Qwen Team, a division of Chinese e-commerce giant Alibaba developing its growing family of open-source Qwen large language models (LLMs), has introduced QwQ-32B, a new 32-billion-parameter reasoning model designed to improve performance on complex problem-solving tasks through reinforcement learning (RL). The model is available as open-weight on Hugging Face and on ModelScope under an Apache 2.0 license. This means it’s available for commercial and research uses, so enterprises can employ it immediately to power their products and applications (even ones they charge customers to use). QwQ, short for Qwen-with-Questions, was first introduced by Alibaba in November 2024 as an open-source reasoning model aimed at competing with OpenAI’s o1-preview. At launch, the model was designed to enhance logical reasoning and planning by reviewing and refining its own responses during inference, a technique that made it particularly effective in math and coding tasks. The initial version of QwQ released back in November 2024 (called simply, “QwQ”) featured 32 billion parameters as well, and a 32,000-token context length. Alibaba highlighted its ability to outperform o1-preview in mathematical benchmarks like AIME and MATH, as well as scientific reasoning tasks such as GPQA.

Full report : Alibaba releases open-source reasoning model QwQ-32B on Hugging Face and ModelScope, claiming comparable performance to DeepSeek-R1 but with lower compute needs.