Recently, UBS held a summit with at least 19 AI companies to discuss topics such as the impact of China's open-source models and token cost optimization. These companies are leading players in their respective verticals and hold significant influence on these issues. After engaging with these companies, UBS reached several conclusions: 1. The AI industry is entering a "multi-model era." The future market will not be dominated by a few closed-source large models but will instead form an ecosystem where cutting-edge models, open-source models, and enterprise-customized models coexist. The rise of China's open-source models is reshaping competitive dynamics. AI competition is no longer solely about pursuing the highest model performance but is shifting toward a comprehensive competition of "performance, cost, and efficiency." 2. Enterprises will dynamically choose between high-performance models and low-cost models based on task complexity to reduce token consumption. This capability will become a core competitive advantage for AI application and infrastructure companies. 3. Industry-specific models fine-tuned from foundational models will also become a key direction, driving AI deeper into vertical scenarios from general capabilities. 4. Cloud providers like AWS and Azure will benefit from the multi-model ecosystem and the continuously growing demand for AI, with a neutral-to-positive impact. 5. GPU demand will not be weakened. AI workloads will expand to include more inference tasks, overall benefiting compute power suppliers like NVIDIA. 6. In contrast, the software industry may face pressure. To control AI costs, enterprises might reduce the use of certain AI functionalities. Meanwhile, traditional software companies may find it challenging to profit from multi-model compatibility capabilities.