Resource
Estimate Token Usage Before You Run It
Know how many tokens a job will consume before you send it — input plus an assumed response, costed per call and at scale.
Calculate AI API Cost for a Prompt
Turn a prompt into a dollar figure: input cost, output cost, combined per call, and the number that actually matters — cost per 1,000 calls.
Overview
A single API call costs a fraction of a cent, which is exactly why teams underestimate the bill. This loads a data-extraction payload with a long response and prices it on every axis: input, output, combined, and at a thousand calls. Cost is a function of tokens times the model's rate, so the model you pick swaps a $1.25 input rate for a $15 one. Prices are labeled approximate and dated, because providers change them — the tool refuses to pretend otherwise.
How to use this resource
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Pick the model
Price varies five-fold across families — the model is the biggest cost lever.
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Cost every axis
Input, output, combined per call — output usually dominates.
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Project the scale
The per-1,000-calls line is where the real budget lives.
Why This Works
- Cost is tokens times rate, so the model choice moves the number the most
- Per-1,000-calls reframes a fraction-of-a-cent call into a real bill
- Pricing is labeled approximate and dated — no false precision on rates
Best for
- Budgeting an API integration
- Comparing cost across model families
- Pricing high-volume batch jobs
Not for
- Exact invoicing — use your provider's billing dashboard
- Checking context-window fit — use the Context Window Estimator
FAQ
What does an AI API cost report calculate per call and at scale?
It prices your prompt on every axis: the input cost, the output cost (usually the bigger share), the combined cost per call, and the per-1,000-calls line. The COST ESTIMATE gives the token count as a range, applies the model's input and output rate, then multiplies out — so a fraction-of-a-cent call becomes a real bill at volume.
Is the AI API cost estimate exact, and can I invoice a client from it?
No — treat it as a planning figure, not an invoice. The numbers come from character-based token estimates and pricing labeled 'approximate, June 2026,' which providers change without notice. Verify current rates before you rely on a figure, and pull your real bill from the provider's billing dashboard. The report prices tokens, not context fit.
Why does the per-1,000-calls line and the input-vs-output rate drive AI API cost?
Because cost is tokens times rate, and both levers stay hidden at the single-call level. That combined $0.0253 call looks trivial until the per-1,000-calls line turns it into $25.32–$25.39 — so budget on volume, not one request. Rate matters just as much: on GPT-5 the $10.00/1M output rate is eight times the $1.25/1M input rate, which is why output usually dominates the bill.
More resources from Token Counter
Resource
Token Counter for AI Prompts
Paste a prompt, get an honest token estimate — a range, not a fake-precise number — plus the cost across GPT, Claude, and Gemini.
Resource
Count Tokens Before Sending to the API
A quick pre-flight check: count a system prompt's tokens and cost before it ships, so the bill and the size hold no surprises.
Resources that pair well
Resource
Estimate Token Budget — Plan Before You Paste
Token budget planning for real workloads: how much of the window a transcript actually consumes, what is left for the answer, and how much headroom remains.
Resource
Message Too Long — the Fix That Doesn't Butcher Content
The "message too long" error has a structural fix: split at paragraph boundaries into sequenced chunks with wait rules, instead of pasting fragments and hoping.
Resource
Prompt Cleanup Examples (Before & After)
A set of before-and-after examples showing exactly what prompt cleanup removes — and what it deliberately leaves alone.
Related tools
Tool
Token Counter
Estimate how many tokens a prompt is and what it costs — honest ranges across GPT, Claude, and Gemini, with per-call and per-1,000-call pricing.