audience Founders Vibe coders Researchers Decision makers

Things people build with this

USE CASE 1

Find and compare open-source LLMs you can run locally without paying API fees.

USE CASE 2

Understand the research foundations of modern AI by reading landmark papers like 'Attention Is All You Need'.

USE CASE 3

Evaluate which AI provider or model to use for your product by reviewing leaderboards and model comparisons.

USE CASE 4

Learn how LLMs work through curated tutorials and courses for non-technical founders and developers.

Getting it running

Difficulty · easy Time to first run · 5min

Released to the public domain. No attribution required.

In plain English

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.

Copy-paste prompts

Prompt 1

I want to run an LLM locally on my machine without API costs, what models does awesome-llm recommend and where do I find them?

Prompt 2

Show me the landmark research papers in awesome-llm that explain how modern AI language models actually work.

Prompt 3

Which open-source LLMs are currently ranked highest on the leaderboards listed in awesome-llm?

Prompt 4

I need to choose between different AI providers for my startup, what comparison resources does awesome-llm have?

Prompt 5

What are the best beginner-friendly tutorials and courses in awesome-llm for learning about LLMs?

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