PyTorch for Jetson Platform

This document describes the key features, software enhancements and improvements, and known issues regarding PyTorch on the Jetson platform. See Installing PyTorch for Jetson Platform for installation information.

Key Features and Enhancements

This release includes the following key features and enhancements.

As of the 23.11 release, NVIDIA optimized PyTorch docker containers will also support iGPU architectures, including some Jetson devices. For more information on the containers themselves, please refer to the PyTorch Container Release Notes.
Starting from 24.06 release, cusparselt support has been enabled for Jetson Platform.

Compatibility

Table 1. PyTorch compatibility with NVIDIA containers and Jetpack
PyTorch Version	NVIDIA Framework Container	NVIDIA Framework Wheel	JetPack Version
2.6.0a0+df5bbc0	24.12	-	6.1
2.6.0a0+df5bbc0	24.11	-	6.1
2.5.0a0+e000cf0ad9	24.10	-	6.1
2.5.0a0+b465a5843b	24.09	24.09	6.1
2.5.0a0+872d972e41	24.08	-	6.0
2.4.0a0+3bcc3cddb5	24.07	24.07	6.0
2.4.0a0+f70bd71a48	24.06	24.06	6.0
2.4.0a0+07cecf4168	24.05	24.05	6.0
2.3.0a0+6ddf5cf85e	24.04	24.04	6.0 Developer Preview
2.3.0a0+40ec155e58	24.03	24.03
2.3.0a0+ebedce2	24.02	24.02
2.2.0a0+81ea7a4	23.12, 24.01	23.12, 24.01
2.2.0a0+6a974bec	23.11	23.11
2.1.0a		23.06	5.1.x
2.0.0		23.05
2.0.0a0+fe05266f		23.04
2.0.0a0+8aa34602		23.03
1.14.0a0+44dac51c		23.02, 23.01
1.13.0a0+936e930		22.11	5.0.2
1.13.0a0+d0d6b1f		22.09, 22,10
1.13.0a0+08820cb	22.07	22.07
1.13.0a0+340c412	22.06	22.06	5.0.1
1.12.0a0+8a1a93a9	22.05	22.05	5.0
1.12.0a0+bd13bc66		22.04
1.12.0a0+2c916ef		22.03
1.11.0a0+bfe5ad28		22.01	4.6.1

Using PyTorch with the Jetson Platform

Storage: If you need more storage, we recommend connecting an external SSD via SATA on TX2 or Xavier devices, or USB on Jetson Nano.

Known Issues

TensorRT Model Optimizer is a new module but is not yet supported on Jetson due to its dependency on pytorch distributed functionality, which was disabled for Jetson.