offpeak

Deadline-priced inference. Same model, same tokens, a different hour.

A large share of AI work — embeddings, evals, backfills, report generation, overnight agents — has no human waiting on it. The providers already price that patience: OpenAI and Anthropic both publish their batch tiers at 50% of list. offpeak is the workflow that collects the difference.

import offpeak

jobs = [offpeak.job("claude-haiku-4-5", f"Summarize:\n\n{d}") for d in docs]

print(offpeak.quote(jobs, deadline="06:00"))   # what is the wait worth?
results = offpeak.run(jobs, deadline="06:00")  # collect it
print(offpeak.receipt(results))                # what it actually cost

• Quickstart — install, quote, run, read the receipt.
• The night board — the same claim, marked nightly against open grid data.
• Spec — deadline semantics, statuses, receipts.
• API reference — every public symbol.
• Roadmap — what exists, what does not, and what is being built.

What it guarantees

One Result per job, always. Provider failures at submit, poll, cancel or sync are captured, not raised. Affected jobs take the sync fallback where the deadline still allows it, and otherwise return failed with the provider's message attached. Exceptions are reserved for programming errors — a deadline in the past, or a model no venue supports.

Your keys, your perimeter. offpeak talks straight to the providers with your own credentials. There is no proxy and no third party in the data path.

Receipts are arithmetic, not estimates. Every figure traces to a published price sheet, and a model that is not on one settles as None rather than a guess.