Abstract: The "main battlefield" of global large language model innovation competition is spreading from the R&D end to the industrial end. Exploring the scientific evaluation system and improvement mechanism of the competitiveness of the large language model industry innovation ecosystem has important theoretical value and practical significance for guiding the construction of the large model ecosystem and forming the competitive advantage of the national large language model ecosystem. Based on the theory of industrial competitive advantage and innovation ecosystem, this study constructed an evaluation index system to measure the comprehensive competitiveness level of the large language model industrial innovation ecosystem. This evaluation system starts from R&D, technology, and application, covering 24 indicators in three aspects: industrial chain self-controllable, technological innovation capability, and innovation ecosystem maturity. This article studies the implementation of classification evaluation for two types of large language models (open source and closed source), and sets baseline, development, and enhancement three types of indicators based on the improvement of the competitiveness of large models to adapt to the characteristics and needs of the development of large models. The results indicate that the competitiveness of large models exhibits dynamic evolution patterns due to the model lifecycle, and their competitiveness improvement are influenced by both internal governance mechanism and innovation policies. At the key stage of the ecological development of the large model industry, this article innovatively proposes a competitiveness evaluation system and improvement mechanisms, which provides a theoretical basis and practical guidance for promoting the high-quality development of the large language model industry ecology.