Prompt Engineering

Token Counter for AI Prompts

Paste a prompt, get an honest token estimate — a range, not a fake-precise number — plus the cost across GPT, Claude, and Gemini.

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Overview

A token is the unit models actually read and bill, and it is neither a character nor a word. This loads a typical assistant prompt and counts it: an estimated token range (because tokenizers genuinely disagree on the same text), the same text's count across four models, and what one call costs versus a thousand. The number is honest about its own uncertainty — that is the point of an estimator that refuses to lie with false precision.

How to use this resource

Paste the prompt

Any text — the report shows counts only, never echoes your content.
Read the range

Tokenizers disagree, so the estimate is a range with the model comparison beside it.
Check the cost

Per call looks trivial; the per-1,000-calls line is the real budget.

Why This Works

A range is honest where a single number would be a lie — tokenizers really do differ
Content-type detection adjusts the estimate for prose, code, and CJK
The cost line turns an abstract count into a number you can budget against

Best for

Getting a quick, honest token count
Sanity-checking a prompt before an API call
Comparing the same text across models

Not for

Deciding whether content fits a context window — that's the Context Window Estimator
Counting characters or words for a text limit — that's the Character Counter

FAQ

Why does the token counter show a range instead of one exact number?

Because tokenizers genuinely disagree on the same text, so a single figure would be false precision. This report gives 'Estimated tokens: ~70 (range 63–77)' and a per-model line — 'GPT-5 ~70 · Claude Opus ~73 · Claude Sonnet ~73 · Gemini Pro ~70' — to show the spread. The ESTIMATION NOTES are explicit that these are character-based estimates, not tokenizer output.

Does token count change between GPT, Claude, and Gemini for the same prompt?

Yes, and the MODEL NOTES list all four for one text so you can compare. The same prompt estimates at GPT-5 ~70, Claude Opus ~73, Claude Sonnet ~73, and Gemini Pro ~70, because each provider tokenizes differently. The note adds these are a count, not a fit check — for 'will it fit?' use the Context Window Estimator.

Can I trust the cost estimate for my actual API bill?

Treat it as a budgeting estimate, not exact billing. The report prices this prompt on GPT-5 and warns that pricing is approximate and 'providers change rates — verify before relying on a number', while the token figure itself is a range, not tokenizer output. The per-1,000-calls line is the honest place to budget, but confirm the real rate with your provider.

Customize This Resource

Opens this text in Token Counter. Count to get the full token and cost report — then adjust the model and assumed response length.

Open in Token Counter

Prompt Template

Copy it as-is, or use Open in Token Counter to load it pre-filled and customize it with your own context.

TOKEN COUNT REPORT

TOKEN ESTIMATE
- Estimated tokens: ~70 (range 63–77)
- Characters: 274
- Words: 45
- Detected content type: Prose
- Tokens per word (approx): 1.6
- Tokens per character (approx): 0.3

COST ESTIMATE — GPT-5
- Pricing (approximate, June 2026): input $1.25/1M tokens · output $10.00/1M tokens
- Input cost (this prompt): $0.000079–$0.000096
- Assumed response: Medium response (~800 tokens) -> output cost $0.008000
- Combined per call: $0.008079–$0.008096
- Per 1,000 calls: $8.08–$8.10

MODEL NOTES
- OpenAI tokenizer (o200k-class) — English averages roughly 4 characters per token.
- Same text, estimated per model: GPT-5 ~70 · Claude Opus ~73 · Claude Sonnet ~73 · Gemini Pro ~70 (a count, not a fit check — for "will it fit?" use the Context Window Estimator).

USAGE GUIDANCE
- For scale on GPT-5: a short prompt ≈ 71, a medium prompt ≈ 506, a large prompt ≈ 3,031 tokens.
- This text is closest to a short prompt.
- A single call looks cheap; the per-1,000-calls line is where token cost becomes real — budget on volume, not on one request.

ESTIMATION NOTES
- A token is not a character and not a word — it is a sub-word chunk. English averages ~4 characters / ~0.75 words per token.
- Estimates vary by tokenizer: the same text tokenizes differently on GPT, Claude, and Gemini — that is why this is a range, not a single number.
- Language matters: CJK and many non-Latin scripts use more tokens per character than English.
- Code differs from prose: symbols, indentation, and punctuation push code to more tokens per character.
- These are character-based ESTIMATES, not tokenizer output. Pricing is approximate as of June 2026; providers change rates — verify before relying on a number.

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Related tools

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Token Counter

Estimate how many tokens a prompt is and what it costs — honest ranges across GPT, Claude, and Gemini, with per-call and per-1,000-call pricing.

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