W8A16 Quantization with LLM.int8-Style Outlier Handling

In Phase 1 , we demonstrated that outliers in transformer models are not "statistical noise"—they are critical carriers of model intelligence and context. When we zeroed outliers in weight matrices, model outputs degraded catastrophically, producing repetitive loops and nonsensical text. But here's the problem : Quantizing weights from BF16 to INT8 reduces memory by ~50%, but it also destroys…