To estimate words to tokens for typical English text, divide the word count by 0.75. For example, 1,000 words is approximately 1,333 tokens. This is not an exact conversion: the tokenizer, language, punctuation, code, numbers, and formatting all change how the same number of words is encoded.
This is an English-language planning estimate, not an exact conversion. Tokenizer, language, punctuation, code, and formatting can change the result.
Paste actual text for a supported tokenizer countWords are reader-facing units, while tokens come from a model vocabulary. One familiar word may remain one token, split into several tokens, or combine with leading whitespace. A words to tokens ratio therefore describes a rough English average, not a tokenizer rule.
Language, uncommon names, punctuation, compact JSON, source code, numbers, emoji, and line breaks can all shift the result. Use this words to tokens calculator for early capacity planning, then count the real text before setting a hard context or cost limit.
A words to tokens estimate is useful before the final text exists, such as budgeting a 2,000-word article or a batch of support transcripts. It is less reliable for multilingual data, code, identifiers, or a complete chat request.
Paste the finished text into the AI token counter, select the model family, and review its accuracy label. Read what an AI token represents when interpreting boundaries, then use the AI token cost calculator to add output, cache, and traffic assumptions.
The words to tokens calculator measured its output with the stated 0.75 English-words-per-token approximation: 1,000 words produces about 1,333 tokens. The main limitation is language and text shape, so code, punctuation, Chinese, URLs, and model-specific tokenization should be checked with the actual text. OpenAI token guide. Last verified: .
| Evidence | Observed result or boundary |
|---|---|
| Words to tokens formula | Words divided by 0.75; 1,000 words is approximately 1,333 tokens. |
| Accuracy boundary | Typical English planning estimate, not an exact provider token count. |
Words to tokens questions
A common English estimate is about 1,333 tokens for 1,000 words. The actual count varies with the tokenizer, language, punctuation, code, and formatting.
No. It uses the approximation that one token is about three-quarters of an English word. Exact word-to-token equivalence does not exist across all text or languages.
No. Chinese and other scripts can have very different token-to-word relationships. Paste representative text into the token counter instead of applying an English ratio.
The words to tokens estimate is suitable for a draft budget before text exists. It is not for production counting; the actual text and provider usage are stronger evidence.