SFMP (LLM quantization): superseded — cited as a baseline and beaten by newer methods. 0 paper(s) critique it, 1 beat it on benchmarks — #64 of 80 most-superseded. Sub-problem: cluster led by AMQ. Newer alternatives in the same sub-problem include SignRoundV2.

LLM quantization

SFMP

SFMP: Fine-Grained, Hardware-Friendly and Search-Free Mixed-Precision Quantization for Large Language Models

Superseded baseline#64 of 80 most-superseded · first seen Feb 1, 2026

Superseded — cited as a baseline and beaten by newer methods

0 papers critique it · 1 beat it on benchmarks

Beaten on benchmarks

Head-to-head results where a newer method reports beating SFMP. Values are copied from the source paper's tables — verify against the cited paper.

SignRoundV2 beats SFMP
68.57 vs 64.34
Avg · [Llama3.1-8B, Avg Bits 2.5]
SignRoundV2: Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs

What to use instead

Recent methods in the same sub-problem, not yet superseded in the knowledge base — arXiv benchmark leaders, not vetted production recommendations.

SignRoundV2SignRoundV2: Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs
Dec 4, 2025