AI API Cost Calculator

AI API providers including OpenAI, Anthropic, and Google charge per token, where a token is roughly four characters of English text. Pricing is typically split between input tokens (your prompt and context) and output tokens (the model's response), with output usually costing more. Monthly cost equals total tokens processed divided by 1,000 (or 1,000,000 for per-million-token pricing) multiplied by the per-token rate for your chosen model. This calculator lets you model usage volume across multiple models.

The best model depends on task complexity and volume. Smaller, faster models like GPT-4o mini, Claude Haiku, and Gemini Flash cost 10 to 50 times less than flagship models like GPT-4o, Claude Sonnet or Opus, and Gemini Pro, while handling a wide range of tasks well. Flagship models are justified for complex reasoning, nuanced writing, or high-stakes decisions where quality matters more than cost. Running A/B tests to verify output quality before committing to a model tier is recommended.

Common causes of higher-than-expected costs include large system prompts or context windows sent with every API call, multi-turn conversation histories that grow with each request, high output token counts for tasks requiring long responses, frequent API calls triggered by user actions rather than batched processing, and using premium models for tasks that cheaper models can handle. Prompt caching features available from Anthropic and OpenAI can significantly reduce costs for repeated context.

A practical rule of thumb is that one token is approximately four characters or three-quarters of a word in English. Most providers offer free tokenizer tools: OpenAI's tokenizer, Anthropic's token counter, and Google's tokenizer. For planning purposes, a typical chatbot interaction (medium system prompt plus user message plus response) might use 500 to 2,000 tokens total. Multiply expected interactions per month by average token count per interaction to project monthly usage and cost.