Red Hat to distribute NVIDIA CUDA across Red Hat AI, RHEL and OpenShift

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2025-10-28 ~1 min read www.redhat.com #kubernetes

⚡ TL;DR

Red Hat to distribute NVIDIA CUDA across Red Hat AI, RHEL and OpenShift Why this matters: Simplicity and consistency Our open source approach to AI About the author Ryan King More like this Blog post Blog post Original podcast Original podcast Keep exploring Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share For decades, Red Hat has been focused on providing the foundation for enterprise technology — a flexible, more consistent, and open platform. Today, as AI moves from a science experiment to a core business driver, that mission is more critical than ever.

📝 Summary

Red Hat to distribute NVIDIA CUDA across Red Hat AI, RHEL and OpenShift Why this matters: Simplicity and consistency Our open source approach to AI About the author Ryan King More like this Blog post Blog post Original podcast Original podcast Keep exploring Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share For decades, Red Hat has been focused on providing the foundation for enterprise technology — a flexible, more consistent, and open platform. Today, as AI moves from a science experiment to a core business driver, that mission is more critical than ever. The challenge isn't just about building AI models and AI-enabled applications; it’s about making sure the underlying infrastructure is ready to support them at scale, from the datacenter to the edge. This is why I'm so enthusiastic about the collaboration between Red Hat and NVIDIA. We've long worked together to bring our technologies to the open hybrid cloud, and our new agreement to distribute the NVIDIA CUDA Toolkit across the Red Hat portfolio is a testament to that collaboration. This isn't just another collaboration; it's about making it simpler for you to innovate with AI, no matter where you are on your journey. Today, one of the most significant barriers to AI adoption isn't a lack of models or compute power, but rather the operational complexity of getting it all to work together. Engineers and data scientists shouldn't have to spend their time managing dependencies, hunting for compatible drivers, or figuring out how to get their workloads running reliably on different systems. Our new agreement with NVIDIA addresses this head-on. By distributing the NVIDIA CUDA Toolkit directly within our platforms, we're removing a major point of friction for developers and IT teams. You will be able to get the essential tools for GPU-accelerated computing from a single, trusted source. This means: A streamlined developer experience.