The hidden cost of cloud GPU training: egress, idle time, and lock-in

Cloud GPU training costs are often underestimated because teams focus on hourly GPU prices and miss idle capacity, egress fees, and migration costs.

The article argues that underutilized GPUs, outbound data transfer charges, and vendor lock-in can add up to more than the headline rate, especially in training workflows.

It cites 2026 utilization and pricing data across AWS, Google Cloud, Azure, and Hetzner to show how these hidden costs accumulate.

Recommended fixes include idle detection, right-sizing hardware, improving pipelines, co-locating compute with storage, compressing data, and using portable tooling like Kubernetes.