Tokenomics
The economic framework around token-based pricing for AI API services, including cost per token, input vs output pricing, and optimization strategies.
Why It Matters
Tokenomics directly impacts the business viability of AI applications. A 10x cost difference between models can make or break a product's unit economics.
Example
GPT-4o costs $2.50/1M input tokens while GPT-4o-mini costs $0.15/1M — choosing the right model for each task can reduce costs by 16x.
Think of it like...
Like the economics of mobile data plans — understanding per-unit costs and optimizing usage patterns is essential for keeping your AI application profitable.
Related Terms
Token
The basic unit of text that language models process. A token can be a word, part of a word, or a punctuation mark. Text is broken into tokens before being fed into an LLM, and the model generates output one token at a time.
API
Application Programming Interface — a set of rules and protocols that allow different software applications to communicate with each other. In AI, APIs let developers integrate AI capabilities into their applications.
Inference
The process of using a trained model to make predictions on new, previously unseen data. Inference is what happens when an AI model is deployed and actively serving results to users.