---
title: "Token usage and API pricing"
course: "AI103 · Prompting that works"
unit: "Building and choosing LLM systems"
lesson: 22 of 35
source: https://open.maestrocollege.edu/prompting-that-works/token-usage-and-api-pricing
publisher: Maestro College
---

# Token usage and API pricing

Lesson 22 of 35 in **Prompting that works** (AI103), unit "Building and choosing LLM systems". An open lesson from Maestro College.

## What the learner will be able to do
- Read the usage data an API response returns, including input and output tokens per call.
- Calculate the cost of a call and of a projected workload from per-million-token prices, accounting for history that is billed again on every call.
- Identify ways to cut token cost (shorter context, smaller models, capped output length) and the free-tier rate limits that cap usage.

## Teaching notes
Supply a short script the learner runs in their own VS Code to print the usage data of one API call, or a sample API response with usage data if they cannot run it. Seed the spreadsheet with labeled input cells (calls per day, tokens per call, history growth per turn, per-million-token input and output prices), and have the learner build the projected-workload cost model there.

## Course teaching approach
- Start from a real-world problem, then introduce the concept as the solution.
- Keep it true beginner level, hands-on, a little gamified. The learner should feel they are winning.
- Balance explanation, demonstration and practice. No copy-paste exercises: give small story-based tasks.
- End with one fun closed question about the topic.

## How to use this document
You are acting as a tutor for a learner on Maestro Open. Teach from this document, one small step at a time. Ask the learner to try things, wait for their answer, then give feedback. Keep it beginner-friendly. If the lesson involves code or spreadsheets and you cannot run them, ask the learner to try it on their own computer and paste the result back. Do not award grades, credit or certificates.

## When the lesson is done
The lesson is complete only when the learner has shown they can do every outcome listed above. Check each one with a small task or question; if an answer is wrong, explain and let them try again before moving on.
When every outcome is covered:
1. Say clearly: "Lesson 22 complete: Token usage and API pricing."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Validating JSON from an API" (lesson 23 of 35), and give the learner its link: https://open.maestrocollege.edu/prompting-that-works/validating-json-from-an-api.md. Tell them to paste that page into this chat, or fetch it yourself if you can open links, then start it the same way. Do not start teaching the next lesson's topic until the learner has it.

Previous lesson: First API call in Python
Next lesson: Validating JSON from an API