LCModel and AMARES, two widely used quantitation tools for magnetic resonance spectroscopy (MRS) data, were employed to analyze simulated spectra similar to those typically obtained at short echo times (TEs) in the human brain at 1.5 T. The study focused mainly on the influence of signal-to-noise ratios (SNRs) and different linewidths on the accuracy and precision of the quantification results, and their effectiveness in accounting for the broad signal contribution of macromolecules and lipids (often called the baseline in in vivo MRS). When applied in their standard configuration (i.e., fitting a spline as a baseline for LCModel, and weighting the first data points for AMARES), both methods performed comparably but with their own characteristics. LCModel and AMARES quantitation benefited considerably from the incorporation of baseline information into the prior knowledge. However, the more accurate quantitation of the sum of glutamate and glutamine (Glx) favored the use of LCModel. Metabolite-to-creatine ratios estimated by LCModel with extended prior knowledge are more accurate than absolute concentrations, and are nearly independent of SNR and line broadening. Magn Reson Med 51:904–912, 2004. © 2004 Wiley-Liss, Inc.