How this AI token calculator works
Large language model APIs usually bill by tokens rather than by words. This page estimates token usage from your prompt, adds the expected output length, and applies the selected model's per-million-token input and output prices.
The token count is an approximation. English text, code, punctuation, whitespace and CJK characters can be split differently by each provider's tokenizer, so the final billed number may not match this estimate exactly.
Use the estimate to compare prompt sizes, model choices and expected output length before sending production traffic. For final budgeting, check the provider's current pricing, tokenizer behaviour, caching rules and account-specific settings.
Local processing note
The prompt estimate runs in your browser. This page does not require API keys and does not call the selected model to calculate the estimate.
Good use cases
- Estimate whether a prompt is likely to fit within a model's context window.
- Compare high-quality and low-cost models before building an API workflow.
- Estimate the cost of a batch job with hundreds or thousands of similar calls.
- Adjust expected output length to understand why generated text can dominate cost.
Is the token estimate exact?
No. It is a planning estimate. Exact token counts depend on the model tokenizer, message format, system prompts, tool definitions and provider billing rules.
Why are output tokens often more expensive?
Generating text is usually priced higher than reading input. That is why long answers can cost more than the prompt that triggered them.
Does this include cached tokens or batch discounts?
No. The main calculation uses standard input and output token prices only. Cached tokens, batch mode, regional processing and tool usage can change the final cost.