Token Counter client-side ?
How to use Token CounterThe token counter estimates how many tokens a text or prompt will use for a large language model (GPT, Claude…). Models don't read characters but tokens - word fragments - and that unit drives both the cost of an API call and how much room you take in the context window. The tool shows characters, words and lines, a token estimate (about 4 characters per token), and whether your text fits common context windows from 8K to 1M.
The estimate is approximate: each model has its own tokenizer, and splitting varies with language and the presence of code. For precise budgeting, keep a margin. Your text is never uploaded - everything runs in your browser
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The token counter estimates how many tokens a text or prompt will use for a large language model (GPT, Claude…). Models don't read characters but tokens - word fragments - and that unit drives both the cost of an API call and how much room you take in the context window. The tool shows characters, words and lines, a token estimate (about 4 characters per token), and whether your text fits common context windows from 8K to 1M. The estimate is approximate: each model has its own tokenizer, and splitting varies with language and the presence of code. For precise budgeting, keep a margin. Your text is never uploaded - everything runs in your browser
The token counter estimates how many tokens a text or prompt will use for a large language model (GPT, Claude…)
How to use Token Counter
The token counter estimates how many tokens a text or prompt will use for a large language model (GPT, Claude…). Models don't read characters but tokens - word fragments - and that unit drives both the cost of an API call and how much room you take in the context window. The tool shows characters, words and lines, a token estimate (about 4 characters per token), and whether your text fits common context windows from 8K to 1M. The estimate is approximate: each model has its own tokenizer, and splitting varies with language and the presence of code. For precise budgeting, keep a margin. Your text is never uploaded - everything runs in your browser
Frequently asked questions
Is the count exact?
It's an estimate (~4 chars/token). The real number depends on the model's tokenizer and the language; keep a margin for precise budgeting
Why count tokens?
LLM APIs bill per token and cap context size. Estimating tokens helps control cost and check that a prompt fits the window
Is my text sent anywhere?
No, counting is 100% local to your browser