MathArena: Evaluating LLMs on Uncontaminated Math Competitions

TL;DR

MathArena introduces a contamination-free, real-time benchmark for evaluating LLMs on math competitions, emphasizing reasoning and proof-writing, and revealing both progress and challenges in current models.

Contribution

We present MathArena, a novel, real-time, uncontaminated benchmark for assessing LLM reasoning and proof-writing on math competitions, addressing limitations of existing datasets.

Findings

Strong signs of contamination in AIME 2024

Top models achieve nearly 40% on IMO 2025

MathArena evaluates over 50 models across seven competitions

Abstract

The rapid advancement of reasoning capabilities in large language models (LLMs) has led to notable improvements on mathematical benchmarks. However, many of the most commonly used evaluation datasets (e.g., AIME 2024) are widely available online, making it difficult to disentangle genuine reasoning from potential memorization. Furthermore, these benchmarks do not evaluate proof-writing capabilities, which are crucial for many mathematical tasks. To address this, we introduce MathArena, a new benchmark based on the following key insight: recurring math competitions provide a stream of high-quality, challenging problems that can be used for real-time evaluation of LLMs. By evaluating models as soon as new problems are released, we effectively eliminate the risk of contamination. Using this framework, we find strong signs of contamination in AIME 2024. Nonetheless, evaluations on harder competitions, such as CMIMC 2025, demonstrate impressive reasoning capabilities in top-performing models. MathArena is also the first benchmark for proof-writing capabilities. On IMO 2025, top models achieve slightly less than 40%, demonstrating both notable progress and significant room for improvement. So far, we have evaluated over $50$ models across seven competitions, totaling $162$ problems. As an evolving benchmark, MathArena will continue to track the progress of LLMs on newly released competitions, ensuring rigorous and up-to-date evaluation of mathematical reasoning.