The study was performed with separate spectra due to a prior study's results indicating that for complex compounds with greater than 9 carbons and 5 supporting spectra, there is not yet an accurate method to provide a molecule's name in a single prompt. For Part A, the scoring difference between 3.5 Sonnet (7.98 avg.) and ChatGPT-4o (8.61 avg.) was largely due to ChatGPT-4o having greater proficiency in evaluating every 2D NMR spectra (GCOSY60, GTOCSY, GHMQC, GHMBC, GHMBC Zoom, and GNOESY). Although the best 13 evaluations of the two models had an average score of 9.01 overall, the responses tended to be verbose and missed some important detail such as exact splitting patterns or intricate correlations between atoms, as effective LMM image analysis will likely continue to see improvements in this area.