Audio signal processing is a core element in hearing devices, allowing for adaptation of the signal properties to the listener’s needs in a specific listening situation. Besides the desired signal manipulations, e.g., spectral equalization and binaural noise reduction, signal processing may also introduce monaural or binaural distortions. Auditory models can be applied to predict the perceptual relevance of such distortions and for their minimization. This, however, requires a balance between prediction accuracy and computational efficiency of the model. In this work, the simplistic binaural processing model of Eurich et al. (2022 JASA, 151(6), pp. 3927-3936), based on the hemispheric two-channel code and consistent with binaural psychophysics, was combined with a modified version of the monaural generalized power spectrum model of quality (Biberger et al. 2018, JAES., vol. 66, no. 7/8, pp. 578-593) to cover binaural and monaural audio quality aspects. The suggested model was evaluated with several databases including music and speech signals processed by loudspeakers and algorithms typically applied in modern hearing devices. The presented model performed similar to previously employed computationally more complex models, which makes it applicable to hearing devices and algorithms.