What are spot prices?
Understand flexible capacity signals.
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Spot GPUs suit flexible work; reserved capacity suits predictable or critical AI workloads that need dependable access.
Use spot GPUs for flexible, fault-tolerant AI workloads that can pause, checkpoint, retry, or wait; use reserved capacity for predictable or mission-critical workloads that need reliable access at a planned time. Spot GPUs vs reserved capacity is a risk decision as well as a price decision.
Memory trick: Spot is cheap when you can wait or restart; reserved is valuable when you cannot miss.
Access terms affect effective compute cost. Spot capacity can lower a flexible experiment bill, but interruption can destroy savings for a time-sensitive training run or production service. Reservations can protect access during tight supply, but buyers may pay for unused capacity.
Assume a restartable batch job would cost an illustrative $10,000 on reliable capacity. A spot offer discounted by 60% would cost $4,000 if it finishes without interruption. If repeated interruptions require running the work three times, the spot compute expense becomes $12,000 and the completion deadline may slip.
Example figures are illustrative calculations, not current quoted market prices.
Market signal
Watch the relationship between spot availability, on-demand terms, and reservation access. When spot offers become scarce or priced nearer to reliable capacity, spare supply may be narrowing. When buyers cannot obtain reservations at a needed date or configuration, anticipated demand may be absorbing future capacity.
Market read: spot measures spare flexible access; reservations measure the value of certainty. The spread between them matters only when both can serve comparable work. Figures here are illustrative unless explicitly sourced and dated — see our methodology.
Do not place a workload on spot simply because the price is lower. If checkpointing is missing, the dataset is costly to restage, the training deadline is fixed, or users depend on the service, interruption can create more cost and harm than the discount saves. Also do not reserve uncertain demand without measuring idle risk.
Practical takeaway
Classify workloads before selecting access: flexible, deadline-driven, or mission-critical. Estimate both compute expense and the consequence of unavailable or interrupted capacity, then decide what portion warrants certainty.
Decision check: use spot only when the job can survive its interruption scenario, and reserve only when the cost of uncertain access or missed timing justifies commitment.
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Use the GPU-Hour Cost Calculator, AI Training Cost Calculator, or Model Serving Cost Calculator.
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Step 5 of 8: When to use spot gpus vs reserved capacity