Why GPU utilization matters for model inference

This post explains the importance of GPU utilization for cost-effective model inference, detailing how to measure compute, memory, and memory bandwidth usage. It emphasizes that increasing batch sizes is a primary method to improve GPU utilization and throughput, while acknowledging the trade-off with latency. The post also suggests considering more powerful GPUs like H100 for highly utilized workloads and points to the Baseten workspace's metrics tab for tracking these optimizations.