What an AI answer really costs
Understand the compute, tokens and money behind AI answers and why prices vary so much
A taste of a lesson
Why does my long chat seem to use up my limit faster as it goes on?
Because the model does not remember the chat between messages; the app sends the whole conversation again each time. Message one might send 500 tokens, but message forty might send 30,000, since all earlier turns ride along. So each new message costs more than the last, and limits are often based on that usage. Fixes: start a fresh chat for a new topic, and carry over a short summary instead of the full history. Quick estimate: if each turn adds 400 tokens, how many tokens does turn 20 send?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Explain why AI is priced by input and output tokens and why output costs more
- Identify what multiplies costs, such as long history, reasoning, images and agent loops
- Estimate the monthly cost of a workload with illustrative prices
- Describe ways to reduce cost, including caching, batching and model choice
Lesson plan
- 1 Tokens are the meter Understand how usage is measured and priced. Start
- 2 What multiplies cost Identify features that drive costs up quickly. Start
- 3 Estimating a workload Build a cost estimate with illustrative prices. Start
- 4 Cutting costs Apply techniques that reduce spending without losing quality. Start
- 5 Free tiers, subscriptions and trends Understand consumer pricing models and long run price trends. Start
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About this tutor
For curious users, managers and early stage builders who want to understand the economics behind AI tools. You learn how providers count input and output tokens, why output usually costs more, why reasoning modes, long contexts, images and agents multiply costs, and how caching and batching reduce them. You see why free tiers exist and have limits, how flat rate subscriptions differ from usage based pricing, and why prices for the same capability have tended to fall while total spending rises. You practise estimating the cost of a realistic workload, without relying on any provider's current price list.
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About the teacher
I explain the kinds of AI models, what they cost to run and how to run one yourself
9 tutors 328 lessons taught Sample
I teach the practical side of modern models: reasoning models, multimodal models, open and closed weights, running a model on your own computer, and the money, energy and hardware behind every answer. I like starting with something you can see or measure, such as the memory a model needs or the number of tokens a task uses, then explaining the...
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