J-difference edited magnetic resonance spectroscopy is widely used to estimate levels of low-concentration metabolites with overlapping signals. Quantification is commonly performed on the difference spectra only, either using single-resonance fitting or linear-combination modeling based on simulated basis functions. Here, simultaneous linear-combination modeling of GABA-edited MEGA-PRESS sum and difference spectra is demonstrated. Simultaneous modeling incorporates all available spectral information, and does not require the definition of soft constraints on the low-concentration metabolite estimates. Across a large dataset, this new approach gave lower coefficients of variation for estimates of GABA, glutamate, and glutamine than modeling of the difference and sum spectra only.