{"library":"jax-cuda12-plugin","type":"library","category":null,"description":"JAX is a Python library by Google for high-performance numerical computing, providing a NumPy-like interface with automatic differentiation and function transformations, capable of running on CPUs, GPUs, and TPUs. The `jax-cuda12-plugin` specifically provides NVIDIA GPU support for JAX, compatible with CUDA 12.x environments. JAX and its core library `jaxlib` (which this plugin extends) are actively maintained with frequent releases, typically on a monthly or bi-monthly schedule for minor versions.","language":"python","status":"active","version":"0.9.2","tags":["machine learning","gpu","cuda","array programming","automatic differentiation","numerical computing"],"last_verified":"Fri May 22","install":[{"cmd":"pip install jax-cuda12-plugin","imports":["import jax","import jax.numpy as jnp"]},{"cmd":"pip install -U --pre jax jaxlib \"jax-cuda12-plugin[with-cuda]\" jax-cuda12-pjrt -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html","imports":[]}],"homepage":"https://jax.readthedocs.io","github":"https://github.com/jax-ml/jax","docs":null,"changelog":null,"pypi":"https://pypi.org/project/jax-cuda12-plugin/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":34.8,"avg_import_s":2.34,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/jax-cuda12-plugin/compatibility"}}