Estimate completed AI translation tasks per hour and per day from worker count, average task time, utilization, and success rate. Use the demand comparison to see whether the configured pipeline has spare capacity.
Gross attempts/hour = workers × 3,600 ÷ task seconds. Successful throughput = gross attempts × utilization × success rate. Daily capacity = successful throughput × 24.
Successful throughput discounts theoretical attempt rate for idle time and failed attempts. The comparison assumes a 24-hour service; for a shorter operating window, multiply hourly throughput by the actual scheduled hours.
Planning estimate only. Validate the result against production telemetry and current provider pricing before committing capacity or budget.
With 12 workers, 0.9 seconds per attempt, 75% utilization, and a 98% success rate, successful throughput is about 35,280 tasks per hour.
Use recent production telemetry or a representative benchmark on the same model, hardware, input size, and quality settings.
No. It focuses on the entered operating assumptions; add fixed staffing, development, and platform overhead separately when building a full budget.
Use the observed fraction of attempts that must be repeated, and avoid adding the same retry overhead to more than one input.
A vendor maximum is a useful ceiling, but measured sustained performance is safer for capacity planning.
Input size, batching, model version, hardware, cold starts, safety checks, and traffic bursts can all change actual results.
| Input | Purpose |
|---|---|
| Workload values | Define the size and frequency of the task. |
| Performance values | Describe measured processing behavior. |
| Planning assumptions | Add utilization, retries, price, or headroom where applicable. |