How much does tokenizer choice affect cost?
Need to compare how tokenizer choice affects token count and cost? Tokens are the unit AI providers bill in, and getting the count wrong throws off every cost estimate. This page helps teams comparing models get an accurate count and the cost that follows from it.
Results update automatically as you type.
- Tokens
- 1,333
- Words
- 1,000
- Characters
- 5,332
- Input cost at this model(GPT-4o)
- $0.00333
| Prose / English | 4 | 1,333 |
| JSON | 3.5 | 1,523 |
| Code | 3.3 | 1,616 |
| Non-Latin / other | 2 | 2,666 |
Why this isn't trivial
The part people underestimate: different tokenizers encode the same text into different token counts, so cost comparisons must account for tokenizer, not just price. In practice the biggest savings come from comparing models on tokens-for-your-text, not list price alone, so it is worth modelling before you commit.
How it's calculated
We estimate this by tokenizing identical text with each model's tokenizer and pricing the result. Every figure uses the current provider prices baked into the site (reviewed daily), and you can override any input to match your own assumptions.
Frequently asked questions
Do tokenizers really differ?+
Yes — the same text can be more or fewer tokens depending on the model.
Why does this matter for cost?+
A cheaper per-token model can lose if its tokenizer produces more tokens.
Are these prices up to date?+
Yes. The model prices behind this calculator are refreshed and reviewed daily, so your estimate reflects current provider rates rather than a stale snapshot.
Related
Estimates for planning. Pricing data last reviewed 18 September 2026.