Open source alternatives to JAX

Open source alternatives to JAX, ranked by GitHub stars and freshness.

5 open-source alternatives in the index, ranked by GitHub stars and freshness.

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An Open Source Machine Learning Framework for Everyone

Best for: Teams building production ML systems that need cross-platform deployment and performance optimization

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Tensors and Dynamic neural networks in Python with strong GPU acceleration

Best for: ML researchers and engineers building custom neural network architectures with GPU training needs

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PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

Best for: Teams building large-scale production ML systems who need distributed training and cross-platform deployment out of the box

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OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.

Best for: Developers who need a high-performance, scalable deep learning framework and are comfortable with C++

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MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.

Best for: Developers seeking an open source deep learning framework for cross-platform deployment from edge to cloud