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AI API Pricing Calculator

Calculate the cost of using AI model APIs based on your token usage.

Configuration
Result
$0.00
Daily Cost
Monthly Cost$0.00
Yearly Cost$0.00
Per request$0.000
Total tokens/day0
Estimates only. Prices are per 1M tokens. Updated 2026-07-25. Check provider pricing for accuracy.

Overview

Estimate API costs based on tokens, model, and volume.

Best for

  • Forecast monthly spend.
  • Compare pricing across models.
  • Forecast monthly spend for a feature.

Step-by-step

  1. Select a model and pricing tier.
  2. Enter input/output tokens or sample text.
  3. Review the total estimate.

Examples

Example 1
Input
Input 100k, Output 20k, Model: X
Output
Estimated cost: $12.50
Calculates total cost from tokens.
Example 2
Input
Requests: 10k/month
Output
Monthly estimate: $85
Scales by volume.
Example 3
Input
Input 50k, Output 10k, Requests 2k
Output
Monthly estimate: $85
Volume multiplies token cost.

Common mistakes

  • Ignoring output tokens underestimates cost.
  • Promo pricing may expire.
  • Ignoring retries can underestimate cost.

Pro tips

  • Model a min/avg/max range.
  • Cache outputs to reduce spend.

FAQ

Are taxes included?
No, estimates exclude taxes and currency conversion.
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

Founders, PMs, and operators modeling how request volume and output length change the cost of an AI workflow.

What this output still does not decide

Cost output is only as good as the pricing assumptions and does not capture taxes, monitoring overhead, or operational waste.

Review before you share or ship
  • The current provider pricing page and any cached, batch, or free-tier rules.
  • Retry behavior, peak usage spikes, and hidden tokens outside the visible prompt.
  • What part of the spend is fixed versus what grows linearly with traffic.
A practical workflow that keeps this page useful
  1. Model one normal week and one peak week instead of trusting a single average.
  2. Include realistic output sizes and retry assumptions.
  3. Compare the result with the provider's official pricing documentation.
  4. Recalculate whenever prompt structure or model choice changes.
Best next step

Keep this estimate tied to the real pricing source so it stays a planning tool instead of becoming stale presentation math.

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