This episode discusses QwQ 32B, a newly released open-source language model by Alibaba. This smaller model reportedly rivals the performance of DeepSeek R1, a significantly larger model, especially in reasoning and agent-related tasks. QwQ 32B achieves this through a two-stage reinforcement learning process, initially focusing on math and coding with verifiable rewards before generalizing to broader capabilities. Benchmarks show comparable or even superior performance in some areas, like the Amy 2024 math benchmark, but weaker results in others compared to models like DeepSeek R1 and GPT-4.5. Its speed and open-source nature are highlighted as major advantages, with impressive inference speeds demonstrated, despite a smaller context window and potentially excessive "thinking."

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