While DeepSeek-R1 operates with 671 billion parameters, QwQ-32B achieves comparable performance with a much smaller footprint ...
After the launch, Alibaba's shares rose over 8% in Hong Kong, which also helped boost the Chinese tech stocks' index by about ...
Alibaba developed QwQ-32B through two training sessions. The first session focused on teaching the model math and coding ...
Alibaba released and open-sourced its new reasoning model, QwQ-32B, featuring 32 billion parameters. Despite being ...
This remarkable outcome underscores the effectiveness of RL when applied to robust foundation models pre-trained on extensive ...
B, an AI model rivaling OpenAI and DeepSeek with 98% lower compute costs. A game-changer in AI efficiency, boosting Alibaba’s ...
The model operates with 32 billion parameters compared to DeepSeek's 671 billion, with only 37 billion actively engaged ...
These reasoning models were designed to offer an open-source alternative for the likes of OpenAI's o1 series. The QwQ-32B is a 32 billion parameter model developed by scaling reinforcement learning ...
The latest model from the Chinese public cloud provider shows how reinforced learning is driving AI efficiency ...