Deep Learning VM release notes

Images with Nvidia 570 drivers have been deprecated as Nvidia officially stopped supporting these versions. You can use images with Nvidia 580 drivers instead.

M132 release

• Ubuntu 22.04 and Ubuntu 24.04 images with Nvidia 580 drivers and CUDA 12.9 stack are now available for Common and PyTorch 2.9 images.

M131 release

• Ubuntu 24.04 images with CUDA 12.8 and PyTorch 2.7 stack are now available for Common and PyTorch images.

M130 release

• Ubuntu 22.04 images with CUDA 12.8 and PyTorch 2.7 stack are now available for Common and PyTorch images.

The following framework versions have reached their end of patch and support dates:

• Base versions with CUDA 12.4 and earlier
• Tensorflow versions 2.17 and earlier
• PyTorch versions 2.3 and earlier

To view the end of patch and support dates, see Supported framework versions.

For more information on what the end of patch and support date means, see Support policy schedule.

If you must use an image after deprecation against Google security recommendations and at your own risk, see After deprecation.

M129 release

• Updated the Dataproc JupyterLab plugin to version 0.1.85.

M128 release

• Except for TensorFlow images, new images don't include conda. This change was made to improve size, performance, and vulnerability management. The existing image names and image family names now point to images and image families that don't include conda (for example: the image name common-cpu-v20250310-debian-11-py310 and corresponding image family name common-cpu-debian-11-py310).
• Images that include conda will be available until at least September 30, 2025. These images now have -conda appended to the name (for example: the image name common-cpu-v20250310-debian-11-py310-conda and corresponding image family name common-cpu-debian-11-py310-conda).
• All TensorFlow images and image families still include conda, but M128 image names and image family names have -conda appended. Specifying images or image families without -conda appended references older images, which also include conda.

M127 release

• Fixed an issue related to ownership of the home directory when using authorized ssh keys.

The following framework versions have reached their end of patch and support dates:

• Tensorflow versions 2.15 and earlier
• PyTorch versions 2.1 and earlier
• Base versions with CUDA 12.2 and earlier

To view the end of patch and support dates, see Supported framework versions. To create a VM instance using an image family that has reached its end of patch and support date, you must specify an image from the image family when you create the VM instance. To list images from an image family name after its end of patch and support date, include the --show-deprecated flag in your gcloud compute images list command, or select Show deprecated images when creating an instance in the Google Cloud console.

M126 release

• CUDA 12.4 VM images are now available.
• PyTorch 2.4.0 with CUDA 12.4 and Python 3.10 VM images are now available.
• Upgraded R from 4.4.1 to 4.4.2 for R VM images.

One or more framework versions have reached their end of patch and support dates. To view end of patch and support dates, see Supported framework versions. To create a VM instance using an image family that has reached its end of patch and support date, you must specify an image from the image family when you create the VM instance. To list images from an image family name after its end of patch and support date, include the --show-deprecated flag in your gcloud compute images list command, or select Show deprecated images when creating an instance in the Google Cloud console.

M125 release

• TensorFlow 2.17 VM images are now available.

M124 release

• Pytorch 2.3.0 with CUDA 12.1 and Python 3.10 VM images are now available.

M123 release

• TensorFlow 2.16 images are now available.

M122 release

• Updated Nvidia drivers to version 550.90.07 to fix vulnerabilities.

M121 release

• CUDA 12.2 images are now available.
• Updated TensorFlow 2.15 images from CUDA 12.1 to CUDA 12.2.
• Re-enabled common-gpu Deep Learning VM releases that were erroneously deactivated in M117.
• Updated Nvidia drivers to 550.54.15 to fix an issue where Nvidia drivers failed to install on startup after Debian 11 images upgraded kernel to linux-image-5.10.0-29-cloud-amd64.
• The linux-headers-cloud-amd64 metapackage is now installed for faster driver recompiling on kernel upgrades.
• TensorFlow 2.6 CPU and GPU images are deprecated. There will be no further updates to these images in future releases.

M120 release

• Upgraded TensorFlow 2.15 images to TensorFlow 2.15.1.
• Added Ubuntu 22.04 support for CPU images, and for GPU images using CUDA 12.1 or higher.

M119 release

• Fixed an issue wherein Dataproc extensions caused JupyterLab to crash when remote kernels weren't available.

M118 release

• Restored legacy gpu image families for TensorFlow 2.12 through 2.14, and for PyTorch 2.0.
• PyTorch 2.1.0 with CUDA 12.1 and Python 3.10 VM images are now available.
• PyTorch 2.2.0 with CUDA 12.1 and Python 3.10 VM images are now available.
• R images (Experimental) updated to R 4.3.3.
• Updated Nvidia drivers of older Deep Learning VM images to R535.

M117 release

• Added the CUDA version (CUDA 11.8) to the TensorFlow 2.12, 2.13, and 2.14 image names and image family names. For example, tf-2-12-gpu is renamed tf-2-12-cu118.

M116 release

• Added the CUDA version to the TensorFlow 2.15 image family name, for this release and future releases. For example, tf-2-15-gpu is renamed to tf-2-15-cu121.
• Deprecated the tf-2-15-gpu image family in favor of tf-2-15-cu121.

M115 release