This article highlights OpenMetal’s perspective on AI infrastructure, as shared by Todd Robinson at OpenInfra Days 2025. It explores how OpenInfra, particularly OpenStack, enables scalable, cost-efficient AI workloads while avoiding hyperscaler lock-in.
Tag: AI workloads
At OpenMetal, you can deploy AI models on your own infrastructure, balancing CPU vs. GPU inference for cost and performance, and maintaining full control over data privacy.
When it comes to raw performance metrics, GPUs often lead the pack. Their architecture is specifically tailored for the high-speed, parallel processing demands of AI tasks. However, this doesn’t always translate into a one-size-fits-all solution.
In this article, we’ll explore scenarios where CPUs might not only compete but potentially gain an upper hand, focusing on cost, efficiency, and application-specific performance.