How many words is 1000 tokens?

For most models (GPT, Gemini, Llama), 1000 tokens is approximately 750 words based on the standard 1.33 tokens-per-word ratio. Claude models average 1.20 tokens per word, so 1000 Claude tokens ≈ 833 words.

Do different AI models count tokens differently?

Yes. Each model family uses its own tokenizer. OpenAI (GPT) and most open-source models average about 1.33 tokens per word. Anthropic's Claude tokenizer is slightly more efficient at ~1.20 tokens per word.

What is the token-to-word ratio for GPT?

GPT models use OpenAI's cl100k_base tokenizer, which produces approximately 1.33 tokens per word for standard English text. That means every 100 words ≈ 133 tokens.

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Tokens-to-Words Converter

Convert token counts to estimated words, characters, and pages — or reverse from words to tokens. Supports all major AI models including GPT, Claude, and Gemini.

The Tokens-to-Words Converter translates between the two units AI developers work with most: tokens and words. Enter a token count to get an estimated word count, character count, and page equivalent — or switch to reverse mode and enter a word count to find out how many tokens it will consume.

The conversion ratio is not fixed. Each AI model uses its own tokenizer, and the same 1000 tokens can represent significantly different amounts of text depending on the provider. GPT-5.5 uses an efficient tokenizer where 1 token averages roughly 0.75 words; other models may produce different ratios for the same content, especially with technical language, code, or non-English text.

Select the model that matches your use case to get the most accurate estimate for your specific tokenizer.

Token count

Model

1 token ≈ 0.75 words for GPT-5.5 (Spud)

Estimated Words

752

Characters

4,000

Pages

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