How Prompt Style Affects AI Accuracy and Speed in Competitive Programming

Saad B. Alarifi, Mohammed A. Alam · 2026 · arXiv

DOI: 10.48550/arXiv.2610.30223 · open-access PDF

Abstract

Large language models are increasingly used in competitive programming, and their outputs are sensitive to how a prompt is phrased. Prior work has compared prompt strategies for accuracy on competitive programming, but not for runtime speed, and has not situated the results against human performance. In an exploratory study of one prompt in each of nine styles on GPT-5.5 across three accuracy tasks from the International Olympiad in Informatics (IOI) and two NP-hard speed tasks, we found that no single prompt was best: the strongest prompt depended on the task type and on whether results were

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