Quantization

Turkish equivalent: NicemlemeDomain: Machine Learning

The representation of model weights, activations, or intermediate values with reduced numerical precision to decrease memory use and often improve inference speed.

Generalisation and Measurement Boundary

Quantization reduces numerical precision and resource cost but is distinct from pruning, distillation, or architectural compression.

Related technical article: Artificial Intelligence: Philosophy, Theory and Practice.

Direct source: The primary paper or official specification for Quantization is linked here for verification.

Updated: 02.09.2026

Related technical publications

Publications whose title or summary directly references this concept.

Variance-Based Color Quantization

Variance-based color quantization uses moments over RGBA space and repeatedly splits the boxes carrying the greatest error to build a limited palette.

LLM Inference on FPGA with High-Level Synthesis

FPGA LLM inference requires algorithm/hardware co-design across quantization, memory bandwidth, pipelining, on-chip buffers and KV cache.

Image from the Perspective of Basic Sciences

A technical note on digital-image formation through pixels, spatial sampling, quantization, bit depth, the electromagnetic spectrum, optics, camera geometry, sensor behavior, and human vision.

Audio Recording and Transmission

The audio chain from microphone and analog-to-digital conversion through sampling, quantization, bit depth, channel layout, codecs, real-time transport, and clock drift.

Generalisation and Measurement Boundary

Related Machine-Learning Concepts

Variance-Based Color Quantization

LLM Inference on FPGA with High-Level Synthesis

Image from the Perspective of Basic Sciences

Audio Recording and Transmission