DeepSeek R1, a recently released AI model, has made significant strides in the AI community by offering performance comparable to leading models at a lower cost, though it can be expensive for high-traffic applications. Its strength lies in generating detailed "chains of thought" (CoT) that enhance reasoning quality but increase inference costs. The model serves as an effective teacher in distillation, transferring its reasoning capabilities to more cost-effective student models, thus reducing overall inference costs. This method allows for the automatic generation of training data without the need for costly human annotations, and synthetic data produced by DeepSeek R1 may even surpass human-labeled data in quality. In a case study using the GSM8K dataset, variants fine-tuned with DeepSeek R1's synthetic reasoning chains demonstrated superior accuracy compared to those using human expert chains, though at the expense of increased reasoning length and inference cost. The model is accessible on the Fireworks AI platform, and its capabilities highlight the potential for machines to exceed human teaching in certain contexts.