LLM quantization
QDrop
QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization
Superseded baseline#16 of 80 most-superseded · first seen Mar 11, 2022
Superseded — cited as a baseline and beaten by newer methods
0 papers critique it · 4 beat it on benchmarks
Beaten on benchmarks
Head-to-head results where a newer method reports beating QDrop. Values are copied from the source paper's tables — verify against the cited paper.
MGRQ beats QDrop
70.02 vs 21.24
Top-1 accuracy · [W4/A4]
MGRQ: Post-Training Quantization For Vision Transformer With Mixed Granularity Reconstruction
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Recent methods in the same sub-problem, not yet superseded in the knowledge base — arXiv benchmark leaders, not vetted production recommendations.
- COD-TDQWhen W4A4 Breaks Camouflaged Object Detection: Token-Group Dual-Constraint Activation QuantizationApr 18, 2026
- Joint Post-Training Quantization of Vision Transformers with Learned Prompt-Guided Data GenerationJoint Post-Training Quantization of Vision Transformers with Learned Prompt-Guided Data GenerationFeb 21, 2026