what is quantization, and why it's the reason you can run AI on a normal PC

Quantization is the trick that shrinks giant AI models to fit consumer GPUs, with almost no quality loss. Here's what those Q4/Q5/Q8 labels actually… Aliteq Lena Fischer · AI & Local Compute Editor

Quantization = storing model weights at lower precision (e.g. 4-bit vs 16-bit) to shrink memory use.

It cuts VRAM by ~75% at 4-bit with minimal quality loss — the reason local AI fits on consumer GPUs.

Q4 / Q5 / Q8 = the bit level — Q4 is 4-bit (smallest), Q8 is 8-bit (larger, higher fidelity).

Q4_K_M is the sweet spot — near-lossless quality at a quarter of the memory. Use it unless you have spare VRAM.

Below ~Q4, quality drops noticeably — Q3 and lower are only for squeezing into tiny VRAM.

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