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suncloudsmoon awesome-open-source-ai

A curated list of useful open-source AI resources

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306

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17

Watchers: 306

Language

License: Creative Commons Zero v1.0 Universal

Repository Radar Score

27 / 100

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Score breakdown

  • popularity 42
  • growth 0
  • activity 15
  • freshness 100
  • community 18

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Awesome Open Source AI Awesome

Awesome Open Source AI is a curated list of useful open-source AI resources, including inference engines, LLMs, and tools. Specifically, this list aims to link to resources that meet the Open Source Initiative® (OSI) definition of open source as much as possible.

Table of Contents

Inference Engines

  • koboldcpp - Is the swiss army knife of LLM inference engines that supports multiple API endpoints such as Ollama.
  • llama.cpp - Barebones LLM inference engine with additional options to control LLM output beyond those of Ollama.
  • Ollama - Easy-to-use LLM inference engine offering an OpenAI-compatible API server.
  • OpenedAI Speech - Great OpenAI-compatible API TTS server that works with Piper TTS, which runs fast on the CPU.

Language Models

  • DeepSeek-R1 - Great language model that's suited for reasoning & logic related tasks.
  • Granite 3.1 - Great for RAG and suited for deployment on low-end consumer hardware.
  • InternVL 2.51 - Great language model for vision-related tasks and scores better on benchmarks compared to Qwen2-VL.
  • OLMo 2 - Completely open language model with all parts of the model training process open-source and scores well on benchmarks.
  • Phi-4 - Great language model that is SOTA in various benchmarks for a medium-sized language model that's great for instruction-following and logical tasks (Note: Phi models typically underform outside benchmarks).
  • Qwen 2.52 - Best in-class language models that excel in benchmarks for math, etc., but may have censorship on certain topics (i.e. Tiananmen Square).
  • Qwen 2.5 Coder3 - Best in-class language models that excel in coding related tasks.
  • Qwen 2.5-1M - Similar to Qwen 2.5 but supports a context length of up to 1M tokens, making it suitable for long-context tasks such as podcast generation.
  • Qwen2.5 VL4 - Great LLM that supports vision understanding (image & video) and is supported by llama.cpp.
  • SmolLM2 - A series of tiny language models that is great for tinkering around and summarizing content (not so great for finetuning).

Embedding Models

Image Models

Coming soon...

Audio Models

Text to Speech (TTS)

  • Kokoro v0.19 - Small TTS model that performs well given its small size (82M parameters).

Speech to Text (STT)

Coming soon...

Video Models

Coming soon...

Tools

Footnotes

  1. Only 1B and 38B models are open-source.

  2. The 3B and 72B models are not open-source.

  3. The 3B model is not open-source.

  4. Only 7B model is open-source.

Created: Dec 22, 2024

Last push: Jan 27, 2025

Default branch: master

Repository Radar analysis

Deterministic insights derived from public metadata and our observations — not personal testing or reviews.

Why this repository is interesting

  • Listed in our discovery index with public GitHub metadata for analysis.

Who should use it

  • Teams exploring AI tooling, agents, or ML infrastructure

Potential use cases

  • Prototype AI/agent workflows or study reference architectures

Strengths

  • README present in our index
  • Declared license: Creative Commons Zero v1.0 Universal

Limitations / considerations

  • Insights are derived from public metadata and our observations — not a substitute for code review

What to watch

  • Radar Score is modest — dig into activity and docs before committing

Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.

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