LLM Token Pricing Explained: How to Calculate and Cut Your API Costs

Understanding Token Pricing

LLM API pricing revolves around tokens — the basic units of text that models process. Understanding how tokens translate to costs is essential for budgeting and optimization. Most providers charge separately for input tokens (your prompt) and output tokens (the model's response), with output tokens typically costing more.

Input vs Output Pricing

Input tokens include your system prompt, conversation history, and current message. Output tokens are what the model generates. Since output tokens often cost 2-4x more than input tokens, optimizing your prompts to be concise while still effective can significantly reduce costs.

Prompt Caching

Many providers offer prompt caching — when the same prefix is used across multiple requests, it's cached and billed at a fraction of the normal rate (often 10%). Structure your system prompts and conversation history to maximize cache hits. Our platform supports caching for all major models, with cache hits clearly visible in your usage dashboard.

Cost-Saving Strategies

• Use shorter system prompts where possible
• Select the smallest model that meets your quality requirements
• Monitor your usage dashboard regularly