This contribution has an exploratory nature, marking the initial phase of a broader research project aimed at achieving both descriptive and theoretical objectives. The primary goal is to evaluate the ‘quality’ of texts produced by Language Model Models (LLMs). Two key aspects are examined: the quality of generated texts in comparison to human-authored texts and the identification of distinctive features characterizing this emerging text typology. The analysis is centered on textual parameters, encompassing various phenomena related to text segmentation and three dimensions of text organization (the referential-thematic dimension, the logico-argumentative dimension, and the polyphonic-enunciative dimension). Results of different case studies based on a self-assemble corpus of biographies generated by ChatGPT-3.5 and published on Wikipedia are presented.