AI Glossary

Pareto Frontier (Cost-Performance Curve)

A Pareto frontier, or cost-performance curve, plots model capability against cost to show which models give the most capability for a given price. A model sits on the frontier when nothing else is both cheaper and more capable. Builders use it to compare tiers, such as a fast cheap model against a larger flagship, and pick the trade-off that fits the task.

Also known as: pareto curve, cost-performance curve, capability-to-cost curve

· Chain of Thought

On a cost-performance curve, each model is a point set by how capable it is and how much it costs to run. The models on the frontier are the best trade-offs on offer at that moment. A model sitting below it is dominated: some other model matches or beats it on both axes at once, so there is no task where it is the right pick on price and capability alone.

Labs use this framing to justify shipping several sizes of one model family, a “pro” tier and a “flash” tier, where the small model pushes the frontier toward lower cost and latency and the large one pushes it toward higher capability. For teams building on those models, the curve is an argument against defaulting to the newest or largest option.

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