High-fidelity ConvRot INT8 reverse hybrid quantization for SDXL diffusion models. HSWQ uses per-layer trajectory-impact measurement instead of naive uniform cast, converting only the K lowest-impact layers to ConvRot INT8 while keeping every other layer at FP16. This is highly useful for users who need to strictly manage their VRAM resources while maintaining maximum image quality. Reverse hybrid (diag → reverse): The FP16 checkpoint is the only input. A per-layer trajectory-impact measurement (sdxl/diagimpactsdxl.py) injects each candidate layer's ConvRot INT8 reconstruction into the FP16 model one at a time and runs the production sampler — recording the final-latent drift. The K…