---
base_model:
- Qwen/Qwen3-4B-Thinking-2507
datasets:
- TianHongZXY/CHIMERA
library_name: transformers
pipeline_tag: text-generation
tags:
- reasoning
- synthetic-data
- chain-of-thought
---

# CHIMERA-4B-RL

This model was introduced in the paper [CHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning](https://huggingface.co/papers/2603.00889).

**Authors:** Xinyu Zhu, Yihao Feng, Yanchao Sun, Xianzhi Du, Pingzhi Li, Olli Saarikivi, Yun Zhu, Yu Meng.

## Description
CHIMERA-4B-RL is [CHIMERA-4B-SFT](https://huggingface.co/TianHongZXY/CHIMERA-4B-SFT) further trained with reinforcement learning on the [CHIMERA](https://huggingface.co/datasets/TianHongZXY/CHIMERA) dataset.

CHIMERA is a compact synthetic reasoning dataset comprising 9K samples designed for generalizable cross-domain reasoning. It provides rich, long Chain-of-Thought (CoT) trajectories across 8 major scientific disciplines. Despite its modest size, post-training a 4B model on this data allows it to approach or match the reasoning performance of significantly larger models like DeepSeek-R1 and Qwen3-235B.

## Results

| Model | GPQA-D | AIME 24 | AIME 25 | AIME 26 | HMMT Feb 25 | HMMT Nov 25 | HLE |
|---|---|---|---|---|---|---|---|
| Qwen3-4B-Thinking-2507 | 65.8 | 81.6 | **81.0** | 80.8 | 59.2 | 57.3 | 7.3 |
| CHIMERA-4B-SFT | 68.8 | 86.5 | 79.8 | 80.3 | 63.1 | 66.3 | **9.0** |
| **CHIMERA-4B-RL** | **70.1** | **86.9** | 80.7 | **82.7** | **65.7** | **67.0** | **9.0** |

## Citation
```bibtex
@article{zhu2026chimera,
  title={CHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning},
  author={Zhu, Xinyu and Feng, Yihao and Sun, Yanchao and Du, Xianzhi and Li, Pingzhi and Saarikivi, Olli and Zhu, Yun and Meng, Yu},
  journal={arXiv preprint arXiv:2603.00889},
  year={2026}
}
```