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LLM 토큰 카운터

OpenAI 모델은 실제 BPE 토크나이저로 정확히 세고, Claude, Gemini 등 다른 모델은 추정치임을 명확히 표시합니다.

Enter some text to see the count.

사용 방법

  1. Paste the text you want to count.
  2. Pick a model. GPT-4o family and GPT-4/3.5 are counted exactly with the real tokenizer.
  3. Claude, Gemini, Llama and Mistral show an estimate, always labeled as one, with the heuristic stated.

참고 사항

Exact counts run entirely in your browser with gpt-tokenizer (o200k_base / cl100k_base); your text is never sent to a server. Other providers do not publish a browser tokenizer, so this page offers only a character-based estimate for them and never presents it as exact.

자주 묻는 질문

How far off can the estimates be?
For English prose, often within 10–20%, but code, long numbers and CJK text can be far off. Keep a margin when budgeting from an estimate.
Why does Japanese cost more tokens?
BPE tokenizers are trained mostly on English, so a Japanese character typically becomes about one token (sometimes more). You can verify this with the exact GPT counters on this page.