{"slug": "macaq-fast-model-agnostic-calibrated-quantization-for-low-precision-weights-and", "title": "MACaQ: Fast, Model Agnostic Calibrated Quantization for Low-Precision Weights and Activations", "summary": "Researchers introduced MACaQ, an MXFP4 W4A4 post-training quantization method for weight-activation quantization that reduces the memory and compute cost of neural-network inference without the expensive optimization and architecture-specific propagation of basis transforms across layers required by recent methods. The work targets low-precision weights and activations and is described as fast and model agnostic.", "body_md": "Weight-activation quantization can reduce the memory and compute cost of neural-network inference, but recent methods often require expensive optimization and architecture-specific propagation of basis transforms across layers. We introduce MACaQ, an MXFP4 W4A4 post-training quantization method that", "url": "https://wpnews.pro/news/macaq-fast-model-agnostic-calibrated-quantization-for-low-precision-weights-and", "canonical_source": "https://aiflash.com/news/149719/", "published_at": "2026-11-11 12:00:05+00:00", "updated_at": "2026-11-11 12:24:54.216082+00:00", "lang": "en", "topics": ["machine-learning", "ai-research", "neural-networks", "ai-infrastructure"], "entities": ["MACaQ"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/macaq-fast-model-agnostic-calibrated-quantization-for-low-precision-weights-and", "markdown": "https://wpnews.pro/news/macaq-fast-model-agnostic-calibrated-quantization-for-low-precision-weights-and.md", "text": "https://wpnews.pro/news/macaq-fast-model-agnostic-calibrated-quantization-for-low-precision-weights-and.txt", "jsonld": "https://wpnews.pro/news/macaq-fast-model-agnostic-calibrated-quantization-for-low-precision-weights-and.jsonld"}}