JAX
A curated list of awesome libraries, projects, tutorials, and resources for the JAX machine learning ecosystem.
What is JAX?
Awesome JAX is a curated list of resources for the JAX machine learning ecosystem. It compiles libraries, models, tutorials, papers, and community links to help developers and researchers discover tools and learn how to use JAX effectively. The project addresses the challenge of navigating the fast-growing JAX landscape by providing a centralized, community-maintained directory.
Machine learning researchers, data scientists, and developers who are using or exploring JAX for high-performance computing, automatic differentiation, and accelerator-based (GPU/TPU) model training.
It saves time by aggregating and categorizing the best JAX resources in one place, is community-driven to ensure freshness, and provides a structured overview of the entire ecosystem, from core libraries to niche research tools.
Overview
JAX - A curated list of resources https://github.com/google/jax
Use Cases
Best For
- Finding JAX libraries for specific tasks like neural networks, optimization, or probabilistic programming
- Discovering research projects and model implementations built with JAX
- Learning JAX through curated tutorials, videos, and blog posts
- Staying updated with the latest JAX ecosystem developments and papers
- Identifying community resources like Discord channels and discussion forums
- Exploring domain-specific applications of JAX in fields like physics, biology, or reinforcement learning
Not Ideal For
- Teams seeking interactive, code-along tutorials with built-in execution environments
- Projects requiring detailed API documentation or direct support for specific JAX libraries
- Organizations needing vendor-backed tooling with guaranteed maintenance and SLAs
- Developers working primarily with other ML frameworks like PyTorch or TensorFlow who need cross-ecosystem comparisons
Pros & Cons
Pros
Aggregates over 100 libraries spanning neural networks (Flax, Haiku), optimization (Optax, JAXopt), and niche domains like physics and biology, as detailed in the extensive Libraries section.
Open to contributions with a 'New Libraries' section for emerging tools like Penzai and Optimistix, ensuring the list stays current with JAX's rapid evolution.
Organizes resources into clear categories like Libraries, Models, Tutorials, and Videos, making it easy to find specific types of content without sifting through clutter.
Described as a 'curated list' with community vetting, providing a quality-filtered hub that saves time compared to unorganized web searches.
Cons
Presented as a static markdown file without search, filtering, or quality ratings, requiring manual exploration and leaving users to assess each resource's relevance.
Relies on community updates, so some links may be outdated or broken, and listed projects range from well-established (Flax) to experimental with limited support.
Merely aggregates external tutorials and papers without providing step-by-step guidance or troubleshooting help, forcing users to navigate multiple sources independently.
Frequently Asked Questions
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