Accurate color reproduction on a display requires an inverse display model, mapping colorimetric values (e.g. CIE XYZ) into RGB values driving the display. To create such a model, we collected a large dataset of display color measurements for a high refresh-rate 4-primary OLED display. We demonstrated that, unlike traditional LCD displays, multi-primary OLED display color responses are non-additive and non-linear for some colors. We tested the performances of different regression methods: polynomial regression, look-up tables, multi-layer perceptrons, and others. The best-performing models were additionally validated on newly measured (unseen) test colors. We found that the performances of several variations of 4th-degree polynomial models were comparable to the look-up table and machine-learning-based models while being less resource-intensive.