While QM-based analysis is required for the interpretation of non-first-order HNMR spectra, the approach can also resolve signal overlap that occurs nearly ubiquitously even in (near) first-order ultra-high field NMR spectra. Non-QM based multiplet/multiplicity analysis typically fails in such instances because computations must consider not just the peaks, but the entirety of the many more lines. Evidently, completely overlapping lines remain unknown unless QM calculations are performed. In contrast, the QM-based approach deals with a much lower number of parameters: rather than all lines (32 in the relatively simple dt/ddd pattern of the axial H-9a in α-santonin), QM only requires significantly fewer values, i.e., the chemical shifts and all coupling constants (1 and 4, resp., in the same example). In addition, line fitting requires matching of line intensity, width, and shape, which quadruples the number of parameters that need to be matched (128). In contrast, intensity, width, and shape are only one parameter each in HiFSA, because they are uniform for a given spin particle. Therefore, QM requires only eight parameters to be determined, compared to 128 for the line-fitting methods. Thus, QM-based HNMR analysis is more efficient and stable than non-QM based methods. Since this advantage is independent of the occurrence of higher-order effects, which are most noticeable in low-magnetic field spectra, but are still common in high-field spectra, QM analysis is not only an approach for particularly complex cases, but the one that ought to be widely applied generally for NMR spectral interpretation and is becoming increasingly automated.