The hourly price looked great, so the cheapest GPU felt like the responsible choice. Then the run stretched into the night and the "cheap" decision stopped looking cheap.
Why this keeps happening
- people compare hourly rate before they compare total job time
- a slower GPU can make the full bill worse even when the hourly number looks better
- longer jobs mean more waiting, more retries, and more chances to waste the whole evening
- cheap compute is only cheap if it actually finishes fast enough
The real comparison
GPU A might be cheaper per hour.
GPU B might finish much faster.
If GPU B cuts the run in half, the total cost and the human cost can both be lower even with a higher hourly rate.
Practical rule
- use RTX 4090 when the workload fits and speed is good enough
- use A100 80GB when memory-heavy or restart-prone jobs keep dragging
- use H100 only when the workload proves smaller cards are not enough
The simple takeaway
If the cheapest GPU turns a two-hour run into an all-night job, it was never the cheaper option.
Optimize for total cost and time-to-result together.
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