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What Is AWQ in LLM Quantization and How to Use It
AWQ is a post-training quantization technique that packs large language models into 4-bit weight formats while shielding the ~1% of salient weights that actually drive quality. In practice it cuts VRAM roughly in half and buys 1.5–3× faster inference than FP16, which is exactly the kind of resource…
