QwQ-32B, from Alibaba Qwen team, is a new open-source 32B LLM achieving DeepSeek-R1 level reasoning via scaled Reinforcement Learning. Features a "thinking mode" for complex tasks.
Matching R1 reasoning yet 20x smaller
QwQ-32B, from Alibaba Qwen team, is a new open-source 32B LLM achieving DeepSeek-R1 level reasoning via scaled Reinforcement Learning. Features a "thinking mode" for complex tasks.
Hi everyone! Check out QwQ-32B, a new open-source language model from the Qwen team. It's achieving something remarkable: reasoning performance comparable to DeepSeek-R1, but with a model that's 20 times smaller (32B parameters vs. 671B)! This is a big deal because: 🤯 Size/Performance Ratio: It punches way above its weight class in reasoning, math, and coding tasks. 🧠Scaled Reinforcement Learning: They achieved this by scaling up Reinforcement Learning (RL) on a strong foundation model (Qwen2.5
This score and size are amazing, I have a few questions What is the difference between it and DeepSeek R1? Do you have plans to make a larger size reasoning model? Thank you for your contribution to the open source community!
I use hugging face every day for my job. I didn't know that models there can be launched on PH. Very cool!
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