A/B Testing GPU Performance (Monthly) Calculator Examples
Worked examples show how to compare monthly GPU capacity, monthly cost, performance gains, and cost per million tasks.
These examples use consistent workloads to illustrate common monthly GPU comparisons. They show why GPU count, throughput, runtime, utilization, and hourly price should be reviewed together rather than in isolation.
Same GPU Count, Faster Configuration B
A team runs an inference workload for 8 hours per day on 22 days each month at 80% utilization.
Input Summary
Configuration A
4 GPUs, 120 tasks/hour/GPU, $2.40/GPU hour
Configuration B
4 GPUs, 180 tasks/hour/GPU, $3.10/GPU hour
Operating plan
8 hours/day, 22 days/month, 80% utilization
Calculation Breakdown
- 1Productive hours8 * 22 * 0.80140.8 hours
- 2A monthly workload4 * 120 * 140.867,584 tasks
- 3B monthly workload4 * 180 * 140.8101,376 tasks
- 4Performance comparison((101376 / 67584) - 1) * 10050.0% more throughput
- 5Efficiency comparisonA: (4 * 2.40 * 140.8 / 67584) * 1000000; B: (4 * 3.10 * 140.8 / 101376) * 1000000A: $20,000.00; B: $17,222.22 per million tasks
Result Summary
Efficiency comparison
A: $20,000.00; B: $17,222.22 per million tasks
A/B Testing GPU Performance (Monthly) Calculator
B delivers 33,792 more tasks per month and a lower cost per million tasks, although its GPU spending is $394.24 higher for the month.
Fewer Faster GPUs Versus More Slower GPUs
A data processing team wants to see whether fewer high-throughput GPUs can match a larger lower-throughput setup.
Input Summary
Configuration A
4 GPUs, 100 tasks/hour/GPU, $2.00/GPU hour
Configuration B
2 GPUs, 220 tasks/hour/GPU, $4.00/GPU hour
Operating plan
10 hours/day, 20 days/month, 75% utilization
Calculation Breakdown
- 1Productive hours10 * 20 * 0.75150 hours
- 2A monthly workload4 * 100 * 15060,000 tasks
- 3B monthly workload2 * 220 * 15066,000 tasks
- 4Monthly GPU costA: 4 * 2.00 * 150; B: 2 * 4.00 * 150A: $1,200; B: $1,200
- 5Cost per million tasksA: (1200 / 60000) * 1000000; B: (1200 / 66000) * 1000000A: $20,000.00; B: $18,181.82
Result Summary
Cost per million tasks
A: $20,000.00; B: $18,181.82
A/B Testing GPU Performance (Monthly) Calculator
B provides 10.0% more monthly capacity at the same estimated monthly GPU cost.
Lower-Cost Configuration A for a Fixed Monthly Schedule
A small batch-processing workload runs overnight on 12 active days each month.
Input Summary
Configuration A
2 GPUs, 150 tasks/hour/GPU, $1.80/GPU hour
Configuration B
2 GPUs, 175 tasks/hour/GPU, $2.60/GPU hour
Operating plan
6 hours/day, 12 days/month, 90% utilization
Calculation Breakdown
- 1Productive hours6 * 12 * 0.9064.8 hours
- 2Monthly workloadA: 2 * 150 * 64.8; B: 2 * 175 * 64.8A: 19,440 tasks; B: 22,680 tasks
- 3Monthly GPU costA: 2 * 1.80 * 64.8; B: 2 * 2.60 * 64.8A: $233.28; B: $336.96
- 4Cost per million tasksA: (233.28 / 19440) * 1000000; B: (336.96 / 22680) * 1000000A: $12,000.00; B: $14,857.14
- 5Performance comparison((22680 / 19440) - 1) * 10016.7% more throughput for B
Result Summary
Performance comparison
16.7% more throughput for B
A/B Testing GPU Performance (Monthly) Calculator
B delivers 16.7% more tasks but has a higher monthly cost and higher cost per million tasks.
How to Read Your Results
Monthly workload is estimated capacity, not a guaranteed production total.
A positive B performance advantage means B completes more tasks than A over the same estimated productive period.
Monthly cost difference is B minus A; a positive amount means B costs more.
Cost per million tasks is useful for comparing efficiency across configurations with different output levels.
Review monthly capacity separately from unit cost because the lowest-cost option may not meet required throughput.
Assumptions & Important Notes
- Every task is defined consistently and has comparable quality across the two configurations.
- The stated hourly rates and throughput figures are applied throughout productive operating time.
- Utilization represents productive work rather than total machine uptime.
- Examples include GPU cost only and exclude other infrastructure or operational costs.
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Frequently Asked Questions
Should I choose the configuration with the lowest cost per million tasks?
It is a useful efficiency measure, but it should be considered alongside the monthly capacity required, availability, and costs outside the entered GPU rate.
Can two configurations have the same monthly cost but different capacity?
Yes. A configuration with greater throughput per dollar can complete more work while costing the same amount for the planned operating period.
Why does the third example favor A even though B is faster?
B's hourly price increases more than its throughput relative to A, making B more expensive per completed task.
Can I use requests, images, tokens, or records instead of tasks?
Yes. Use any consistent unit of completed work, provided both configurations are measured with the identical unit and workload conditions.
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