AI Token Counter

A token is the basic unit AI models use to process text. In English, one token is roughly 3–4 characters or 0.75 words, "chatbot" is one token, "chatbots are useful" is four. Models charge per token for both input and output, so understanding token counts helps you predict API costs before you build.

Each model family uses its own tokenizer. GPT-4o uses the cl100k_base tokenizer, Claude uses a similar BPE approach, and Gemini uses SentencePiece. The same text can produce slightly different counts, usually within 5–10%. The differences become more meaningful at high call volumes when budgeting.

No. All token counting runs entirely in your browser using JavaScript. Your text is never sent to any server, stored, or logged. You can verify this by opening browser dev tools and checking the Network tab, there are no outbound API calls when you paste text.

Reading time divides your word count by a default reading speed of 225 words per minute, the average adult pace. You can adjust this with the WPM slider. Slow readers typically read at 150 WPM; fast readers at 300+ WPM. This is useful for content creators estimating how long readers will spend with their copy.

Input token counts are similar across all major models for the same English text. Where counts diverge is with code or non-Latin scripts, some models handle these more efficiently. Output token counts depend on model behavior and the generated response, not the input tokenizer.

Yes. There is no hard token limit. Counting large documents may take a moment since all processing runs in your browser, but results will be accurate. For very long documents, the paragraph count and reading time metrics are especially useful for spotting structural issues.