CHIMERA is a synthetic inference dataset designed specifically for inference training; related research papers include... CHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning This dataset covers a wide range of STEM subjects and provides long chain thinking (CoT) trajectories. This dataset contains 9,225 questions across 8 subjects (mathematics, computer science, chemistry, physics, literature, history, biology, and phonetics). All examples are generated by a large language model (LLM) and are automatically validated without manual annotation. Discipline Distribution:

• Mathematics: 4,452
• Computer Science: 1,303
• Chemistry: 1,102
• Physics: 742
• Literature: 504
• History: 422
• Biology: 383
• Linguistics: 317

Citation

@article{chimera2026, title = {CHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning}, author = {Xinyu Zhu and Yihao Feng and Yanchao Sun and Xianzhi Du and Pingzhi Li and Olli Saarikivi and Yun Zhu and Yu Meng}, journal = {arXiv preprint arXiv:2603.00889}, year = {2026} }