# What is a cost cross-check?

> A cost cross-check compares your own calculated figure against the provider's reported one, with a tolerance small enough to catch a wrong rate.

URL: https://getculpa.com/what-is-cost-cross-check
Last reviewed: 2026-08-02

## Answer
A cost cross-check compares the figure you calculated from tokens and rates against the figure the provider reported for the same call, and flags a difference bigger than display rounding explains. Culpa, a local-first LLM cost, margin, and forecast ledger, reconciles the two per model, so a wrong rate surfaces as a disagreement rather than as a plausible total.

## Why this happens
A calculated cost is only as good as the rate behind it, and a rate is a number somebody typed. That's the weak joint in every cost ledger, and it fails silently, because a wrong rate produces totals that are internally consistent and uniformly wrong. When a provider reports its own cost figure alongside the response, you get a second opinion for free. The two should agree to within a whisker, and the size of that whisker matters: too tight and ordinary rounding looks like a fault, too loose and a real error hides.

## What this usually looks like
- Your rates were entered once and nothing has ever checked them against a provider.
- One model's totals are consistently off while every other model reconciles.
- A provider returns a cost figure and nothing in your pipeline reads it.
- Rate updates ship with no test that would catch a mistyped decimal.

## Common mistakes
- Trusting a calculated cost because it's self-consistent. Why it hurts: A wrong rate is self-consistent across every row it touches, which is what makes it survive. Do instead: Compare against the provider's own figure wherever one exists, per model rather than in total.
- Comparing only monthly totals. Why it hurts: One model's error can hide inside another model's volume, so the aggregate agrees while a rate is wrong. Do instead: Group the comparison by model. An error that vanishes in the total stands out per model.
- Setting the tolerance by feel. Why it hurts: Too tight and rounding noise buries the signal, too loose and a real rate error passes. Do instead: Set it just above provider display rounding, so anything larger is worth investigating.

## Self-check
- Check whether any provider you use returns its own cost figure, and whether you keep it.
- For a month, compare calculated against reported per model rather than in aggregate.
- Divide each model's difference by its call count to get a per-call delta.
- Treat anything meaningfully above rounding noise as a rate to re-verify against the provider page.
- Re-run the comparison after every price-book update, because that's when a digit goes missing.

## Three models compared per call, not in total (illustrative)
900,000 calls in a month across three models where the provider returned its own cost figure. A tolerance of $0.000002 per call absorbs provider-side display rounding. Figures are modelled.
  Model A, 400,000 calls: calculated $12,400.00, reported $12,400.02, per-call delta $0.00000005
  Model B, 300,000 calls: calculated $8,900.00, reported $8,900.06, per-call delta $0.0000002
  Model C, 200,000 calls: calculated $3,100.00, reported $3,410.00, per-call delta $0.00155
  A and B sit below the tolerance, so both are rounding rather than error
  C is 775 times the tolerance, and $3,410 / $3,100 = 1.10, so its rate is 10% low
Two models agree to within display rounding and one disagrees by exactly a tenth. The per-call view is what makes that legible, because in a $24,400 total a $310 error looks like nothing.

## Cost figures
Every figure carries its confidence and its source. No figure on this site is provider-reported.
- $0.000002 — per-call tolerance that separates provider display rounding from a genuine pricing error [calculated] Source: An absolute per-call tolerance chosen to sit just above provider-side display rounding, applied to the absolute difference between calculated and reported cost.
- $310.00 — modelled monthly disagreement on one model, from a rate entered 10% low [calculated] Source: $3,410.00 reported minus $3,100.00 calculated, from the teardown arithmetic. The call volumes are modelled.

## FAQ
Q: Why not just use the provider's reported cost?
A: Because it isn't always there, and when it does arrive it carries no attribution. A calculated figure can be split by feature, user and customer, which is the whole point. The reported figure is best used as a check on the calculated one rather than as a replacement for it.

Q: How small should the tolerance be?
A: Just above provider display rounding. Around two micro-dollars per call works, because it absorbs the rounding a provider applies to its own figures while still catching a rate that's wrong by any meaningful margin.

Q: Does this site publish provider-reported figures?
A: No, and that's a different question from what the product records. Every cost figure on these pages is calculated with the arithmetic shown or an estimated range, because no customer invoice data backs a reported one here. A product reconciling against a provider's number is doing the opposite of publishing it.

## Sources
- Anthropic pricing: https://platform.claude.com/docs/en/docs/about-claude/pricing

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