ChatGPT-4o had the best overall scores for 10/13 of the spectra analyzed, with a clear edge in processing 2D NMR spectra as shown in 5. The remaining 3 prompts used were from 3.5 Sonnet generations to complete the text based chain of 13 for a combined average overall score of 9.01/10 scored by ScholarGPT for Part A. All of the 8 models tested in Part B were typically able to grasp some intricate contextual tasks they were given with using advanced forms of natural language processing. Only Sonnet 3.5 was able to combine its reasoning of spectra using the provided molecular formula to provide more accurate compounds. The model did so by outputting an isomer with an identical compound name for 3 of its generations, and only varied in average molecular weight by by 0.66 g/mol between six total generations. What this meant was that although there were likely training data deficiencies to support 6 of the 2D NMR spectra, 3.5 Sonnet was still able to provide a reasonable compound matching the molecular formula C 15 H 22 O 2 .