Predict Before You Deploy: Offline Prediction of Quantization-Induced Task Degradation for World Action Models

World action models (WAMs) rely on video-generation backbones, requiring substantial memory and compute for deployment. Post-training quantization reduces memory and can accelerate inference, but bit width, grouping, and quantizer choice define a large configuration space. Identifying configurations