LongReasonArena: A Long Reasoning Benchmark for Large Language Models

• URL: http://arxiv.org/abs/2508.19363v1
• Date: Tue, 26 Aug 2025 18:41:53 GMT
• Title: LongReasonArena: A Long Reasoning Benchmark for Large Language Models
• Authors: Jiayu Ding, Shuming Ma, Lei Cui, Nanning Zheng, Furu Wei,
• Abstract summary: LongReasonArena is a benchmark designed to assess the long reasoning capabilities of Large Language Models (LLMs)<n>By controlling the inputs, the required reasoning length can be arbitrarily scaled, reaching up to 1 million tokens of reasoning for the most challenging tasks.
• Score: 94.58086553970101
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Existing long-context benchmarks for Large Language Models (LLMs) focus on evaluating comprehension of long inputs, while overlooking the evaluation of long reasoning abilities. To address this gap, we introduce LongReasonArena, a benchmark specifically designed to assess the long reasoning capabilities of LLMs. Our tasks require models to solve problems by executing multi-step algorithms that reflect key aspects of long reasoning, such as retrieval and backtracking. By controlling the inputs, the required reasoning length can be arbitrarily scaled, reaching up to 1 million tokens of reasoning for the most challenging tasks. Extensive evaluation results demonstrate that LongReasonArena presents a significant challenge for both open-source and proprietary LLMs. For instance, Deepseek-R1 achieves only 7.5% accuracy on our task. Further analysis also reveals that the accuracy exhibits a linear decline with respect to the logarithm of the expected number of reasoning steps. Our code and data is available at https://github.com/LongReasonArena/LongReasonArena.

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