See exactly how a model splits your text into tokens — and what that split costs in budget and context.
Try this Paste real text or a code snippet and watch the live token count. Switch the model to compare how GPT-4o, Gemini, Claude, and Llama tokenize the same text. Toggle “as chat message” to reveal the hidden chat-template overhead you also pay for. Good to know A token is not a word: common words are one token, rare words and code split into several. Cyrillic and source code usually cost 2–3× more tokens than the same amount of English prose. Claude and Gemini counts come from a live call to the provider’s API (marked Verified) when the backend is reachable; if that call fails, the tool honestly falls back to an Approximate count instead of guessing silently. Some models can generate hidden reasoning tokens that get billed as output but never appear in the visible response — this tool can’t count them, since that number is only decided when the model actually generates a reply. Ask Synapse
Why is the count for Claude approximate? What are hidden reasoning tokens? Why does Cyrillic cost more tokens than English?
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Still in training — may invent facts. Verify before you trust it.