See how many retries your prompts truly need. Balance quality gains against time and spend. Generate exportable reports for teams, audits, and planning today.
| Scenario | Prompts | Retries | Success | Avg tokens | Cost / 1k | Latency (s) |
|---|---|---|---|---|---|---|
| Balanced production | 200 | 60 | 230 | 900 | 0.40 | 3.20 |
| High retries, marginal gains | 200 | 180 | 250 | 950 | 0.40 | 3.40 |
| Low retries, stronger first pass | 200 | 30 | 210 | 800 | 0.40 | 2.80 |
This calculator models retries as extra attempts that can increase acceptance, but also add cost and latency. It produces a composite efficiency score from four components.
CostScore and LatencyScore use smooth penalties so small increases do not overreact, while large increases reduce the score more strongly.
Prompt retry efficiency matters when teams chase better outputs through repeated attempts. This calculator treats retries as measurable operational load. Enter total prompts and retries from logs, plus accepted outputs. When successful outputs exceed prompts, it often indicates variant generation, batching, or multi-candidate selection workflows.
Attempts increase token consumption linearly, so total tokens equal attempts multiplied by average tokens per attempt. With a unit price per 1,000 tokens, the calculator estimates spend for the entire run. Cost per attempt helps compare different prompt designs, models, and sampling settings on equal footing.
Retries also add time. Total latency is calculated as attempts times average latency per attempt, providing a practical proxy for user waiting time and system capacity usage. Higher latency weight is appropriate for interactive products, while batch pipelines can prioritize cost and success instead.
Quality gain can be entered as an uplift percent or derived from baseline and post-retry scores. The calculator uses whichever gain is larger to avoid understating improvement. This approach supports both automated scoring and human review programs where quality is expressed on a 0–100 scale.
The composite efficiency score blends success, quality gain, cost score, and latency score using your weights, then adjusts by retry efficiency. Retry efficiency penalizes heavy retry rates, emphasizing first-pass performance. The suggested retry cap is a heuristic that tightens limits when retries, costs, or latency are pushing the score down.
It is the count of outputs that meet your acceptance criteria, such as passing evaluation checks, matching a rubric, or being approved by reviewers.
Some pipelines generate multiple candidates per prompt and accept more than one, or measure success as “accepted responses” rather than “accepted prompts.” The calculator supports those cases by using attempts as the denominator.
Set higher success and quality weights for reliability-focused use cases. Increase cost and latency weights for budget or responsiveness goals. Weights are automatically normalized so they always sum to one.
Retry efficiency is success rate divided by one plus retry rate. It rewards high acceptance while penalizing excessive retry pressure, so improving first-pass prompts usually increases it quickly.
It reduces your current cap when retry rate is high or when cost and latency scores are low. This is a heuristic to guide policy tuning, not a guaranteed optimum.
Yes. Run the calculator for each variant using the same time window. Compare efficiency score, total cost, and suggested cap to decide which prompt design delivers better outcomes per unit of effort.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.