API Cost Calculator
Struggling to estimate your AI API expenses? Our API Cost Calculator helps you predict costs for OpenAI, Anthropic, and Google AI models before you scale. Enter your token usage and see exactly what you'll pay per request, per day, and per month.
Calculate Your API Costs
Enter your token usage to calculate API costs
How It Works
AI API providers like OpenAI, Anthropic, and Google charge based on tokens - the basic units of text that their models process. One token is roughly 4 characters or about ¾ of a word. Costs are typically quoted per million tokens.
- Select your provider and model - Different models have vastly different pricing
- Estimate your tokens - Input tokens (your prompt) and output tokens (AI response)
- Enter daily volume - How many API calls you expect to make
- View your costs - See per-request, daily, monthly, and yearly projections
📐 The Formula
Cost per Request =
(Input Tokens ÷ 1,000,000 × Input Rate) + (Output Tokens ÷ 1,000,000 × Output Rate)
Monthly Cost = Cost per Request × Requests per Day × 30
Note: Output tokens are typically 2-4x more expensive than input tokens because generating new text requires more computational resources than processing existing text.
📊 Example Calculation
Let's calculate the cost for a typical chatbot using GPT-4o:
🎯 Use Cases
💬 Chatbots & Assistants
Estimate costs for customer service bots, virtual assistants, and conversational AI applications.
📝 Content Generation
Calculate costs for blog writing, product descriptions, email drafting, and marketing copy.
🔍 Data Analysis
Budget for document summarization, sentiment analysis, and data extraction tasks.
💻 Code Assistance
Plan costs for code generation, debugging, documentation, and code review tools.
❓ Frequently Asked Questions
What is a token in AI APIs?
A token is the basic unit of text that AI models process. In English, one token is roughly 4 characters or about ¾ of a word. For example, "Hello, world!" is about 4 tokens. Different languages may have different token-to-character ratios.
Why are output tokens more expensive than input tokens?
Generating new text (output) requires the model to run inference and produce each token sequentially, which is computationally intensive. Processing input text is faster since it can be done in parallel.
How do I reduce my API costs?
Use smaller, cheaper models when possible (GPT-4o-mini vs GPT-4o). Optimize prompts to be concise. Cache responses for repeated queries. Set max_tokens limits to prevent unexpectedly long responses. Use batch processing for non-real-time tasks.
How accurate is this calculator?
This calculator uses current published pricing from each provider. Actual costs may vary based on volume discounts, enterprise agreements, or pricing changes. Always verify with the official pricing pages before budgeting.
Which model should I choose?
Start with smaller models (GPT-4o-mini, Claude Haiku, Gemini Flash) for simple tasks. Use flagship models (GPT-4o, Claude Sonnet, Gemini Pro) for complex reasoning. Reserve premium models (o1, Claude Opus) for tasks requiring advanced problem-solving.