Is DuQuant superseded?

DuQuant (LLM quantization): superseded — cited as a baseline and beaten by newer methods. 1 paper(s) critique it, 1 beat it on benchmarks — #39 of 80 most-superseded. Sub-problem: cluster led by GPTAQ. Newer alternatives in the same sub-problem include SplitQ, MARR, Quantization-aware Integrated Gradients (QIG), SPEED-Q, Quant-dLLM.

LLM quantization

DuQuant

DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs

Superseded baseline#39 of 80 most-superseded · first seen Jun 3, 2024

Superseded — cited as a baseline and beaten by newer methods

1 papers critique it · 1 beat it on benchmarks

What papers say

Verbatim critique sentences, each from a paper that cites DuQuant as a baseline.

lin2024duquant manually design a zigzag permutation pattern in an attempt to distribute outlier weights throughout the network.

— Exploring Model Invariance with Discrete Search for Ultra-Low-Bit Quantization

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Recent methods in the same sub-problem, not yet superseded in the knowledge base — arXiv benchmark leaders, not vetted production recommendations.

SplitQBreaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models
May 19, 2026
MARRMARR: Module-Adaptive Residual Reconstruction for Low-Bit Post-Training Quantization
May 18, 2026
Quantization-aware Integrated Gradients (QIG)Fine-Grained Post-Training Quantization for Large Vision Language Models with Quantization-Aware Integrated Gradients
Mar 18, 2026
SPEED-QSPEED-Q: Staged Processing with Enhanced Distillation towards Efficient Low-bit On-device VLM Quantization
Nov 12, 2025
Quant-dLLMQuant-dLLM: Post-Training Extreme Low-Bit Quantization for Diffusion Large Language Models
Sep 27, 2025