Citigroup: MEITUAN-W LongCat-2.0 open source benefits competitive moat, maintains "Buy" rating
Citi released a research report stating that MEITUAN-W will officially open source the trillion-parameter large model LongCat-2.0, believing that this strategic move will further consolidate its leadership position in the local life services market. The model's advanced Agentic architecture will enhance internal R&D efficiency and attract external developers. The report maintains a "Buy" rating on MEITUAN with a target price of HKD 113. It indicates that by leveraging its vast and proprietary offline transaction and operational data, MEITUAN can provide unique AI-driven marketing and business insights for small and medium-sized enterprises. The firm believes this will create a competitive moat, distinguishing it from other large language model providers and deepening relationships with merchants and consumers. The firm believes MEITUAN's model has a significant differentiation advantage due to its proprietary data from the rider network and accumulated experience in order dispatch algorithms
According to the Zhitong Finance APP, Citibank released a research report stating that MEITUAN-W (03690) will officially open source the trillion-parameter large model LongCat-2.0, believing that this strategic move will further consolidate its leadership position in the local life services market. The model's advanced Agentic architecture will enhance internal R&D efficiency and attract external developers. The rating for MEITUAN is maintained at "Buy" with a target price of HKD 113.
The report indicates that by utilizing its vast and proprietary offline transaction and operational data, MEITUAN can provide unique AI-driven marketing and business insights for small and medium-sized enterprises. The bank believes this will create a competitive moat, distinguishing it from other large language model providers and deepening relationships with merchants and consumers. The bank believes that MEITUAN's model has a significant differentiated advantage due to its proprietary data from the rider network and accumulated experience in order dispatch algorithms
