#459 · AI Cost Tool

AI Model Comparison Calculator

Compare estimated cost across OpenAI, Claude, Gemini, and custom model pricing for the same workload.

Calculator

Model comparison inputs
tokens
tokens
req
$
$
$
$
$
$
$
$
Pricing reference date: 2026-06-19. Default rates are editable estimates. Verify current provider pricing before final budgeting.
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Growth forecast

ScenarioMonthly Cost
Current usage—
+25% growth—
+50% growth—
+100% growth—
Annual projection—
3-year projection—

Cost Breakdown

MetricValue
Main result—
Monthly / unit metric—
Annual / secondary metric—
Status—

How to use this calculator

  1. Enter the same workload for every model.
  2. Edit provider input and output token prices.
  3. Calculate monthly cost for each model.
  4. Review cheapest, most expensive, and savings.
  5. Use the result for routing or budget planning.

What the result means

The calculator compares cost only. The cheapest model may not be the best model if quality, latency, or reliability differs.

Model cost = requests × ((input tokens × input price) + (output tokens × output price)) ÷ 1,000,000.

Default prices are editable planning assumptions. Always verify current official pricing before committing to a vendor.

Example calculation

A workload with 100,000 monthly requests, 4,000 input tokens, and 1,000 output tokens can vary dramatically by model price.

Tips for better results

  • Compare quality and cost together.
  • Use small models for simple tasks.
  • Route complex tasks to stronger models.
  • Recalculate after price updates.

FAQ

What is AI model comparison?

AI model comparison estimates how much the same workload would cost across different model providers or custom pricing assumptions.

How is AI model comparison calculated?

The calculator combines your usage assumptions with editable prices, fixed costs, and volume assumptions to estimate cost, savings, or capacity.

Is this estimate accurate?

It is a planning estimate. Actual bills can differ because providers change prices, apply tiers, add taxes, or bill extra features separately.

What affects the result most?

The largest drivers are usage volume, output length, tool calls, review work, fixed platform costs, and the price per unit you enter.

How can I improve the result?

Reduce unnecessary tokens, batch low-priority work, use smaller models where possible, cache repeated context, and review provider pricing regularly.

What are common mistakes?

Common mistakes include ignoring retries, forgetting fixed monthly costs, using outdated token prices, and assuming every task needs the most expensive model.

When should I use this calculator?

Use it before launching, scaling, or changing an AI workflow so you can estimate budget impact before real usage grows.

Sensitivity analysis

ScenarioEstimate
Current usage—
+25% usage—
+50% usage—
+100% usage—

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