Abstract: Research funding serves as a primary driving force for universities to conduct scientific and technological innovation, it is also recognized as a critical area in the reform of national science and technology management. However, there is currently a lack of scientific and quantitative methods for evaluating the management capabilities of research funding in universities, alongside an inadequate evaluation to accurately assess the performance outcomes generated from such funding. A two-stage entropy model is constructed in this paper to conduct quantitative research on the capacity and effectiveness of research funding utilization at Chinese universities. The analysis reveals that the research funding management system of Chinese universities is generally in an entropy increase state, which has been found to indicate insufficient management capabilities and unsatisfactory results. In particular, challenges are still being faced in managing scientific instrument operations, promoting the transformation of technological achievements, and cultivating major innovative achievements. At present, efforts are needed to coordinate various research funding resources and increase investment in key areas; institutional innovation for the "lump-sum system" can be implemented by exploring new models such as "lump-sum contract by subject"; flexibility should be improved into budget control within university research funding management; artificial intelligence technology can be introduced to build an intelligent funding management system that provides intelligent and refined services.