Cost, capacity, and reliability · Lesson 3 of 14 · 6 min

Compare model cost profiles

Model cost comparison should use the same workload and required quality. A cheaper request that repeatedly fails the task may not be the better operating choice.

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learner@clairos:~ $

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-cost-reliability-003.json. Separate the recorded facts from your assumptions.
Hint & worked example
Model cost comparison should use the same workload and required quality. A cheaper request that repeatedly fails the task may not be the better operating choice.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-cost-reliability-003.json
```
Common mistake to avoid: Select the lowest price regardless of whether the task succeeds.
2
Isolate the deciding signal
Select the b_quality_pass field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Hold model B because it failed the required quality gate despite lower unit cost.
A successful JSON query isolates b_quality_pass.
```
jq .b_quality_pass /opt/ai-lab/cases/aiops-cost-reliability-003.json
```
Common mistake to avoid: Using a different case or an unrelated signal as the justification.
3
Record your operational decision
Choose the justified code: hold-cheaper-failure, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-cost-reliability-003-decision.txt.
Hint & worked example
Hold model B because it failed the required quality gate despite lower unit cost.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'hold-cheaper-failure' > /home/learner/lab/aiops-cost-reliability-003-decision.txt
```
Common mistake to avoid: Select the lowest price regardless of whether the task succeeds.

Understand the pattern

Model cost comparison should use the same workload and required quality. A cheaper request that repeatedly fails the task may not be the better operating choice.

Interpret the evidence

Hold model B because it failed the required quality gate despite lower unit cost.

A tempting mistake

Select the lowest price regardless of whether the task succeeds.

All names, measurements, prices, versions, and thresholds in this exercise are fictional training data. The evidence supports this bounded scenario, not a claim about a live provider.

Worked example and expected result

$ cat /opt/ai-lab/cases/aiops-cost-reliability-003.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "model_a_cost": 0.002,
  "model_b_cost": 0.001,
  "a_quality_pass": true,
  "b_quality_pass": false
}

Exit status: 0. The command completed successfully in the training fixture.

$ jq .b_quality_pass /opt/ai-lab/cases/aiops-cost-reliability-003.json

false

Exit status: 0. The command completed successfully in the training fixture.

$ printf '%s\n' 'hold-cheaper-failure' > /home/learner/lab/aiops-cost-reliability-003-decision.txt

(no output; exit 0)

Exit status: 0. The command completed successfully in the training fixture.

Try a variation

Name the assumption that would have to change for “hold-cheaper-failure” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Compare model cost profiles” justify?Make the change now and gather the missing evidence afterward.Hold model B because it failed the required quality gate despite lower unit cost.Select the lowest price regardless of whether the task succeeds.

Apply it elsewhere

A colleague concludes: “Select the lowest price regardless of whether the task succeeds.” What should you do?Reject that conclusion; return to the case evidence and its stated limits.Accept it because the training command completed.Treat this fixture as a live measurement.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Inspect cache effectiveness Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision