AI Performance Myths: Do IOPS Actually Matter?
Inside AI News, Friday, November 7th, 2025
With all the buzz around artificial intelligence and machine learning, it's easy to lose sight of which high-performance computing storage requirements are essential to deliver real, transformative value for your organization.
When evaluating a data storage solution, one of the most common performance metrics is input/output operations per second (IOPS). It has long been the standard for measuring storage performance, and depending on the workload, a system's IOPS can be critical.
In practice, when a vendor advertises IOPS, they are really showcasing how many discontiguous 4 KiB reads or writes the system can handle under the worst-case scenario of fully random I/O. Measuring storage performance by IOPS is only meaningful if the workloads are IOPS-intensive (e.g., databases, virtualized environments, or web servers). But as we move into the era of AI, the question remains: does IOPS still matter?