OpenMathReasoning OpenMathReasoning is a large scale math reasoning dataset for training large language models (LLMs). This dataset contains 306K unique mathematical problems sourced from AoPS forums with: 3.2M long chain of thought (CoT) solutions 1.7M long tool integrated reasoning (TIR) solutions 566K samples that select the most promising solution out of many candidates (GenSelect) Additional 193K problems sourced from AoPS forums (problems only, no solutions) We used Qwen2.5 32B Instruct to preprocess problems, and DeepSeek R1 and QwQ 32B to generate solutions. This dataset was a foundation of our winning submission to the AIMO 2 Kaggle competition. See our paper to learn more details! NOTE: We initially reported 540K unique problems in our dataset, but this figure represented the question count at the pipeline's beginning. But the actual CoT and TIR solutions in the released dataset correspond to 306K problems. Since our OpenMath Nemotron models were trained on this reduced subset, all published results remain reproducible with the current release—only our initial problem count was overstated. Two factors explain this discrepancy in question numbers. Our filtering process rem…
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