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.
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 (Qwen2.5-32B). 🤔 "Thinking Mode": Like some other recent models, it has a special "thinking mode" (activated with tags) that allows for longer chains of thought. ✅ Open Source: Model weights are available under Apache 2.0.
The implications of getting this level of reasoning performance from a 32B model are huge. It opens up possibilities for deploying powerful AI on less powerful hardware, reducing costs, and making advanced reasoning capabilities more accessible.
