<hi xmlns="http://www.tei-c.org/ns/1.0" rend="color(#0e101a)">In this paper, we present our case study that focuses on the visual and narrative features of Olga Abramchik’s 2021 documentary </hi> <hi xmlns="http://www.tei-c.org/ns/1.0" rend="italic">Мы не знали друг друга до этого лета</hi> <hi xmlns="http://www.tei-c.org/ns/1.0" rend="color(#0e101a)"> [</hi> <hi xmlns="http://www.tei-c.org/ns/1.0" rend="italic">We Didn't Know Each Other Before This Summer</hi> <hi xmlns="http://www.tei-c.org/ns/1.0" rend="color(#0e101a)">] (Abramchik, 2021) by using two different MLLMs. First, we introduce our case study</hi>. Afterwards, we <hi xmlns="http://www.tei-c.org/ns/1.0" rend="color(#0e101a)">describe the image analysis pipeline that combines MLLM annotation with topic modelling. We then discuss our main findings by comparing the annotation results of the two models, focusing on the interpretability of the topics extracted from these annotations. Finally, we discuss the strengths and limitations of both MLLMs in the image annotation task and their use in understanding the analysed video as a whole.</hi>