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.

摘要： 全球大模型创新竞争的“主战场”正从研发端向产业端拓展，探索大模型产业创新生态系统综合竞争力的评价体系和提升机制，对于引导大模型生态建设，形成国家大模型生态竞争优势具有重要的理论价值和实践意义。本文基于产业竞争优势和创新生态系统理论，构建了衡量大模型产业创新生态系统综合竞争力水平的评价指标体系。该指标体系涵盖产业链自主可控、技术创新能力、创新生态成熟度3个方面共24项指标。研究针对开源和闭源两类大模型实施分类评价，并根据大模型竞争力提升设置底线型、发展型和增强型三类指标，以适应大模型发展的特点和需求。研究指出，大模型竞争力因大模型生命周期而呈现动态演化规律，并且其竞争力提升受到内部治理和创新政策的共同影响。在大模型产业生态发展的关键阶段，本文创新性提出竞争力评价体系与提升机制，为加速大模型产业生态高质量发展提供了理论依据和实践指导。