Concepts & capability filters
quantization
Quantization reduces LLM precision by mapping high-bit weights and activations (e.g., FP16) to lower-bit representations (e.g., INT8 or INT4), minimizing memory footprint and inference latency.
- Category
- Not classified
- Difficulty
- Not classified
- Aliases
- None tracked
- Last reviewed
- 2026-07-02
Key facts
- Techniques like post-training quantization preserve accuracy by calibrating rounding errors, enabling deployment on resource-constrained hardware.