Orbax: Distributed Checkpointing with JAX
In a landscape of high-performance distributed ML systems, JAX has emerged as a framework of choice. However, JAX's modular design philosophy leaves it without a standardized checkpointing solution. In this paper, we introduce Orbax, a modular, JAX-native checkpointing library that abstracts the complexities of distributed accelerator systems while also providing flexibility for user-friendly checkpoint manipulations throughout the ML model lifecycle. We demonstrate performance exceeding comparable PyTorch competitors by up to 3.5$\times$ for saving and 2$\times$ for loading. The library is available at https://github.com/google/orbax.
| Authors | Colin Gaffney, Shutong Li, Daniel Ng et al. |
|---|---|
| Primary category | cs.DC |
| Published | 21 May 2026 |
| Last updated at source | 26 May 2026 |
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