At the moment there are three potential models and associated measures to replace the FLIR92 model and the MRTD as the standard for sensor performance characterization and TA range predictions. These are: (1) the NVTherm model that calculates the MRTD-ID, (2) the TRM3 model that calculates the MTDP and (3) the TOD model that calculates the TOD. The three models are grossly different in theoretical approach. We ran the models for the same set of hypothetical cameras. As default sensor, we used a 'typical' under-sampled Focal Plane Array camera. Then, we independently varied the pre- and post-filter MTF's over a wide range while keeping the sampling frequency fixed so that the cameras ranged between well-sampled and highly under-sampled. The differences in outcome are striking. For example, for a range of sensors around the default the TOD model predicts that performance is determined primarily by the sampling frequency, while NVTherm predicts that pre- an post-filter blur dominate in this region. The results with TRM3 are surprising: the model predicts that increasing image information content by applying microscan to the default sensor, decreases predicted TA performance. The origin lies in the use of the periodic four-bar test pattern and the definition of the MTDP. In the low contrast region, the MTDP and the TOD are similar but the MRTD-ID deviates from these two. The MTDP and MRTD-ID are different even in the well-sampled region where they both should be equivalent to the conventional MRTD. The study shows that the choice of a model has a large impact on sensor design decisions or trade-offs between sensors. The TOD method is the most general of the three approaches and has the strongest basis. Until now, validation of the model predictions is very limited. Therefore, a joint TA performance study with simulated sensors (e.g. those used in the present study) and target contrast as variables would be very useful.