AI Token Cost Calculator

AI Token Cost Calculator

Work out what an AI feature will actually cost before you build it. Pick a model, set your prompt and reply sizes, and see the cost per request, per day and per month — then compare every major model on the same workload.

Input tokens per request
Output tokens per request
Share of input served from cache
0%
Requests per day
Batch API
Asynchronous processing — 50% off at OpenAI, Anthropic and Google
Example workloads
0 characters · 0 words · ≈ 0 tokens
Estimated cost on —
$0.00 / month
Per request
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Per 1K requests
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Per day
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Per year (365d)
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Tokens / month
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Requests / month
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Fresh input—
Cached input—
Output—

Same workload, every model

Monthly cost for the exact workload set above, cheapest first. Click any row to load that model into the calculator.

Last verified: 16 Oct 2026 — prices checked against the providers’ official pricing pages. INTRO rates and the GPT-4o shutdown are flagged on their rows below.

Model Provider Input $/1M Output $/1M Per request Monthly

How the billing works: you pay one rate for tokens you send (input) and a higher rate for tokens the model writes (output, which includes reasoning/thinking tokens). Repeated prompt prefixes read from cache are billed at the much lower cached rate. Prices are standard short-context list prices in USD, checked 16 Oct 2026 — see sources below.

Model prices: standard API list prices, USD per 1M tokens, checked 16 Oct 2026 against the providers’ official pricing pages (OpenAI, Anthropic, Google) and DeepSeek’s API docs. Watch the exceptions: GPT-5.6 Sol is at a promotional rate through 21 Nov 2026 (list $5/$30); Gemini 3.1 Pro charges $4/$18 once a prompt passes 200K tokens; Claude Haiku 5.5’s rate shown covers prompts up to 100K tokens ($0.50/$2.50 above that). Cached rate = the provider’s cache-read price where one is published. Estimates only — confirm on the provider’s page before budgeting.

Token estimates from pasted text use the rough rule of ~4 characters per token for English. Real tokenizers differ by model — Anthropic notes Claude 4.7 and later produce roughly 30% more tokens for the same text.