This episode details the development of DeepSeek-R1, a large language model enhanced for reasoning capabilities through reinforcement learning (RL). Two versions are described: DeepSeek-R1-Zero, trained solely with RL, and DeepSeek-R1, which incorporates a multi-stage training process including cold-start data and supervised fine-tuning to improve readability and performance. DeepSeek-R1 achieves results comparable to OpenAI's o1-1217 model on various reasoning benchmarks. Furthermore, the research explores distilling DeepSeek-R1's reasoning abilities into smaller, more efficient models, achieving strong performance despite the absence of RL in the smaller models. The authors open-source their models and findings to benefit the research community.

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