How does NumStack calculate AI token costs?

NumStack uses real published pricing from OpenAI, Anthropic, Google, and other AI providers. Enter your typical usage (input tokens, output tokens, requests per day) to see projected monthly costs across all models.

Why do different AI models have different token prices?

Different models have different computational costs. Smaller models like GPT-4o mini or Haiku are cheaper but less capable. Larger models like GPT-4o or Claude Sonnet are more powerful but cost more per token.

How can I reduce my AI API costs?

Use smaller models for simple tasks, cache repeated prompts, trim output length (output tokens cost 3-5x more than input), and batch requests instead of real-time when latency allows.

NumStack

AI Token Cost Calculator

Know your AI spending. Find where you could save. 30+ models. Real pricing. No guessing.

Your Usage

Enter your typical AI usage patterns to see your monthly costs

Why AI token costs are hard to predict

Every AI model prices input and output tokens differently — and the difference can be 10x between models. GPT-4o, Claude Sonnet, and Gemini Flash all have different sweet spots depending on your prompt length and response size.

NumStack pulls real published pricing from Anthropic, OpenAI, Google, and others so you can compare apples-to-apples before you commit to a model. Enter your typical usage pattern above to see your projected monthly spend across all 30+ models at once.

How to reduce your AI API costs

•Use smaller models (Haiku, GPT-4o mini, Gemini Flash) for simple tasks
•Cache repeated system prompts where supported
•Trim output length — output tokens cost 3-5x more than input
•Batch requests instead of real-time where latency allows
•Use the NumStack API to automate cost tracking in your CI/CD pipeline

🔌 Want to automate this? Use the NumStack API to calculate costs programmatically in your own apps.