Of keen interest to the IC industry are advanced computational lithography applications such as Optical Proximity Correction, OPC, Optical Proximity Effect matching, OPEM, and Source-Mask Optimization, SMO. Lithographic mask models used by these simulators and their interactions with scanner illuminator models are key drivers impacting the accuracy of the image predications of the computational lithography applications. To construct topographic mask model for hyper-NA scanner, the interactions of the fields with the mask topography have to be accounted for by numerically solving Maxwell’s equations. The simulators used to predict the image formation in the hyper-NA scanners have to rigorously treat the topographic masks and the interaction of the mask topography with the scanner illuminators. Such mask models come at a high computational cost and pose challenging accuracy vs. compute time tradeoffs. To address the high costs of the computational lithography for hyper-NA scanners, we have adopted Reduced Basis, RB, method to efficiently extract accurate, near field images from a modest sample of rigorous, Finite Element, FE, solutions of Maxwell’s equations for the topographic masks. The combination of RB and FE methods provides means to efficiently generate near filed images of the topographic masks illuminated at oblique angles representing complex illuminator designs. The RB method’s ability to provide reliable results from a small set of pre-computed, rigorous results provides potentially tremendous computational cost advantage. In this report we present RB/FE technique and discuss the accuracy vs. compute time tradeoffs of hyper-NA imaging models incorporating topographic mask images obtained with the RB/FE method. The examples we present are representative of the analysis of the optical proximity effects for the current generation of IC designs.