Prompt Tokenizer

A prompt tokenizer helps you estimate how many tokens your text will consume when sent to an AI model. Tokens are the units models use to process text — roughly 4 characters or 0.75 words in English. Knowing your token count helps you stay within context limits (e.g., 8K, 32K, 128K) and estimate API costs.

This tool uses a simple approximation: splitting by whitespace and punctuation, then applying a word × 1.3 rule. It is not exact. For precise counts, use OpenAI's official tokenizer or the API response.

Every AI model has a context window — the maximum number of tokens it can process in one request. Exceeding it causes errors or truncation. Token count also drives cost: most APIs charge per token for both input and output.

Before sending a long prompt, estimate its tokens to ensure it fits. If you're building a system prompt plus user messages, add them together. This tool gives you a quick sanity check without leaving your workflow.

The visual breakdown shows how your prompt segments map to estimated tokens. Each 'word' or punctuation chunk gets an approximate token count. Longer or more complex segments (code, numbers, non-English text) often use more tokens per character.

Use this to identify which parts of your prompt consume the most tokens. Sometimes shortening a single section can significantly reduce total count. Remember: this is an approximation. Exact counts require the model's tokenizer.