What one Issue delivery actually costs

THE MEASUREMENT

46 real deliveries, measured on our own repository

Every Orbi delivery runs two agent sessions — the implementation, then an independent review that can repair the branch and rerun the suite. As of 2026-09-12 we aggregated the session logs of n=46 deliveries of the orbi repository itself (Python, full CI, issues written to spec). The sample is whatever worktrees are on disk that day — it moves as worktrees get cleaned up — so n is a snapshot as of the stated date, not a permanent fact. Here is the complete per-delivery distribution of totalTokens — the count the provider actually bills, cache reads included:

Source, so anyone can re-derive it: the agent session logs of the orbi-build/orbi repository's git worktrees (<repo>/.worktrees/*/.pi-session/*.jsonl), aggregated 2026-09-12. One delivery = one worktree's implement + review sessions; a delivery's totalTokens = the sum of usage.totalTokens over every logged record; n = worktrees whose logs carry at least one usage record (older or newer sessions without usage logging are not countable); percentiles by nearest rank. The sample moves as worktrees are cleaned up. Where the tokens go: 95.9% cache reads, 3.4% input, 0.7% output.

READ THE LIMITS FIRST

Three things this page does not claim

• OUR REPO ONLY
  This is our repository's measured range — not a promise to everyone

  Python, a full CI suite, and issues written to spec keep our context short. A repository with longer context, slower tests, or vaguer issues lands elsewhere in the distribution. Treat the tables above as what they are: our repo's measured range.

• CACHING IS LOAD-BEARING
  95.9% cache reads assumes the provider supports prompt caching

  The whole cost structure rests on cache hits. On an endpoint without prompt caching — where every token bills as a miss — the same work costs roughly an order of magnitude more. Check your provider before extrapolating.

• TOTAL TOKENS, AS BILLED
  Numbers are totalTokens, cache reads included

  That is the line the provider actually bills. Counting only input + output would hide about 96% of the real consumption and flatter the number — the opposite of what this page is for.

WHY IT'S SO CHEAP

A cache hit costs 1/50 of a miss — and 95.9% of the work is cache hits

Each delivery re-reads the same repository context: the tree, the conventions, the issue, the failing tests. Prompt caching turns that repeated reading into billed hits at $0.003/1M instead of misses at $0.15/1M. That single ratio is why a full delivery — implementation plus independent review that can repair and rerun — costs cents. It is also the honest question to ask any BYOK agent vendor: what share of your tokens are cache hits, and what does your provider charge for each?