Machine Learning & Scientific Python

JAX

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01 / Overview

What is JAX?

JAX combines array computation and automatic differentiation for numerical and machine-learning work.

Who is JAX for?

Teams evaluating JAX for machine learning & scientific python workflows, particularly array computation and automatic differentiation. Check the edition and intended deployment before selecting a package.

02 / Capabilities

JAX features

The core capabilities to consider for your workflow.

  • Array computation
  • Automatic differentiation
  • Accelerated numerical operations
03 / Plans & costs

JAX pricing

Plan availability

Open-source software

Review the software licence and distribution, then scope infrastructure, maintenance and support. Commercial hosting, proprietary extensions and managed services can be priced separately.

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Free access & evaluation

An open-source software edition is available. Check the exact licence and distribution; hosting, operation, support and separately licensed extensions may still cost money.

04 / Buying checklist

Before you choose JAX

  • Is the task numerical analysis, model training, experiment tracking, model serving or ongoing monitoring?

  • Which languages, hardware, model formats, deployment targets and operating costs must be supported?

05 / Related software

Explore related software

06 / Questions answered

JAX FAQs

Does JAX have a free plan?

An open-source software edition is available. Check the exact licence and distribution; hosting, operation, support and separately licensed extensions may still cost money.

Who is JAX for?

Teams evaluating JAX for machine learning & scientific python workflows, particularly array computation and automatic differentiation. Check the edition and intended deployment before selecting a package.

What should I compare before buying?

Check the tier that contains your essential features, confirm plan limits and compare the total quote with your own expected usage.