Hartmanis and Simon demonstrated that certain number-theoretic algorithms are genuinely more efficient on RAM models, suggesting the asymptotic equivalence masks model-relative complexity differences.

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Asymptotic equivalence(as used in computational complexity theory): The idea that two different algorithms appear equally fast when you look at really large inputs, even though they might differ in how fast they actually are on real computers.
Efficiency(as used in this statement about judicial decision-making): Accomplishing a goal with minimal waste of time, resources, or effort; getting maximum results with minimum effort.
Hartmanis and Simon(as referenced in computer science and computational complexity): Juris Hartmanis and Herbert Simon are computer scientists who studied how different ways of measuring computer performance can give different results depending on the machine you're using.
Model-relative complexity differences(as used in computer science): Variations in how fast an algorithm actually performs depending on what type of computer or mathematical model you're measuring it on.

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