Sept. 11, 2025 — NVIDIA announced the CUDA software stack is being deployed across various operating systems and package managers. The company said it is working with its ecosystem of distribution platforms to allow redistribution of CUDA, including OS providers Canonical, CIQ, and SUSE, and developer environment manager Flox—which enables package manager Nix—will redistribute CUDA software directly.
The company said they can now embed CUDA into their package feeds, which will simplify installation and dependency resolution. “It’s particularly beneficial for incorporating GPU support into complex applications like PyTorch and libraries like OpenCV,” NVIDIA said.
Building and deploying applications can be challenging for developers, requiring them to navigate the complex relationship between hardware and software capabilities and compatibility, according to NVIDIA. “Ensuring that each underlying software component is not only installed correctly but also matches the required versions to avoid conflicts can be a time-consuming task, and often leads to deployment delays and operational inefficiencies in application workflows.”
This effort augments existing ways developers have CUDA access by letting them obtain the software needed in one location. Additional distributors are coming soon.
Each distribution platform that redistributes CUDA will include:
-
Consistent CUDA Toolkit naming: Third-party packages will match NVIDIA naming conventions to avoid confusion in documentation and tutorials.
-
Timely CUDA updates: Third-party packages will be updated in a timely manner after NVIDIA official releases to ensure compatibility and reduce QA overhead.
-
Continued free access: CUDA itself will remain freely available—even when packaged in paid software. Distributors may charge for access to their packages or software but will not monetize CUDA specifically.
-
Comprehensive support options: You can access support via distributors and can also find help via NVIDIA forums or NVIDIA’s developer site, just like always.
Obtaining CUDA software from NVIDIA is free, and current avenues to get CUDA remain (they include downloading the CUDA Toolkit, pulling the CUDA container, installing for Python using pip or conda).
“But the ability for distribution platforms to package CUDA within larger enterprise deployments and software applications allows us to ensure your experience as a developer is simple. You download and install your application, and under the covers, the correct CUDA version is installed, as well,” the company said in a blog by NVIDIA’s Jonathan Bentz, Rob Armstrong and Anshuman Bhat. “Working with the NVIDIA ecosystem in this way is a significant milestone in our mission to reduce friction in GPU software deployment. By collaborating with key players across the OS and package management landscape, NVIDIA is ensuring that CUDA remains accessible, consistent, and easy to use—no matter where or how developers choose to build.”
