AI Token Counter

Token counts are estimates based on average character-per-token ratios. Actual tokenization depends on each model specific tokenizer. Estimates are typically within 10-20% of actual counts for English text.

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Each AI model uses a different tokenizer that splits text into subword pieces differently. GPT-4 uses cl100k_base, while Claude uses its own tokenizer. A word like "unbelievable" might be 1 token in one model and 3 tokens in another, depending on the vocabulary.

Remove unnecessary whitespace, redundant instructions, and filler words from your prompts. Use concise system prompts, avoid repeating context the model already has, and set appropriate max_tokens limits on responses. For large documents, summarize or chunk the content instead of sending it all at once.