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A tokens to words calculator estimates the relationship between AI language model tokens and human-readable words. Tokenization splits text into subword units — most English words are 1–2 tokens.
Fórmula
words ≈ tokens × 0.75 (rough estimate; varies by tokenizer)
- T
- Tokens (tokens) — LLM token count
- W
- Words (words) — Approximate English word count
Guia passo a passo
- 1Rule of thumb: 1 token ≈ 0.75 words (or 4 characters)
- 21,000 tokens ≈ 750 words ≈ 3 pages A4
- 3Common words are usually 1 token; rare words may be 2–4 tokens
- 4GPT-4 context limit: 128K tokens ≈ 96,000 words
Exemplos resolvidos
Entrada
1,000 words
Resultado
~1,333 tokens
Entrada
128,000 tokens (GPT-4 context)
Resultado
~96,000 words or ~384 A4 pages
Entrada
1 token
Resultado
~0.75 words or ~4 characters
Perguntas frequentes
Why is the conversion approximate?
Different tokenizers (OpenAI, Anthropic, etc.) split text differently. BPE tokenization is probabilistic. A rough rule: 4 tokens ≈ 3 words.
What is a token?
A token is a subword unit. Common words = 1 token; rare words or punctuation = multiple tokens. Special tokens and formatting add overhead.
How accurate is the conversion?
For English, the 0.75 factor is a rough guideline. Expect ±10–20% variance depending on text complexity, language, and tokenizer.
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