Tokenomics of AI
The economics of token-based pricing in AI APIs, including cost per input/output token, strategies for cost optimization, and the financial implications of different model choices.
Why It Matters
Understanding AI tokenomics is essential for budgeting and scaling AI applications. A 10x difference in token price between models can make or break a business case.
Example
Choosing GPT-4o mini at $0.15/1M input tokens for simple tasks versus GPT-4o at $2.50/1M for complex reasoning — matching model capability to task requirements for cost efficiency.
Think of it like...
Like choosing between first class and economy on flights — both get you there, and matching the ticket class to the trip type optimizes your travel budget.
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.