Enter samples, candidate models, trials per sample, token sizes, and an optional LLM-as-judge pass; Model Ruler returns total and per-run cost. Samples times models times trials multiplies cost linearly, so treat recurring CI/eval usage as a monthly line item, not a one-off.
Budgets repeated model-evaluation runs across samples, candidate models, trials, and optional judge passes.
Formula: total_cost = primary_eval_calls * primary_model_cost + judge_eval_calls * judge_model_cost
Audit coverage: Eval-suite budget
What does this calculator compute?
It multiplies samples, candidate models, and trials by per-call token cost — plus an optional judge pass — to budget an evaluation run.
What should I check before committing to a workload shape?
Eval cost scales with the number of test cases, how often the suite runs, and whether you use a judge model. A large judge model run on every commit is usually the dominant line; check whether a smaller judge or a reduced eval cadence holds quality before scaling frequency.
Is this a quote or a benchmark?
Neither. It is a computed estimate. Real-world cost varies by rate-limit shape, caching, token-count precision, and provider-specific discounts not reflected in the public pricing table.
Estimates use published per-token API pricing for the model/provider path shown by the calculator, reviewed on the source date shown. Provider rates change frequently; verify current pricing on the provider's own page before committing to traffic volume, eval cadence, or agent-loop workload shape. View methodology.