How an 8B Model Shrinks from 16GB to 4GB: Understanding Quantization
techNmak · x · 2026-08-16
Model quantization significantly reduces VRAM requirements by decreasing the bits used per parameter. An 8B model requires 16GB in BF16 but only 4GB in 4-bit. The core mechanism involves using a scale factor to map float weights to low-precision integers or floats, trading precision for storage space.
The post clarifies terminology: GPTQ/AWQ are quantization methods, INT4/FP4 are number formats, and GGUF is a file format. Quantization affects not just weights but also activations and KV Cache, with the latter becoming a major memory consumer in long contexts.
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