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Module 06 — Practice: calculate and choose

Time: 120 minutes · Artifact: labs/06-economics/


Task 1. Manual calculation (20 min)

Given:

model A: input $0.25 / 1M, output $1.25 / 1M
model B: input $5.00 / 1M, output $30.00 / 1M

The task: an agent loop of 8 steps, each with ~40k input tokens and ~500 output tokens.

Calculate:

  1. The cost of model A.
  2. The cost of model B.
  3. How many times more expensive B is.
  4. At what number of steps B becomes cheaper, if B solves the task in 3 steps and A in 12?

Acceptance: the calculation, with formulas, in the report.


Task 2. Measure a real session (30 min)

Do the same task two ways:

A) one big session with 3 tasks
B) three separate sessions

Compare:

opencode stats

or the cost counter in the interface.

Record: input/output tokens, cost, time. Draw a conclusion: which is cheaper and why.


Task 3. Cache in action (25 min)

Make 5 similar edits in a row in one session (for example, a rename across 5 files), without changing the instructions.

Then do the same thing, but change AGENTS.md between steps.

Record: the difference in cost (cache hits are visible in the provider/OpenCode statistics). Conclusion: how to structure requests so that the cache works.


Task 4. Model selection table (30 min)

Build a table for your project:

Task Model Why Expected cost
rename fast template $
new tests fast/balanced by example $
new feature balanced needs context $
architectural refactoring frontier needs thinking $
incident analysis from logs long-context 500k tokens $

Acceptance: at least 5 rows with a justification, not "the smartest one".


Task 5. Compare two models on the same task (15 min)

Take a medium-complexity task. Do it on a cheap model and on an expensive one. Compare:

cheap expensive
iterations to green tests
cost
your time on review
diff quality (1–5)

Conclusion: which model is more cost-effective for this class of tasks.


Submission criteria

  • Manual calculation with formulas and an answer to the 3 vs 12 steps question.
  • Real measurements of the two session strategies.
  • Analysis of the cache effect.
  • Model selection table with 5+ rows.
  • Comparison of two models with a conclusion.