The integration of Large Language Models (LLMs) in software modeling tasks presents both opportunities and challenges.
This Expert Voice addresses a significant gap in the evaluation of these models, advocating for the need for standardized
benchmarking frameworks. Recognizing the potential variability in prompt strategies, LLM outputs, and solution space, we
propose a conceptual framework to assess their quality in software model generation. This framework aims to pave the way
for standardization of the benchmarking process, ensuring consistent and objective evaluation of LLMs in software modeling.
Our conceptual framework is illustrated using UML class diagrams as a running example.
