How is the cost calculated?

Cost per request is prompt tokens times the model's input price plus completion tokens times its output price, both priced per million tokens. The monthly projection multiplies that by your requests per day and 30 days.

Why do input and output have different prices?

Providers charge more for output (generated) tokens than input (prompt) tokens because generation is more compute-intensive. That is why output-heavy workloads like long-form writing cost far more than input-heavy ones like classification.

Are these prices current?

They are published list rates in USD per million tokens at the time of the last update, but providers change pricing regularly. Always confirm against each provider's official pricing page before committing to a budget.

Does this account for caching or batch discounts?

No. The calculator uses standard list pricing, so it does not include prompt-caching discounts, batch-API discounts, or volume agreements. Those can reduce real costs substantially, especially for repetitive prompts.

LLM Model Pricing Calculator

Compare LLM costs across every major provider at once

Picking a model on price alone is hard when each provider lists input and output rates separately and the numbers are per million tokens. This calculator collapses all of that into one comparison: enter your typical token counts and request volume, and see the real per-request cost and monthly spend for every current model side by side.

How it works

You provide three numbers — average input tokens, average output tokens, and requests per day. For each model the tool computes cost per request as (input ÷ 1M × input_price) + (output ÷ 1M × output_price), then projects monthly spend by multiplying by your daily volume and 30 days. The table covers OpenAI, Anthropic, Google Gemini, and Mistral, and you can sort by per-request cost, monthly projection, or name to find the right fit. Everything runs client-side.

Tips and notes

Output tokens dominate cost for generation-heavy tasks, so estimate them carefully — a chat assistant that writes long replies can cost several times more than the prompt suggests. The cheapest model is highlighted, but balance price against quality: a mini/flash/haiku tier model is often the right default, with a frontier model reserved for hard requests. These are list prices; prompt caching and batch APIs can cut real spend further, so treat the monthly figure as an upper bound and confirm rates on each provider’s pricing page before budgeting.