300 words
- Tokens from words ≈ 300 × 1.33 = 399
- Tokens from chars (1500) ≈ 375
- Estimated tokens ≈ 399
tech calculator
Token Estimator
Estimate token count from words or characters as a quick budgeting tool for LLM/API usage.
Results
- Tokens (from words heuristic)
- 399
- Tokens (from chars heuristic)
- 375
- Estimated tokens
- 399
How to use this calculator
- Enter word count and/or character count for your text.
- Review token estimates from each heuristic.
- Use the estimated token count to budget API costs.
Inputs explained
- Words
- Count of words in your prompt/completion content.
- Characters
- Character count (including spaces); useful if word count not available.
How it works
Tokens from words ≈ Words × 1.33 (since ~0.75 words per token).
Tokens from characters ≈ Characters ÷ 4 (common char/token heuristic).
We show both and take the higher as a conservative estimate.
Formula
Tokens from words ≈ Words × 1.33 Tokens from chars ≈ Characters ÷ 4 Estimated tokens = max(tokensFromWords, tokensFromChars)
When to use it
- Budgeting prompt/completion token usage before calling an API.
- Sanity-checking content length for pricing estimators.
- Estimating batch job token costs without running a tokenizer.
Tips & cautions
- These heuristics vary by language/content; for precise counts, use the model’s tokenizer.
- Take the higher of the two estimates to stay conservative on cost.
- If you have only one metric (words or chars), enter it and leave the other at default.
- Heuristics only; actual tokenization varies by model and language.
- Does not account for encoding-specific quirks (e.g., many symbols/emojis).
- For exact counts, use the model’s tokenizer.
Worked examples
800 words
- Tokens from words ≈ 1,064
- Tokens from chars (4000) ≈ 1,000
- Estimated tokens ≈ 1,064
Deep dive
Estimate tokens from words or characters to budget LLM/API usage without running a tokenizer.
Uses common heuristics (~0.75 words/token, ~4 chars/token) for quick planning.
FAQs
- How accurate is this?
- It’s a heuristic. Expect variance by language, symbols, and tokenizer. Use model-specific tokenizers for precision.
- Which estimate should I use?
- Use the higher estimate to stay conservative on cost planning.
- Does this handle multiple documents?
- Enter combined words/chars for all documents to get a batch estimate.
- Can I plug this into cost calculators?
- Yes—combine with your per-1k token rate to estimate spend.
- Why 1.33 and 4?
- Common rules of thumb: ~0.75 words/token and ~4 characters/token across many English texts.
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Heuristic estimate only. For billing-critical scenarios, run the model’s tokenizer to get exact token counts.