CUDA DL Release 25.04

The NVIDIA container image for PyTorch, release 25.04, is available on NGC.

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Contents of the PyTorch container

This container image contains the complete source of the version of PyTorch in /opt/pytorch. It is prebuilt and installed in the default Python environment (/usr/local/lib/python3.10/dist-packages/torch) in the container image.

The container also includes the following:

• Ubuntu 24.04 including Python 3.12
• NVIDIA CUDA 12.9.0
• NVIDIA cuBLAS 12.9.0.2
• NVIDIA cuDNN 9.9.0.52
• NVIDIA NCCL 2.26.3
• rdma-core 50.0
• NVIDIA HPC-X 2.21
• GDRCopy 2.4.1
• TensorBoard 2.16.2
• Nsight Compute 2025.2.0.11
• Nsight Systems 2025.2.1.130
• NVIDIA TensorRT™ 10.9.0.34

Driver Requirements

Release 25.04 is based on CUDA 12.9.0 which requires NVIDIA Driver release 575 or later. However, if you are running on a data center GPU (for example, T4 or any other data center GPU), you can use NVIDIA driver release 470.57 (or later R470), 525.85 (or later R525), 535.86 (or later R535), or 545.23 (or later R545).

The CUDA driver's compatibility package only supports particular drivers. Thus, users should upgrade from all R418, R440, R450, R460, R510, R520, R530, R545, R555 and R560 drivers, which are not forward-compatible with CUDA 12.9. For a complete list of supported drivers, see the CUDA Application Compatibility topic. For more information, see CUDA Compatibility and Upgrades.

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Key Features and Enhancements

This CUDA DL release includes the following key features and enhancements.

• CUDA DL container image is based on Ubuntu 24.04.

Announcements

• Starting with the 25.03 release, NVIDIA provides two CUDA DL images: Developer and Runtime

Known Issues

• None.