Your workload & batch tier

Total API calls you run in a month.
Prompt sent per request.
Generated tokens per request.
Base real-time input price — edit to your model.
Base real-time output price — edit to your model.
Sets the discount below — editable.
Async-tier discount vs the real-time rate.
Only offline / non-interactive work qualifies. Anything a user waits on in real time stays full price — set this to the share that can tolerate up to ~24h turnaround.
All real-time / month
$0
With batch tier / month
$0
Cost component All real-time With batch tier

The discount defaults to an illustrative 50% — the common batch-tier discount — for reference only; providers differ and pricing changes, so pick a profile or edit the field to match yours. Confirm live rates at OpenAI, Anthropic, and Google Gemini. The discount only applies to the async-tolerant share you enter — real-time requests stay full price, which is why the blended saving is the discount times that share, not a blanket 50% off. Batch trades turnaround time (minutes to ~24h) for the price cut; it never costs more in dollars, so this tool never shows a negative — it shows $0 saved when nothing is batchable. The Local (ABUZ8 OS) row is $0 per token — a model on hardware you own has no per-token charge at any speed; the fixed hardware is covered in the self-host vs cloud calculator. Reusing the same prefix instead? See the prompt caching calculator.

Batch is a discount on tokens you are still renting.

The async tier trims the bill for work that can wait — but you are still paying per token, and still shipping your data to someone else's queue. ABUZ8 OS runs the model on hardware you own: real-time or bulk, input and output are $0 per token, no 24-hour wait, and nothing leaves the machine. Sovereign by default, cloud only when it genuinely wins.

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How batch API economics actually work

Related: Token counter · LLM API price comparison · Prompt caching calculator · AI agent cost calculator

Same model, cheaper because you wait

A batch tier is not a smaller or worse model — it is the exact same model, run on the provider's spare capacity and returned within a window instead of instantly. That flexibility is what earns the discount, commonly around half off both input and output. If your job does not need an answer this second, batching is usually the single biggest lever on the bill short of leaving the cloud entirely.

The discount only touches what can wait

The saving is never a flat 50% off your whole bill — it is the discount applied only to the requests you actually route through the queue. A product that is half real-time chat and half overnight batch jobs saves the discount on that half, not the whole. This calculator makes you name the async-tolerant share on purpose, so the number it shows is the honest blended saving rather than a best-case headline.

The one cost is latency, not dollars

Batch never costs more money than real-time — that is why this tool never shows a negative saving. What it costs is time: results can take minutes, and providers reserve the right to take up to roughly a day. So batch is right for bulk classification, embedding a corpus, generating content ahead of time, evaluations, and enrichment — and wrong for anything a person is sitting there waiting on.

The sovereign floor: $0 per token

Batch pricing is still a per-token rental — a cheaper rental, but a rental, and your data still goes to someone else's queue. A model running locally on a GPU you own has no per-token bill at all, real-time or bulk, with only electricity as the variable cost. Above a modest scale, owning the model beats even the batch rate, and you keep both the speed and the data. ABUZ8 OS runs locally by default and only reaches for a paid API when a hosted model clearly wins.

Is my data sent anywhere?

No. This calculator runs entirely in your browser. Nothing you enter is uploaded, logged, or stored.