AI Token Calculator — Tokens to Dollars, Any Model
Who this is for: For developers and API users holding a token count and a model name who need the dollar number — before the invoice arrives.
Turn a token count into dollars on any model — or estimate tokens from text you paste.
Quick answer: Token prices are quoted per 1M tokens and span roughly 300×: input from $0.05 (GPT-5 nano) to $15 (Claude Opus 4.1), output from $0.40 to $75. A million in and a million out costs $11.25 on GPT-5, $18.00 on Claude Sonnet 4.5, $0.70 on DeepSeek V3. Cached input drops to 10% of list on Anthropic. Enter your token counts below.
cached rate $0.125/M
| Formula | tokens ÷ 1M × price per 1M |
|---|---|
| Input band | $0.05 – $15 /1M |
| Output band | $0.40 – $75 /1M |
| Words per token | ≈0.75 words/token (1.3 tokens/word) |
| Cache read | Anthropic 10% · OpenAI 10–50% |
| Status | List prices collected Oct 2026 from each provider's public pricing page. Providers change tiers often — always confirm on the official page before billing decisions. |
How much does one million tokens cost?
Token pricing is quoted per million tokens and differs by an order of magnitude between tiers. Input prices run from $0.05 (GPT-5 nano) to $15 (Claude Opus 4.1) per million; output prices run from $0.40 to $75. The same 1M input + 1M output job costs $11.25 on GPT-5, $18.00 on Claude Sonnet 4.5, $2.25 on GPT-5 mini and $0.70 on DeepSeek V3. Cached input changes the arithmetic further: Anthropic bills cache reads at 10% of base input price and OpenAI at 10–50% depending on model. The calculator below prices any token count against each model's published rate, and can estimate tokens from text you paste in.
Common uses
- Converting a token count into dollars for a chosen model
- Comparing the same workload across providers before switching
- Costing a cached-input workload against the uncached price
- Estimating how many tokens a block of text will consume
Why per-token pricing is hard to compare
Providers quote per million tokens, but the usable work per token varies: a reasoning model may spend thousands of tokens thinking before it answers, and a long agent loop re-sends its tool definitions on every call. Two models at the same list price can differ several-fold in the cost of finishing the same task. Use this calculator to price a known token count accurately, then measure real consumption on your own workload before drawing conclusions about which provider is cheaper.
Frequently Asked Questions
How do I calculate token cost?
How many tokens is a word?
Which model has the cheapest tokens?
Do cached tokens really cost less?
Is my text or data stored?
More API cost
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