DeepSeek's Qwen-distilled models are compact reasoning models derived from DeepSeek-R1, achieving exceptional performance by distilling larger model reasoning patterns into smaller architectures. Spanning from 1.5B to 70B parameters, the models are based on Qwen2.5 and Llama3, with the standout DeepSeek-R1-Distill-Qwen-32B outperforming OpenAI-o1-mini and setting new dense model benchmarks. By combining reinforcement learning (RL) and supervised fine-tuning (SFT), these open-source models provide a powerful resource for advancing research and practical applications.

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