A new metric called Data-Model Compatibility (DMC) has been introduced to enhance the effectiveness of reasoning distillation from large language models to smaller ones by assessing dataset suitability. The study shows that dynamically selecting datasets based on DMC can significantly improve performance across various models and tasks.