AI Model Comparison Calculator
Compare what different models would cost for your actual workload. List each model with its input and output price per million tokens and its context window, then enter the tokens per request and requests per month. The calculator ranks the models by monthly cost, shows the cost per request and how many times more each costs than the cheapest, and flags models whose context window is too small.
- Runs in your browser
- No sign-up
- Free to use
Replace the examples with the models and current prices you are considering.
Prices are placeholders you replace with your provider’s current price list – they change often and differ by model, region and contract. Cost is only one factor: compare quality on your own tasks too.
How to use AI Model Comparison Calculator
- List models: name | input price | output price | context.
- Enter tokens per request.
- Enter requests per month.
- Read the ranking.
AI Model Comparison Calculator features
Same workload
Fair comparison.
Context check
Too-small windows flagged.
Cost ratio
Versus the cheapest.
Your prices
No built-in prices that go out of date.
Paste from spreadsheets
Tab or | separated lines.
Any currency
Choose from 30+ currencies; amounts are formatted for it.
When to use AI Model Comparison Calculator
- Choosing a model for a feature.
- Explaining costs to stakeholders.
- Re-checking after price changes.
- Routing between small and large models.
AI Model Comparison Calculator FAQ
Why example model names?
Prices change often; the examples are placeholders for you to replace with current names and prices.
Is the cheapest model the best choice?
Only if it is good enough. Test quality on your own tasks.
What about speed?
Latency and rate limits also matter; check them separately.
Can I combine models?
Many apps route simple requests to small models and hard ones to large models.
Cost is one dimension
Price differences between models can be tenfold or more for the same workload. Comparing on your real token counts avoids decisions based on headline prices.
Combine this with quality tests: a model that needs fewer retries can be cheaper overall.
Prices, limits and tokenizers differ between providers and change often. Enter the current values from your provider’s pricing and documentation pages, and re-check them before committing to a budget.
Measure real usage once you have it: average tokens per request in production are often different from the estimates used at the planning stage, especially once system prompts, retrieved context and conversation history are included.