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Token Calculator

Estimate the number of tokens in your text for GPT and other language models.

Enter text to count tokens
Result
0
Estimated Tokens
0
Words
0
Characters
Estimated Cost
GPT-4o$0.000
GPT-4$0.000
Claude Sonnet 4$0.000
Gemini 1.5 Pro$0.000
Gemini Flash$0.000

Overview

Estimate token counts and cost for AI usage.

Best for

  • Budget API usage before running jobs.
  • Compare models by context limits.
  • Estimate budget for a new prompt.

Step-by-step

  1. Paste your text.
  2. Choose a model or tokenizer.
  3. Review tokens and estimated cost.

Examples

Example 1
Input
Hello world
Output
Tokens: 2
Short text uses few tokens.
Example 2
Input
Long prompt...
Output
Tokens: 350 | Est. cost: $0.01
Shows a cost estimate.
Example 3
Input
Prompt: short paragraph
Output
Tokens: ~45
Estimates, not exact counts.

Common mistakes

  • Different models tokenize differently.
  • Counts are estimates, not billing totals.
  • Tokenization differs by model.

Pro tips

  • Keep prompts concise to reduce cost.
  • Include output tokens in your budget.

FAQ

Is this the same as API billing?
No, it's an estimate and may differ from final billing.
Does this upload my data?
No. Everything runs locally in your browser.
Can I use it offline?
Yes. After the page loads, most tools work offline. Some assets (like fonts) may need a connection.

Data & privacy

All processing happens locally in your browser. No data is uploaded or stored.

Why this page is useful in real work

The widget gives you a fast result. This review section explains where that result is genuinely useful and where a second check still matters before you act on it.

Real workflow fit

Teams estimating prompt budgets, request volume, and rough usage ceilings before wiring an API into production.

What this output still does not decide

A token estimate can drift from provider billing because tokenizers, wrapper text, system prompts, and cached paths differ.

Review before you share or ship
  • Model-specific tokenization and pricing rules.
  • Hidden boilerplate such as system prompts, retries, and logging wrappers.
  • Whether the workload has peak cases that are much larger than your sample.
A practical workflow that keeps this page useful
  1. Estimate one representative prompt instead of starting with best-case averages.
  2. Add expected output length and multiply by real request volume.
  3. Model peak and retry scenarios so the budget has a safety margin.
  4. Compare this estimate with live provider dashboards once traffic exists.
Best next step

Keep this calculator in the planning loop, but let live billing and telemetry overrule paper estimates as soon as production data exists.

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