A/B Testing GPU Performance Per-User Calculator Examples
Worked examples showing how GPU time and estimated infrastructure cost per user can change between an A/B test control and variant.
These examples use the same per-user method with different workload patterns, GPU rates, and user volumes. They show why a faster variant does not always produce the same percentage of cost savings.
Faster model on the same GPU rate
A product team tests an optimized inference path for 10,000 users over one month.
Input Summary
Control GPU time per request
2.5 seconds
Variant GPU time per request
1.8 seconds
Requests per user
120
GPU hourly cost for both groups
$2.50
Users in period
10,000
Calculation Breakdown
- 1Control time per user2.5 × 120300 seconds
- 2Variant time per user1.8 × 120216 seconds
- 3Time saved300 − 21684 seconds
- 4Cost savings per user(300 ÷ 3600 × 2.50) − (216 ÷ 3600 × 2.50)$0.0583
- 5Period savings0.0583 × 10,000$583.33
Result Summary
Period savings
$583.33
A/B Testing GPU Performance Per-User Calculator
The variant reduces GPU time by 28% and estimates $583.33 in GPU cost savings for the period.
Faster variant with a higher hourly GPU cost
A team tests a faster premium GPU deployment for a high-volume image feature.
Input Summary
Control GPU time per request
4.0 seconds
Variant GPU time per request
2.5 seconds
Requests per user
80
Control GPU cost per hour
$2.00
Variant GPU cost per hour
$3.00
Users in period
50,000
Calculation Breakdown
- 1Control time per user4.0 × 80320 seconds
- 2Variant time per user2.5 × 80200 seconds
- 3Time reduction(320 − 200) ÷ 320 × 10037.5%
- 4Control cost per user320 ÷ 3600 × 2.00$0.1778
- 5Variant cost per user200 ÷ 3600 × 3.00$0.1667
- 6Period savings(0.1778 − 0.1667) × 50,000$555.56
Result Summary
Period savings
$555.56
A/B Testing GPU Performance Per-User Calculator
The variant saves 120 GPU seconds per user and about $0.0111 per user despite its higher hourly rate.
Slower variant with lower-cost capacity
A team evaluates a lower-cost serving setup for a moderate-use feature.
Input Summary
Control GPU time per request
1.5 seconds
Variant GPU time per request
2.0 seconds
Requests per user
30
Control GPU cost per hour
$4.00
Variant GPU cost per hour
$2.00
Users in period
25,000
Calculation Breakdown
- 1Control time per user1.5 × 3045 seconds
- 2Variant time per user2.0 × 3060 seconds
- 3Time saved45 − 60−15 seconds
- 4Control cost per user45 ÷ 3600 × 4.00$0.0500
- 5Variant cost per user60 ÷ 3600 × 2.00$0.0333
- 6Period savings(0.0500 − 0.0333) × 25,000$416.67
Result Summary
Period savings
$416.67
A/B Testing GPU Performance Per-User Calculator
The variant is 33.3% slower in GPU time but estimates $0.0167 less cost per user.
How to Read Your Results
Positive GPU time saved means the variant uses fewer GPU seconds per user; a negative value means it uses more.
GPU time reduction is measured relative to the control, not relative to the variant.
Positive cost savings per user favor the variant under the entered effective hourly costs.
Estimated period savings assume every user in the stated period receives the variant.
Review time, cost, quality, reliability, and experiment evidence together rather than using one output alone.
Assumptions & Important Notes
- All inputs refer to the same reporting period and comparable workload.
- Average requests per user are representative of the rollout population.
- Hourly costs are effective costs expressed in the same currency.
- Savings are scaled linearly and do not account for capacity commitments or utilization thresholds.
Related Examples
Frequently Asked Questions
Should I use the mean GPU time in these examples?
Use the metric that matches the decision. Mean GPU time is generally useful for total usage and cost estimates; percentile measures can supplement it for latency analysis.
Why can time savings be much larger than cost savings?
The variant may have a higher hourly GPU cost, or some infrastructure costs may be fixed rather than usage-based.
Can I use these examples for API requests instead of users?
Yes. Set requests per user to 1 and treat each user record as one comparable request, or use a calculator designed around request volume.
What does a negative period saving mean?
It means the variant's estimated GPU cost is higher across the entered population.
Ready to calculate your own result?
Use the live calculator with your own inputs, timing, and preferences.