Recent consensus states that linear-combination modeling (LCM) is the preferred method for modeling GABA-edited spectra. However, there is little peer-reviewed literature investigating how this should be performed. Here, we compare various modeling strategies for GABA-edited spectra, with different approaches to macromolecular signal parametrization, baseline stiffness, and fitting range. Variance of GABA+/tCr estimates decreased when prior knowledge was maximized, i.e., when a full fit range was used with a dedicated co-edited MM basis function. These new modeling strategies have been implemented in the MATLAB-based open-source MRS analysis toolbox Osprey (github.com/schorschinho/osprey).