The timescale over which magma rises to the surface during a volcanic eruption is a critical parameter that controls eruption style but is challenging to determine. Melt embayments, which are pockets of magma trapped within crystals but are still open to the host magma, tend to develop volatile (e.g., H2O, CO2) concentration gradients during ascent through the process of diffusion. These gradients are increasingly used as output constraints for diffusion models to calculate total ascent time. However, there are two main assumptions associated with the method that have yet to be properly evaluated. First, the diffusion models tend to be carried out in 1D, which may be less accurate than 3D models if the embayment narrows near the opening. This geometry has more complicated volatile flux pathways that 1D models cannot account for. Second, the models typically assume that volatile contents follow equilibrium saturation trends defined by depth below the surface, which may not be accurate for high silica magmas. For these compositions, a significant supersaturation of volatiles may be needed for volatile exsolution to start, depending on the availability of suitable crystal phases for bubble nucleation. This nucleation lag delays the start of diffusion as well and could influence modeled timescales. We developed 3D diffusion models to evaluate the degree of inaccuracy in calculated timescales introduced by these assumptions for high silica magmas. We built synthetic embayments with variable 3D geometries and imposed both equilibrium and disequilibrium ascent conditions in our models. Our results indicate that the inaccuracy introduced by embayment geometry in 1D diffusion models increases as the diameter of the embayment opening decreases. This degree of inaccuracy is also tied to diffusion duration – as it increases, so does the relative error in timescales retrieved by 1D models fitting 3D-generated profiles. Once the diffusion front extends beyond the narrow, “necked” region of the embayment, relative error increases with increasing diffusion time. However, volatile disequilibrium behavior does not appear to significantly impact modeled timescales. These results indicate that embayment geometry is a critical variable that must be accounted for whereas delayed nucleation is of secondary influence.