---
title: NuminaMath-QwQ-CoT-5M
canonical_url: "https://www.modelscope.cn/datasets/PrimeIntellect/NuminaMath-QwQ-CoT-5M"
md_url: "https://www.modelscope.cn/datasets/PrimeIntellect/NuminaMath-QwQ-CoT-5M.md"
repository: PrimeIntellect/NuminaMath-QwQ-CoT-5M
last_updated: 2025-02-07
license: "Apache License 2.0"
storage_size: "17 GB"
downloads: 1236
stars: 2
---

# NuminaMath-QwQ-CoT-5M

> NuminaMath-QwQ-CoT-5M - PrimeIntellect 在 ModelScope 开源的数据集。INTELLECT-MATH: Frontier Mathematical Reasoning through Better Initializations for Reinforcement Learning

PrimeIntellect/NuminaMath-QwQ-CoT-5M 是 ModelScope 魔搭社区上的数据集，存储大小 17 GB，采用 Apache License 2.0 许可。

- **Repository**: PrimeIntellect/NuminaMath-QwQ-CoT-5M
- **License**: Apache License 2.0
- **Storage size**: 17 GB
- **Downloads**: 1236
- **Stars**: 2
- **Last updated**: 2025-02-07

Source: https://www.modelscope.cn/datasets/PrimeIntellect/NuminaMath-QwQ-CoT-5M

---

# INTELLECT-MATH: Frontier Mathematical Reasoning through Better Initializations for Reinforcement Learning

INTELLECT-MATH is a 7B parameter model optimized for mathematical reasoning. It was trained in two stages, an SFT stage, in which the model was fine-tuned on verified QwQ outputs, and an RL stage, in which the model was trained using the [PRIME-RL](https://github.com/PRIME-RL/PRIME) recipe.

We demonstrate that the quality of our SFT data can impact the performance and training speed of the RL stage: Due to its better synthetic SFT dataset that encourages the model to imitate the reasoning behavior of a strong teacher model, INTELLECT-MATH outperforms Eurus-2-PRIME, the previous state-of-the-art trained with PRIME-RL, and matches its performance with 10x faster training.



|      | Intellect-Math (Step 255) | Intellect-Math (Step 47) | Eurus-2-Prime (Step 592) | Intellect-Math-SFT | Eurus-2-SFT | Qwen-2.5-Math |
|----------------|---------------------------:|--------------------------:|--------------------------:|--------------------:|------------:|-------------:|
| **MATH-500**   | 82.0                      | 81.6                     | 79.2                     | 72.8               | 65.1        | 79.8         |
| **OLYMPIADBENCH** | 49.5                   | 46.7                     | 42.1                     | 39.1               | 29.8        | 40.7         |
| **AIME 2024**  | 26.7                      | 26.7                     | 26.7                     | 16.6               | 3.3         | 13.3         |
| **AMC**        | 60.2                      | 57.8                     | 57.8                     | 45.8               | 30.1        | 50.6         |
| **MINERVA MATH** | 39.7                    | 37.8                     | 38.6                     | 33.8               | 32.7        | 34.6         |
| **AVG**        | 51.6                      | 50.1                     | 48.9                     | 41.6               | 32.2        | 43.8         |




### Links

- 📜 [Blog Post](https://www.primeintellect.ai/blog/intellect-math)
- 🔗 [Github](https://github.com/PrimeIntellect-ai/INTELLECT-MATH)
- 🤗 [Hugging Face Collection](https://huggingface.co/collections/PrimeIntellect/intellect-math-678a2a25d7c5d74b37b16581)