Live market-vs-spot spread
See the current CT-MKT vs CT-SPOT gap on the Market page.
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On-demand, reserved, and spot GPU pricing are three ways buyers obtain and pay for AI compute capacity.
On-demand vs reserved vs spot GPU pricing describes three ways to pay for AI compute capacity. On-demand capacity is flexible, reserved capacity exchanges commitment for access or discount, and spot capacity is typically discounted because it may be reclaimed or interrupted.
Memory trick: On-demand is a hotel room, reserved is a lease, and spot is a standby ticket: lower certainty can mean a lower price.
Contract type changes both buyer risk and what a displayed price means. The mix of buyers choosing flexible capacity, longer reservations, or interruptible supply reveals how much certainty is worth in a market shaped by GPU availability, power, and workload deadlines.
Assume a job needs 8 GPUs for 100 hours, or 800 GPU-hours. At an illustrative on-demand rate of $8 per hour it costs $6,400. Reserved at $6.50 costs $5,200 if the commitment fits. Spot at $3 costs $2,400 only if interruptions do not force costly delay or repeated work.
Example figures are illustrative calculations, not current quoted market prices.
Market signal
Compare the spread between similar on-demand and spot capacity. A wide discount can indicate available interruptible capacity or weak short-term demand; a narrow discount may indicate tighter supply. Strong demand for reservations can show that buyers value future certainty before visible list prices increase.
Market read: contract spreads translate buyer urgency into observable terms. When reliability commands a larger premium or spot discounts disappear, available flexible capacity may be tightening. See the live market-vs-spot spread on ComputeTape's Market page (CT-MKT vs CT-SPOT) for the current read. Figures here are illustrative unless explicitly sourced and dated — see our methodology.
The beginner mistake is assuming the lowest quoted rate wins. Spot capacity can be expensive when interruptions waste engineering time, miss a deadline, or cause a run to restart. Reserved capacity can be expensive when the buyer overcommits and leaves GPUs idle.
Practical takeaway
Match contract type to workload criticality and predictability. Flexible experiments may suit on-demand access; dependable production serving or scheduled training may justify reservation; fault-tolerant batch jobs may use spot when savings exceed interruption cost.
Decision check: assign each workload a tolerance for delay, interruption, and unused commitment before selecting the price type that appears cheapest.
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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: On demand vs reserved vs spot GPU pricing