LLM Cost Leak Scanner

Estimate avoidable spend from hidden leak paths: retries, malformed outputs, and overpowered default models. Then apply routing + eval guardrails to cut waste.

Monthly requests

Avg tokens per request (in + out)

Current blended $ per 1M tokens

Retry rate (%)

Malformed/failed output reruns (%)

Traffic that can use cheaper models (%)

Average cheaper-model discount (%)

Estimated Avoidable Monthly Spend

Estimated Avoidable Annual Spend

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How to use this report

Fix retries first with schema guards and deterministic retries.
Route low-risk traffic to cheaper models with quality thresholds.
Run eval packs weekly so routing rules track quality drift.

Inference Labs automates this loop with policy routing, trace logging, and eval workflows. Use the trial link above with the scanner attribution tag to apply your report in production.