GPU Cloud Quote Checklist

Short Answer

• Do not compare GPU providers on hourly rate alone.
• Ask what has to be paid, moved, stored, retried, reserved, and operated for the workload to finish.
• The cheapest listed H100 can be the wrong placement if capacity is unreliable or data movement dominates the job.

Quote Fields To Request

• GPU model, memory, interconnect, and number of GPUs per node.
• Minimum rental window, reservation length, commitment, or deposit.
• Storage included versus billed separately, including snapshots and persistent volumes.
• Ingress, egress, inter-region, and private network transfer charges.
• Idle capacity, queue time, failed job, and retry assumptions.
• Support level, SLA, managed Kubernetes or inference service fees.
• Whether pricing changes for spot, reserved, marketplace, or dedicated capacity.

Comparison Table

• Sticker GPU rate: useful for screening, weak for final decisions.
• Useful GPU-hour: better for training and batch jobs because utilization is visible.
• Total job cost: best for one-off training runs because retries and data movement are included.
• Monthly serving cost: best for inference because idle baseline and traffic variance matter.
• Ops-adjusted cost: best when the team has limited infrastructure tolerance.

Rough Math

• Estimated job cost = GPU hourly rate x GPU count x runtime hours + storage + transfer + managed fees + idle/retry allowance.
• Estimated inference month = baseline GPU hours + burst GPU hours + storage + transfer + observability + support.
• Utilization-adjusted GPU rate = listed hourly rate / expected utilization.
• Label every number as provider quote, observed bill, benchmark result, or estimate.

Questions To Send Providers

• What exactly is included in the hourly GPU rate?
• What happens if capacity is unavailable when the job starts?
• Are storage and data transfer billed by a separate product?
• Do failed jobs, checkpoint restores, or retries create extra billable hours?
• Can I cap spend or set an alert before the workload runs?
• What is the lowest-friction way to leave with my data and artifacts?

Red Flags

• A quote that does not mention egress or persistent storage.
• A low hourly rate with unclear capacity reliability.
• A managed inference price that hides utilization assumptions.
• A provider comparison that ignores engineer time.
• A benchmark that does not match your batch size, model size, or data path.

When To Use The Quiz

• Use the RunPlacement quiz after collecting at least one real quote or bill line.
• The quiz is most useful when you can state workload type, GPU need, data movement, priority, budget band, and ops tolerance.