Cost-Quality Pareto Frontier
About This MicroSim
A scatter plot of nine representative model configurations on log-scale cost vs quality. The Pareto frontier (green) connects non-dominated points — those for which no other configuration is both cheaper and higher quality. Dominated points (gray) should never be chosen. Sliders apply quality-floor and cost-ceiling constraints, gray-fading any configuration that fails the test, leaving only the survivors.
How to Use
- Read the green frontier. These are the only configurations worth considering. The dashed line connects them.
- Notice the dominated points. Any gray point — its cost-quality position is strictly worse than some green point. Never pick these.
- Set quality floor to 80. Watch some frontier points fade. Read the survivor list at the bottom.
- Set cost ceiling to $0.01. Combined with quality 80, the survivor set narrows further. Often it collapses to a single configuration — the right pick.
Bloom Level
Evaluate (L5) — judge which model configurations are worth considering for a given workload and which are strictly dominated.
Iframe Embed Code
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Lesson Plan
Audience
Engineers and ML engineers selecting model configurations for production workloads.
Duration
10–15 minutes inside Chapter 3.
Prerequisites
Chapter 3 sections on Cost-Quality Tradeoff, Pareto Frontier, Cached Input Price.
Activities
- Identify the frontier (3 min). Without sliders, name every green point.
- Spot the dominators (3 min). For each gray point, name the green point that strictly dominates it and explain why.
- Apply constraints (5 min). Set quality floor to 85, cost ceiling to $0.05. List the survivors. Argue for the best pick.
Practice Scenarios
| # | Quality floor | Cost ceiling | Survivor |
|---|---|---|---|
| 1 | 0 | $1.00 | (full frontier) |
| 2 | 80 | $0.05 | ? |
| 3 | 90 | $0.20 | ? |
| 4 | 75 | $0.005 | ? |
| 5 | 95 | $1.00 | ? |
Assessment
Learner has met the objective when, given a new configuration, they can decide whether it joins the frontier or is dominated.
References
- Multiple-Criteria Decision Analysis — for the formal Pareto-dominance definition.
- Anthropic / OpenAI / Google pricing pages — for the actual configurations plotted here.
- Chapter 3 of this textbook — Cost-Quality Tradeoff.
Senior Instructional Designer Quality Review
Reviewer perspective: 15+ years designing engineering and decision-science curricula for adult professional learners.
Overall verdict
Approve as-is for Chapter 3. Score: 89/100 (B+). Pareto-frontier visualization is the canonical primitive for L5 "judge"; this implementation makes the dominated set undeniably visible.
What works
- Bloom alignment correct. L5 "judge" requires applying explicit criteria; the constraint sliders externalize the criteria.
- Log-scale X axis. Without it, the cheap-model cluster vs expensive-thinking cluster wouldn't both be visible.
- Dashed frontier line. Visually proves the "non-dominated" claim — every green point is reachable on the line.
- Survivor list in the status banner. Translates filtering to action.
Gaps
- Only 9 configurations. Real teams have many more (different prompts, caching variants, vendor combos). A "load my own configurations" or "add a custom point" affordance would teach the methodology, not just the answer. Score impact: −3.
- No way to define a custom quality metric. Different workloads care about different quality dimensions; the single 0–100 score conflates them. Score impact: −2.
- No explicit dominance explainer. Hovering a gray point should show "dominated by:
" in the tooltip. Score impact: −2.
Accessibility
Color-blind safe (green/gray with size differences). Tooltips have full text. Slider labels show numeric values.
Cognitive load
9 points + 2 sliders + frontier line. Tractable.
Recommendation
Approve. Open follow-up for hover-explains-dominance (gap 3) — small but high-impact addition.