AI Cost Calculator

Calculate the cost of AI API usage across different models and providers. Enter your token usage and pricing to get accurate cost estimates for OpenAI GPT, Anthropic Claude, or any custom AI model pricing structure.

Updated June 2026 · How this works

Input tokens

Output tokens

Input price per 1K tokens

Output price per 1K tokens

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How It Works

The formula, explained simply

The AI cost calculator determines the total expense of using AI APIs by calculating separate costs for input and output tokens, then combining them for a complete request cost.

AI providers like OpenAI, Anthropic, and others charge based on token usage rather than fixed fees. Tokens represent pieces of text - roughly 4 characters or 0.75 words in English. Each API request consumes input tokens (your prompt) and generates output tokens (the AI's response), with different pricing for each type.

The calculation process involves dividing your token counts by 1000 (since pricing is typically per 1K tokens), then multiplying by the respective rates. For example, if you use 2000 input tokens at $0.0015 per 1K tokens, the input cost is (2000 ÷ 1000) × $0.0015 = $0.003. Output tokens are calculated the same way but usually cost more due to the computational effort required to generate new text.

Understanding token-based pricing helps optimize your AI usage costs. Shorter, more focused prompts reduce input tokens, while setting appropriate response length limits controls output tokens. This calculator lets you estimate costs before making API calls or analyze spending patterns across different models and use cases.

When To Use This

Right tool, right situation

Use this calculator when budgeting AI projects, comparing costs across different models, optimizing prompts for cost efficiency, or tracking API spending. It's essential for businesses planning AI integration, developers choosing between model options, and anyone wanting to understand their AI usage expenses before scaling up.

Common Mistakes

Why results sometimes look wrong

Common AI cost calculation mistakes include confusing per-token with per-1K-token pricing, using the same rate for both input and output tokens, and forgetting to account for system messages or conversation history in multi-turn chats. Always verify pricing units and distinguish between input and output rates.

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The Math

Worked examples and deeper derivation

AI cost calculation uses straightforward multiplication and division:

Input Cost = (Input Tokens ÷ 1000) × Input Price per 1K Output Cost = (Output Tokens ÷ 1000) × Output Price per 1K Total Cost = Input Cost + Output Cost

For example, with 1500 input tokens, 800 output tokens, $0.003 input pricing, and $0.006 output pricing: Input Cost = (1500 ÷ 1000) × $0.003 = $0.0045 Output Cost = (800 ÷ 1000) × $0.006 = $0.0048 Total Cost = $0.0045 + $0.0048 = $0.0093

OpenAI GPT-3.5 Turbo request

1500 input tokens, 800 output tokens, $0.0015 input price, $0.002 output price

Total cost is $0.0039 for this API call with mixed input and output usage.

Large Claude 3 analysis task

5000 input tokens, 2000 output tokens, $0.008 input price, $0.024 output price

Total cost is $0.0880 for processing a large document with detailed AI analysis.

Custom model deployment

800 input tokens, 1200 output tokens, $0.001 input price, $0.0015 output price

Total cost is $0.0026 for this custom model with lower per-token pricing.

Common questions

How do I calculate OpenAI API costs per request?

To calculate OpenAI API costs, multiply your input tokens by the input price per 1K tokens, multiply output tokens by the output price per 1K tokens, then add both costs together. OpenAI charges different rates for input and output tokens, with output tokens typically costing more.

What is the difference between input and output token pricing?

Input tokens are the text you send to the AI (your prompt), while output tokens are the text the AI generates in response. Most AI providers charge more for output tokens because generating text requires more computational resources than processing existing text.

How can I reduce my AI API costs?

Reduce AI API costs by optimizing prompts to be concise, using smaller models when possible, limiting output length with max_tokens parameters, and batching requests. Consider using cheaper models like GPT-3.5 instead of GPT-4 for simpler tasks to cut costs significantly.

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