Monthly GPU Performance A/B Testing Formula
Learn how monthly GPU throughput, operating cost, cost per million tasks, and performance advantage are calculated for two configurations.
This calculator estimates how much work two GPU configurations can complete in a month under the same schedule and utilization assumption. It combines benchmark throughput, GPU quantity, productive run time, and hourly GPU cost so that performance and efficiency can be compared on a consistent basis.
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Configuration B Monthly Performance Advantage
Where:
Divide B's estimated monthly tasks by A's estimated monthly tasks, subtract 1, and convert the result to a percentage. A positive result means B completes more work; a negative result means it completes less.
Variables Explained
| Variable | What It Means | Unit |
|---|---|---|
| monthlyWorkA - Configuration A monthly workload | Estimated number of tasks completed by configuration A during productive monthly operating time. | tasks |
| monthlyWorkB - Configuration B monthly workload | Estimated number of tasks completed by configuration B during productive monthly operating time. | tasks |
| gpuCountA - GPUs in configuration A | Number of GPUs assigned to configuration A. | number |
| gpuCountB - GPUs in configuration B | Number of GPUs assigned to configuration B. | number |
| throughputA - Configuration A throughput per GPU | Measured average work completed by one GPU in configuration A per hour. | tasks per hour |
| throughputB - Configuration B throughput per GPU | Measured average work completed by one GPU in configuration B per hour. | tasks per hour |
| productiveHoursMonthly - Productive GPU hours per month | Scheduled monthly hours adjusted for expected productive GPU utilization. | hours |
| hourlyRateA - Configuration A cost per GPU hour | Hourly cost assigned to one GPU in configuration A. | currency |
| hourlyRateB - Configuration B cost per GPU hour | Hourly cost assigned to one GPU in configuration B. | currency |
Step-by-Step Calculation
Calculate scheduled monthly hours
Multiply the planned daily operating time by the number of active days in the month.
scheduledHoursMonthly = hoursPerDay * daysPerMonth
Adjust time for productive utilization
Reduce scheduled hours to the expected time GPUs are doing productive work.
productiveHoursMonthly = hoursPerDay * daysPerMonth * (utilization / 100)
Estimate configuration A monthly workload
Multiply A's GPU count, per-GPU throughput, and productive monthly hours.
monthlyWorkA = gpuCountA * throughputA * productiveHoursMonthly
Estimate configuration B monthly workload
Use the same method for configuration B, based on its own GPU count and benchmark throughput.
monthlyWorkB = gpuCountB * throughputB * productiveHoursMonthly
Calculate monthly GPU cost
Multiply each configuration's GPUs, hourly rate, and productive hours.
monthlyCostA = gpuCountA * hourlyRateA * productiveHoursMonthly; monthlyCostB = gpuCountB * hourlyRateB * productiveHoursMonthly
Calculate cost efficiency
Scale the cost of completed work to one million tasks for an efficiency comparison.
costPerMillionA = (monthlyCostA / monthlyWorkA) * 1000000; costPerMillionB = (monthlyCostB / monthlyWorkB) * 1000000
Compare monthly performance
Express B's monthly workload difference relative to A as a percentage.
performanceAdvantageB = ((monthlyWorkB / monthlyWorkA) - 1) * 100
Four-GPU Monthly Configuration Comparison
Productive monthly hours
8 * 22 * (80 / 100)
140.8 hours
Configuration A workload
4 * 120 * 140.8
67,584 tasks
Configuration B workload
4 * 180 * 140.8
101,376 tasks
Configuration A monthly GPU cost
4 * 2.40 * 140.8
$1,351.68
Configuration B monthly GPU cost
4 * 3.10 * 140.8
$1,745.92
Cost per million tasks
A: (1351.68 / 67584) * 1000000; B: (1745.92 / 101376) * 1000000
A: $20,000.00; B: $17,222.22
B performance advantage
((101376 / 67584) - 1) * 100
50.0%
Final Result
Configuration B produces an estimated 33,792 additional tasks per month, or 50.0% more throughput than A. It costs $394.24 more per month but has a lower estimated GPU cost per million tasks.
Assumptions
- ✓Both configurations process the same workload with matching model versions, data, batch size, precision, and software settings.
- ✓The per-GPU throughput measurements are representative of productive production work.
- ✓The utilization percentage applies equally to both configurations.
- ✓The entered hourly rate represents the GPU costs intended for the comparison.
- ✓Monthly productive hours are estimated from the stated schedule rather than actual job logs.
Limitations
- !Actual throughput can change with input mix, batch sizes, data loading, memory constraints, software updates, and multi-GPU scaling behavior.
- !The calculation does not automatically include storage, CPU instances, networking, licenses, support, or engineering costs.
- !Cloud availability, preemption, maintenance, failures, and queueing can reduce real completed work.
- !Cost per million tasks is only meaningful when a task has the same definition and quality standard in both tests.
Common Mistakes to Avoid
Comparing throughput benchmarks measured with different models, precision modes, batch sizes, or input datasets.
Entering total configuration throughput in a field that expects throughput per GPU.
Using scheduled hours as if every scheduled hour is productive rather than applying a realistic utilization estimate.
Comparing hourly GPU price alone instead of cost per completed task.
Treating a benchmark result as guaranteed production throughput without testing representative workloads.
Related Formulas
Frequently Asked Questions
How is monthly GPU workload calculated?
Monthly workload equals GPU count multiplied by throughput per GPU and productive monthly hours. Productive hours are scheduled hours multiplied by utilization.
How is GPU cost per million tasks calculated?
The calculator divides estimated monthly GPU cost by estimated monthly completed tasks, then multiplies by 1,000,000.
Why can configuration B be more expensive monthly but cheaper per task?
If B's throughput rises by more than its GPU hourly cost, it can complete each task at a lower estimated cost even while its total monthly bill is higher.
What does a negative performance advantage mean?
A negative result means configuration B is estimated to complete fewer monthly tasks than configuration A.
Does utilization change the cost per million tasks?
When the same utilization is applied to both monthly cost and workload, it generally does not change cost per million tasks. It does change monthly capacity and monthly spend.
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