Pricing

frites can estimate per-child spend from a config-driven, per-model rate table. Pricing is opt-in: there are no built-in rates. When you supply rates, frites uses them to fill in spend figures that a backend doesn't self-report.

This page documents the pricing model itself. The pricing config key is defined in configuration.

Authoritative vs. estimated spend

How spend is reported depends on the backend:

Backend	Spend source	Display
claude (claude -p)	The CLI self-reports actual cost.	Authoritative: shown as $0.0123.
codex (ChatGPT backend)	Reports no cost.	Estimated from the pricing table when rates exist, shown with a leading tilde, ~$0.0123.

Without a pricing table, codex spend reads as cost n/a (and previously made codex look "free" next to claude). Supplying rates replaces those blanks with estimates. Authoritative claude figures are never overwritten by estimates: the reported cost always wins, and the estimate is only computed when the backend reported none.

The rate table

The pricing config key is a map of model → rates, in dollars per million tokens ($/Mtok):

{
  "pricing": {
    "gpt-5.5": {
      "inputPerMtok": 1.25,
      "outputPerMtok": 10.0,
      "cachedInputPerMtok": 0.125,
      "cacheWritePerMtok": 1.5625
    }
  }
}

Field	Required	Meaning
inputPerMtok	yes	Rate for fresh (uncached) input tokens.
outputPerMtok	yes	Rate for output tokens (reasoning-inclusive).
cachedInputPerMtok	no	Rate for cached/reused input (cache reads). Defaults to inputPerMtok when omitted.
cacheWritePerMtok	no	Rate for cache-write (creation) input, claude only. Defaults to inputPerMtok when omitted.

How a rate is selected

For a given model name, frites resolves the table entry as follows:

1. Exact match wins. If the table has a key equal to the model name, that entry is used.

2. Otherwise a prefix match in either direction: a table key is used if the model name starts with the key or the key starts with the model name.

The bidirectional prefix rule means a coarse key like "gpt-5.5" covers a fully versioned model id like "gpt-5.5-2026-…", and a fully versioned key still matches a bare alias. If nothing fits, no rate is found and that child's spend is left unestimated.

How an estimate is computed

frites normalizes usage to a provider-agnostic shape before estimating:

• inputTokens is the grand total input (all categories summed).

• cacheReadTokens is the cached/reused portion of that total.

• cacheCreationTokens is the cache-write portion (claude only).

• outputTokens is reasoning-inclusive on both providers.

The fresh (newly billed) input is inputTokens − cacheReadTokens − cacheCreationTokens (floored at zero). The estimate is then:

fresh * inputPerMtok
  + cacheReads * (cachedInputPerMtok ?? inputPerMtok)
  + cacheWrites * (cacheWritePerMtok ?? inputPerMtok)
  + output * outputPerMtok

divided by 1,000,000. When no rates are supplied for the model, the estimate is undefined; estimation is strictly opt-in.

Where estimates surface

Estimated spend appears in the same places authoritative cost does: the live per-agent progress line, the per-turn council recap, and the gateway log, always marked with a ~ so estimates are visually distinct from claude's reported figures. The same estimator (@frites/core) is the single source of truth used by both the gateway's answer-council path and the worktree engine path.

See cost telemetry for how these figures are displayed during a turn, and configuration for the pricing key alongside the other config keys.