Image Classification on CIFAR-10 (Pruning Performance and Efficiency) benchmark leaderboard · SOTA2 Research

Image Classification on CIFAR-10 (Pruning Performance and Efficiency)

94.48Top-1 Accuracy (Base)SCOP

Evaluation Results

Method	Links
SCOP2025.05		94.48	94.24	-0.24	1.67
AMC2025.05		94.48	93.48	-1	1.86
Random Pruning2025.05		94.48	92.51	-1.97	1.93
CoSeP2025.05		94.48	94.81	0.33	1.93
AAP2025.05		94.46	94.7	0.24	1.97
ATO2025.05		94.45	94.78	0.33	1.84
DMC2025.05		94.23	94.49	0.26	1.66
Electrostatic-p2025.05		94.05	93.88	-0.17	2.17
DECORE-5002025.05		93.96	94.02	0.06	2.35
CSPrune2025.05		93.75	92.57	-1.18	2.55
HRank2025.05		93.64	93.11	-0.53	2.15
AAP2025.05		93.64	93.82	0.18	2.57
SNF2025.05		93.61	93.75	0.14	2.13
FPGM2025.05		93.59	93.26	-0.33	2.11
Random Pruning2025.05		93.58	91.75	-1.83	2.28
CoSeP2025.05		93.58	93.82	0.24	2.28
AMC2025.05		93.55	92.15	-1.4	1.98
Random Pruning2025.05		93.55	91.88	-1.67	2.59
CoSeP2025.05		93.55	93.92	0.37	2.59
GReg2025.05		93.51	93.28	-0.23	1.99
ATO2025.05		93.5	93.74	0.24	2.22
Torque2025.05		93.48	93.76	0.28	2.15
CSPrune2025.05		93.39	90.6	-2.79	2.13
GCNP2025.05		93.27	93.08	-0.19	2.34
DECORE-4502025.05		93.26	93.34	0.08	1.32
DECORE-2002025.05		93.26	93.26	0	2
HRank2025.05		93.26	93.17	-0.09	2
ABCPruner2025.05		93.26	93.23	-0.03	2.18
AAP2025.05		92.84	91.78	-1.06	2.17
SCOP2025.05		92.84	92.9	0.06	2.27
AMC2025.05		92.8	91.9	-0.9	2
CP2025.05		92.8	91.8	-1	2