国产大模型密集"上新"，港股AI概念板块集体走强，机构：2026年或重塑全球竞争格局

Core Insights - The AI sector in Hong Kong has shown strong performance, particularly in areas such as large models, storage, and computing power, driven by a wave of new product launches ahead of the Lunar New Year [1][3] Group 1: Product Launches and Innovations - Alibaba is set to release its new generation Qwen 3.5 large model on New Year's Eve, featuring architectural innovations [3] - ByteDance has launched the Doubao large model 2.0, which has undergone significant optimization for complex tasks [3] - Zhipu has introduced its flagship model GLM-5, increasing its parameter scale from 355 billion to 744 billion, with an average performance improvement of over 20% [3] - MiniMax has released the M2.5 model, designed for agent scenarios, achieving a 37% improvement in task completion speed compared to its predecessor [3] - Other products like DeepSeek-V4 and Kimi-K3 are expected to be released within February, indicating a significant product launch wave in the domestic large model sector [3] Group 2: Market Dynamics and Future Outlook - More domestic AI companies are choosing to list in Hong Kong, injecting new vitality into the sector, exemplified by Haizhi Technology Group's stock surging over 320% shortly after its listing [3] - Zhongyuan Securities predicts that the pace of AI application deployment in China will exceed market expectations by 2026, with domestic large models set to rival overseas counterparts in terms of performance, power consumption, and pricing [3] - Bank of America Securities notes that the acceleration of large model iterations in China is enhancing data center demand, which will drive adoption among enterprises and developers, subsequently increasing demand for inference data centers [3][4] Group 3: Structural Opportunities in AI Computing - Guosheng Securities highlights that breakthroughs from companies like ByteDance and Alibaba are shifting the focus of AI applications from technology development to large-scale deployment, creating a strong demand for AI computing resources [4]