Tag: LLM quantization

Post-Training Quantization for Large Language Models: 8-Bit and 4-Bit Methods Explained

Post-training quantization cuts LLM memory use and speeds up inference by 2-3x without retraining. Learn how 8-bit and 4-bit methods like SmoothQuant, AWQ, and GPTQ make it possible-and what you need to know to use them.

Quantization-Aware Training for LLMs: How to Keep Accuracy While Shrinking Model Size

Quantization-aware training lets you shrink large language models to 4-bit without losing accuracy. Learn how it works, why it beats traditional methods, and how to use it in 2026.