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About

​JAX is a Python library designed for high-performance numerical computing and machine learning research. It offers a NumPy-like API, facilitating seamless adoption for those familiar with NumPy. Key features of JAX include automatic differentiation, just-in-time compilation, vectorization, and parallelization, all optimized for execution on CPUs, GPUs, and TPUs. These capabilities enable efficient computation for complex mathematical functions and large-scale machine-learning models. JAX also integrates with various libraries within its ecosystem, such as Flax for neural networks and Optax for optimization tasks. Comprehensive documentation, including tutorials and user guides, is available to assist users in leveraging JAX's full potential. ​

About

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook Not Supported

Audience

Professional researchers and developers searching for a solution to manage their numerical computing and machine learning operations in Python

Audience

Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Supported
Live Online Not Supported
In Person Not Supported

Company Information

JAX
United States
docs.jax.dev/en/latest/

Company Information

PyTorch
Founded: 2016
pytorch.org

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Alternatives

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AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Categories

AI Development Supported
Machine Learning Supported
Neural Network Supported

Integrations

AWS EC2 Trn3 Instances Supported
Flower Supported
Gemma 3n Supported
IREN Cloud Supported
LiteRT Supported
Thunder Compute Supported
ApertureDB Not Supported
Cyfuture Cloud Not Supported
Gemma 3 Not Supported
Giskard Not Supported
Graphcore Not Supported
Horovod Not Supported
NVIDIA FLARE Not Supported
NVIDIA PhysicsNeMo Not Supported
NVIDIA TensorRT Not Supported
Sesterce Not Supported
SiMa Not Supported
TensorFlow Supported
Voyager SDK Not Supported
io.net Not Supported

Integrations

AWS EC2 Trn3 Instances Supported
Flower Supported
Gemma 3n Supported
IREN Cloud Supported
LiteRT Supported
Thunder Compute Supported
ApertureDB Supported
Cyfuture Cloud Supported
Gemma 3 Supported
Giskard Supported
Graphcore Supported
Horovod Supported
NVIDIA FLARE Supported
NVIDIA PhysicsNeMo Supported
NVIDIA TensorRT Supported
Sesterce Supported
SiMa Supported
TensorFlow Not Supported
Voyager SDK Supported
io.net Supported
Claim JAX and update features and information
Claim JAX and update features and information
Claim PyTorch and update features and information
Claim PyTorch and update features and information