Container
Python with CUDA 12.0 - AI Workbench Default Container
1.0.9
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Python CUDA 12.0 - NVIDIA AI Workbench Default Container
NVIDIA AI Workbench provides a set of default base images, referred to as Base Environments in the application, that can be used as the starting point when creating the container for a new project.
This is a CUDA image with CUDA 12.0 and Python 3.10 and JupyterLab installed.
CHANGELOG
All notable changes to this image are documented here
[1.0.1] - 2023-10
- First draft of image, based on nvidia/cuda:12.0.0-runtime-ubuntu22.04
- Installed curl git git-lfs python3 gcc python3-dev python3-pip vim
- Installed Jupyterlab 4.0.7
[1.0.3] - 2023-12
- Re-built with updated base image
[1.0.4] - 2024-04
- Upgraded Jupyterlab to 4.1.2
- Disabled Jupyterlab announcement banner
[1.0.5] - 2024-08
- Re-built with updated base image
- Upgraded Jupyterlab to 4.2.4
[1.0.6] - 2025-02
- Re-built with updated base image
- Upgraded Jupyterlab to 4.2.5
[1.0.7] - 2025-04
- Re-built with updated base image
- Upgraded Jupyterlab to 4.3.5
[1.0.8] - 2025-07
- Re-built with updated base image
Shared Responsibility Model
NVIDIA AI Workbench employs a shared responsibility model. The subset of responsibilities related to base images are:
NVIDIA Responsibilities
- Updating base environment images with a newer tag in case a critical or high CVE is discovered.
- Providing prompt notifications in the case of updates via
- Notifications posted on the program DevZone site
- Email to the accounts registered in the Early Access program on DevZone
End User and Organization Responsibilities
- Following notifications from NVIDIA, ensuring the Default Base Images are updated to the latest versions to mitigate risks associated with vulnerabilities that might impact older images.
Open Source 3rd Party Notices
The 3rd party notices file can be found in the container at /NOTICES
Publisher
NVIDIA
Latest Tag1.0.9
UpdatedFebruary 25, 2026 UTC
Compressed Size2.4 GB
Multinode SupportNo
Multi-Arch SupportYes
System