AI Token Counter

What is AI Token Counter?

Tokens are the fundamental unit that large language models use to process text. A token is not the same as a word — in English, a token is typically 3–4 characters, meaning an average word is 1–2 tokens. Punctuation, whitespace, and subword pieces all become separate tokens. This tool uses per-model character-ratio heuristics that match the real tokenisers within about 3–5% for typical English text.

How to use this tool

1. 1 Select your model from the dropdown — GPT-4o, GPT-4o mini, Claude 3.5 Sonnet, Gemini, Llama 3, Mistral, or others.
2. 2 Paste your system prompt, user message, document, or any text into the textarea. Token count, character count, word count, and line count update in real time.
3. 3 Check the context window usage bar — it shifts amber at 75% and red at 90%, which are danger zones for long conversations.
4. 4 Read the estimated input cost based on published API pricing, and switch models to compare how the same text affects cost across providers.

When would you use this?

• Prompt engineers staying within context window limits when designing multi-turn conversations or RAG retrieval chunks.
• API developers estimating call costs before running experiments at scale — a prompt can easily be 500–1000 tokens of system instructions.
• Content teams checking whether an article will fit in a single LLM call for summarisation.
• Model evaluators comparing how different models tokenise the same input to understand relative token efficiency.

Related tools