jax-cuda13-plugin
JAX Plugin for NVIDIA GPUs
What it is and what it does
jax-cuda13-plugin is a platform-specific plugin that enables JAX to compile and execute numerical computations on NVIDIA GPUs using CUDA 13. It acts as a bridge between JAX's compiler infrastructure and NVIDIA's GPU hardware, allowing automatic differentiation, JIT compilation, and vectorization operations to run on GPUs for significant performance gains in machine learning and scientific computing workloads.
The plugin is tightly integrated with JAX's ecosystem and depends on jax-cuda13-pjrt for the underlying PJRT implementation. It is distributed as pre-compiled wheels for Linux systems (both x86_64 and aarch64 architectures) and supports Python 3.12, 3.13, and 3.14, including free-threaded variants. Installation requires CUDA 13 to be present on the system.
Use it for:
- Accelerate machine learning training on NVIDIA GPUs by enabling JAX's JIT compilation and automatic differentiation to target GPU hardware.
- Run numerical simulations and scientific computations that benefit from GPU parallelization through JAX's vmap and pmap transformations.
- Deploy JAX-based inference pipelines on GPU clusters for production machine learning systems.
- Develop and test GPU-accelerated JAX code on Linux systems with NVIDIA GPUs before scaling to multi-GPU environments.
Worth the install?
AI-flagged interpretation of the facts on this page — verify before relying
Provides NVIDIA GPU support for JAX by enabling CUDA 13 compilation and execution on compatible GPUs through the jax-cuda13-pjrt runtime.
Yes, if you are using JAX on Linux with an NVIDIA GPU and CUDA 13 installed. This plugin is essential for GPU acceleration and is actively maintained with no known vulnerabilities. Install friction is moderate but manageable for systems meeting the platform requirements. Not applicable on non-Linux systems or without compatible NVIDIA hardware.
Install
jax-cuda13-plugin on PyPI
pip
pip install jax-cuda13-pluginuv
uv add jax-cuda13-pluginpoetry
poetry add jax-cuda13-pluginInstalling jax-cuda13-plugin
Before you install
Medium install friction due to platform-specific wheels (x86_64 and aarch64 Linux only) and a single runtime dependency on jax-cuda13-pjrt. Actively maintained with recent releases and no known vulnerabilities.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most projects.
Quickstart
pip install jax-cuda13-plugin
import jax
import jax.numpy as jnp
# GPU acceleration is automatically available
x = jnp.ones((100, 100))
result = jax.jit(lambda a: a @ a)(x)
Requires NVIDIA CUDA 13 toolkit and compatible GPU; only available on Linux x86_64 and aarch64; requires Python 3.12 or later.
Verify before relying
- Whether this plugin is required separately or included in main JAX installations for GPU users
- Specific NVIDIA GPU models and driver versions supported by CUDA 13
- Performance characteristics compared to alternative JAX GPU backends
Package facts
| License | Apache-2.0 (permissive) |
| Python support | supports the current Python release (>=3.12) |
| Install friction | medium — platform-specific wheel |
| Runtime dependencies | 1 — jax-cuda13-pjrt |
| Maintenance | actively maintained — 29 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 420,823/month — #6,787 on PyPI (30-day window, as of 2026-08-14) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-14) |
Evidence: jax_cuda13_plugin-0.11.0-cp312-cp312-manylinux_2_27_aarch64.whl; jax_cuda13_plugin-0.11.0-cp312-cp312-manylinux_2_27_x86_64.whl; jax_cuda13_plugin-0.11.0-cp313-cp313-manylinux_2_27_aarch64.whl; jax_cuda13_plugin-0.11.0-cp313-cp313-manylinux_2_27_x86_64.whl; jax_cuda13_plugin-0.11.0-cp314-cp314-manylinux_2_27_aarch64.whl; jax_cuda13_plugin-0.11.0-cp314-cp314-manylinux_2_27_x86_64.whl; jax_cuda13_plugin-0.11.0-cp314-cp314t-manylinux_2_27_aarch64.whl; jax_cuda13_plugin-0.11.0-cp314-cp314t-manylinux_2_27_x86_64.whl
Tags
More Artificial Intelligence packages
LiteLLM provides a unified Python interface to…
permissive · top 100 on PyPI
huggingface-hubClient library and CLI tool for downloading,…
permissive · top 100 on PyPI
langchainLangChain provides a framework for building…
permissive · top 1,000 on PyPI
hf-xethf-xet provides chunk-based deduplication and…
permissive · top 1,000 on PyPI
tokenizersTokenizers converts raw text into token…
permissive · top 1,000 on PyPI
transformersTransformers provides a unified framework for…
permissive · top 1,000 on PyPI
jax-cuda12-pluginEnables JAX to run numerical computations and…
permissive · top 15,000 on PyPI
jax-cuda12-pjrtProvides NVIDIA GPU acceleration for JAX…
permissive · top 15,000 on PyPI
jax-cuda13-pjrtProvides NVIDIA GPU acceleration for JAX…
permissive · top 15,000 on PyPI
tokamaxTokamax provides custom accelerator kernels for…
permissive · top 15,000 on PyPI
augmaxAugmax is a JAX-based image data augmentation…
permissive · top 15,000 on PyPI
jaxlibjaxlib is the compiled XLA backend that enables…
permissive · top 5,000 on PyPI
jaxJAX is a Python library for automatic…
permissive · top 1,000 on PyPI
klujaxSolves sparse linear systems in JAX using the…
copyleft · top 15,000 on PyPI
jax-jumpyJax-jumpy provides a unified interface that…
permissive · top 15,000 on PyPI
blackjaxBlackJAX provides a collection of MCMC and…
permissive · top 15,000 on PyPI