Token Economics
definition
LLM pricing is based on the number of input and output tokens processed, with output tokens typically costing 3-5x more than input tokens. Understanding tokenization, context window costs, and the price differences between models is essential for building agent systems that are economically viable at scale — an unoptimized agent loop can burn through hundreds of dollars per day in production.
LLM pricing is based on the number of input and output tokens processed, with output tokens typically costing 3-5x more than input tokens. Understanding tokenization, context window costs, and the price differences between models is essential for building agent systems that are economically viable at scale — an unoptimized agent loop can burn through hundreds of dollars per day in production. Smart token management through caching, prompt optimization, and model routing can reduce costs by 10x or more without sacrificing quality. This concept connects directly to context window budgeting for maximizing information density, model selection for cost-performance tradeoffs, and context caching for reducing redundant token consumption across repeated calls.