JAX
docs.jax.dev
Spec sheet
- What it does
- JAX is a Python library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and large-scale machine learning.Read 11 Oct 2026 · docs.jax.dev
- Platforms
- The installation guide lists CPU support for Linux, macOS and Windows, with accelerator support varying by operating system and hardware.Read 11 Oct 2026 · docs.jax.dev
- Integrations
- The documentation lists ecosystem libraries including Flax, Keras, Optax, TensorFlow Datasets, Hugging Face Datasets, NumPyro, and PyMC.Read 11 Oct 2026 · docs.jax.dev
- Security
- Distributed coordination connections are neither encrypted nor authenticated by default; the documentation describes optional mutual TLS for securing them.Read 11 Oct 2026 · docs.jax.dev
- Support
- The installation guide directs users with problems using prebuilt wheels to the JAX GitHub issue tracker.Read 11 Oct 2026 · docs.jax.dev
- Accelerator support
- The project describes its core library as focused on machine learning and numerical computing, with a modular backend stack for targeting different accelerators.Read 11 Oct 2026 · github.com
- Contributors
- The project says it welcomes open-source contributions and frequently receives contributions from Google DeepMind, Alphabet, NVIDIA and others.Read 11 Oct 2026 · github.com
- Development
- JAX development takes place in the open on GitHub through pull requests, the issue tracker, discussions and JAX Enhancement Proposals.Read 11 Oct 2026 · github.com
- Ecosystem
- The documentation lists ecosystem tools including Flax, Keras, Optax, TensorFlow Datasets, Hugging Face Datasets and NumPyro.Read 11 Oct 2026 · docs.jax.dev
- Hardware
- The same code can execute on multiple backends, including CPU, GPU, and TPU.Read 11 Oct 2026 · docs.jax.dev
- Installation
- JAX uses the `jax` Python package and `jaxlib`, which contains compiled binaries with different builds for operating systems and accelerators.Read 11 Oct 2026 · docs.jax.dev
- Numerical behavior
- The FAQ explains that XLA optimizations can cause JIT-compiled computations to produce numerically different results from eager computations.Read 11 Oct 2026 · docs.jax.dev
- NumPy-style API
- JAX provides a familiar NumPy-style API for researchers and engineers.Read 11 Oct 2026 · docs.jax.dev
- Open development
- JAX development takes place in the open on GitHub, where the project uses pull requests, an issue tracker, discussions, and JAX Enhancement Proposals.Read 11 Oct 2026 · docs.jax.dev
- Platform limits
- The installation guide labels Windows x86_64 CPU support experimental and Apple GPU support on Apple ARM experimental.Read 11 Oct 2026 · docs.jax.dev
- Scope
- The JAX project says the core library is narrowly scoped around efficient array operations and program transformations, with an evolving surrounding ecosystem.Read 11 Oct 2026 · docs.jax.dev
- Security limits
- The documentation says CPU and non-NVLink GPU collectives, and the JAX profiler server connection, are plaintext and unauthenticated.Read 11 Oct 2026 · docs.jax.dev
- Transformations
- JAX includes composable transformations for compilation, batching, automatic differentiation, and parallelization.Read 11 Oct 2026 · docs.jax.dev
- Who it is for
- The project describes its core library as focused on the fundamentals of machine learning and numerical computing at scale.Read 11 Oct 2026 · docs.jax.dev
Plans and prices
JAX Free Open-source Python library; installation requires the `jax` package and platform-specific `jaxlib` binaries Read 11 Oct 2026 · github.com
Where Specifiction places it
- Deep Learning Software#7 of 358.3