Browse free open source Generative AI and projects for Mac and ChromeOS below. Use the toggles on the left to filter open source Generative AI by OS, license, language, programming language, and project status.

  • Gemini 3 and 200+ AI Models on One Platform Icon
    Gemini 3 and 200+ AI Models on One Platform

    Access Google's best plus Claude, Llama, and Gemma. Fine-tune and deploy from one console.

    Build generative AI apps with Vertex AI. Switch between models without switching platforms.
    Start Free
  • AI-generated apps that pass security review Icon
    AI-generated apps that pass security review

    Stop waiting on engineering. Build production-ready internal tools with AI—on your company data, in your cloud.

    Retool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
    Try Retool free
  • 1
    llama.cpp

    llama.cpp

    Port of Facebook's LLaMA model in C/C++

    The llama.cpp project enables the inference of Meta's LLaMA model (and other models) in pure C/C++ without requiring a Python runtime. It is designed for efficient and fast model execution, offering easy integration for applications needing LLM-based capabilities. The repository focuses on providing a highly optimized and portable implementation for running large language models directly within C/C++ environments.
    Downloads: 109 This Week
    Last Update:
    See Project
  • 2
    GPT-NeoX

    GPT-NeoX

    Implementation of model parallel autoregressive transformers on GPUs

    This repository records EleutherAI's library for training large-scale language models on GPUs. Our current framework is based on NVIDIA's Megatron Language Model and has been augmented with techniques from DeepSpeed as well as some novel optimizations. We aim to make this repo a centralized and accessible place to gather techniques for training large-scale autoregressive language models, and accelerate research into large-scale training. For those looking for a TPU-centric codebase, we recommend Mesh Transformer JAX. If you are not looking to train models with billions of parameters from scratch, this is likely the wrong library to use. For generic inference needs, we recommend you use the Hugging Face transformers library instead which supports GPT-NeoX models.
    Downloads: 1 This Week
    Last Update:
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