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Image Classification on ImageNet 1K (val) (Single Accuracy Metric)

86.6Accuracy4M-L
78.2880.4482.684.76Jan 9, 2023Jul 19, 2023Jan 27, 2024Aug 5, 2024Feb 13, 2025Aug 23, 2025Mar 3, 2026

Evaluation results

MethodLinks
4M-LProtocol=Fine-tuning (FT), Extra Labels=Yes2026.0386.6
MambaVision-L+MAPResolution=224x224, Parameters=241M, Throughput=229, Memory=78.6G, Pretraining=MAP2024.1086.4
HybridNet-L + MAPResolution=384x384, Parameters=443M, Throughput=63, Pretraining=MAP2024.1086.2
ViT-L/16 + MAPResolution=224x224, Parameters=307M, Throughput=149, Pretraining=MAP2024.1086.1
ViT-L/16 + MAEResolution=224x224, Parameters=307M, Throughput=1492024.1085.9
HybridNet-B + MAPResolution=384x384, Parameters=128M, Throughput=244, Memory=76.1G, Pretraining=MAP2024.1085.5
MambaVision-LResolution=224x224, Parameters=241M, Throughput=229, Memory=78.6G2024.1085.3
HybridNet-L + MAPResolution=224x224, Parameters=443M, Throughput=63, Memory=78.3G, Pretraining=MAP2024.1085
MambaVision-B+MAPResolution=224x224, Parameters=97M, Throughput=826, Memory=50.8G, Pretraining=MAP2024.1084.9
HybridNet-B + MAPResolution=224x224, Parameters=128M, Throughput=244, Memory=30.0G, Pretraining=MAP2024.1084.9
SparKArch.=ConvX-B, Eff. epoch=1600, Fine-tuning resolution=2242023.0184.8
MambaR-L+MAPResolution=224x224, Parameters=341M, Throughput=92, Memory=55.5G, Pretraining=MAP2024.1084.8
STL (FAN-L-Hybrid)Params (M)=77.32024.0184.7
HybridNet-LResolution=384x384, Parameters=443M, Throughput=632024.1084.6
STL (FAN-B-Hybrid)Params (M)=50.92024.0184.5
ARM-L (Mamba+AR)Resolution=224x224, Parameters=297M, Throughput=111, Memory=53.1G2024.1084.5
HybridNet-BResolution=384x384, Parameters=128M, Throughput=244, Memory=76.1G2024.1084.5
FAN-L-HybridParams (M)=76.82024.0184.3
MambaVision-BResolution=224x224, Parameters=97M, Throughput=826, Memory=50.8G2024.1084.2
SimMIMArch.=Swin-B, Eff. epoch=800, Fine-tuning resolution=2242023.0184
LV-ViT-MParams (M)=562024.0184
MambaR-B+MAPResolution=224x224, Parameters=99M, Throughput=315, Memory=20.3G, Pretraining=MAP2024.1084
FAN-B-HybridParams (M)=50.42024.0183.9
M2PT-PointSetting=Pretrained, Evaluation Protocol=tune acc, Backbone=ViT-B2024.0183.9
VMamba-BResolution=224x224, Parameters=89M, Throughput=246, Memory=37.1G2024.1083.9
HybridNet-B + MAEResolution=224x224, Parameters=128M, Throughput=244, Memory=30.0G, Pretraining=MAE2024.1083.9
Supervised (Liu et al., 2022)Arch.=ConvX-B, Eff. epoch=300, Fine-tuning resolution=2242023.0183.8
ConvNext-BParams (M)=88.62024.0183.8
ConvNeXt-BResolution=224x224, Parameters=89M, Throughput=334, Memory=17.9G2024.1083.8
HybridNet-B + ARResolution=224x224, Parameters=128M, Throughput=244, Memory=30.0G, Pretraining=AR2024.1083.8
M2PT-AudioSetting=Pretrained, Evaluation Protocol=tune acc, Backbone=ViT-B2024.0183.7
MambaR-B+ARResolution=224x224, Parameters=99M, Throughput=315, Memory=20.3G2024.1083.7
MAEArch.=ViT-B, Eff. epoch=1600, Fine-tuning resolution=2242023.0183.6
MAE-ViT-BParams (M)=862024.0183.6
MFFSetting=Pretrained, Evaluation Protocol=tune acc, Backbone=ViT-B2024.0183.6
M2PT-VideoSetting=Pretrained, Evaluation Protocol=tune acc, Backbone=ViT-B2024.0183.6
ViT-B/16 + MAEResolution=224x224, Parameters=86M, Throughput=284, Memory=63.8G2024.1083.6
ViT-B/16 + MAPResolution=224x224, Parameters=86M, Throughput=284, Memory=63.8G, Pretraining=MAP2024.1083.6
VMamba-SResolution=224x224, Parameters=50M, Throughput=313, Memory=27.6G2024.1083.6
Supervised (Liu et al., 2021)Arch.=Swin-B, Eff. epoch=300, Fine-tuning resolution=2242023.0183.5
FAN-S-HybridParams (M)=26.32024.0183.5
STL (FAN-S-Hybrid)Params (M)=26.52024.0183.4
Swin-SParams (M)=502024.0183.4
Swin-BParams (M)=87.82024.0183.4
SemMAESetting=Pretrained, Evaluation Protocol=tune acc, Backbone=ViT-B2024.0183.4
LV-ViT-SParams (M)=262024.0183.3
MAESetting=Pretrained, Evaluation Protocol=tune acc, Backbone=ViT-B2024.0183.3
MambaVision-SResolution=224x224, Parameters=51M, Throughput=1058, Memory=36.6G2024.1083.3
MoCov3Arch.=ViT-B, Eff. epoch=1600, Fine-tuning resolution=2242023.0183.2
BEITArch.=ViT-B, Eff. epoch=800, Fine-tuning resolution=2242023.0183.2
MambaR-LResolution=224x224, Parameters=341M, Throughput=92, Memory=55.5G2024.1083.2
ARM-B (Mamba+AR)Resolution=224x224, Parameters=85M, Throughput=325, Memory=19.7G2024.1083.2
HybridNet-LResolution=224x224, Parameters=443M, Throughput=63, Memory=78.3G2024.1083.2
ConvNeXt-SResolution=224x224, Parameters=50M, Throughput=444, Memory=13.1G2024.1083.1
MambaR-B+MAEResolution=224x224, Parameters=99M, Throughput=315, Memory=20.3G2024.1083.1
HybridNet-BResolution=224x224, Parameters=128M, Throughput=244, Memory=30.0G2024.1083.1
HybridNet-B + CLResolution=224x224, Parameters=128M, Throughput=244, Memory=30.0G, Pretraining=CL2024.1083.1
MambaR-BResolution=224x224, Parameters=99M, Throughput=315, Memory=20.3G2024.1082.9
MambaVision-TResolution=224x224, Parameters=35M, Throughput=1349, Memory=10.7G2024.1082.7
DREAMProtocol=Fine-tuning (FT)2026.0382.7
XCIT-S24Params (M)=47.72024.0182.6
RVT-BParams (M)=91.82024.0182.6
E2E-FT + Weight-space ensembleBackbone=CLIP ViT-B/162024.1182.5
E2E-FT + Weight-space ensembleBackbone=ViT-B/16, Ensemble=Weight-space2024.1182.5
ViT-B/16 + ARResolution=224x224, Parameters=86M, Throughput=284, Memory=63.8G2024.1082.5
VMamba-TResolution=224x224, Parameters=31M, Throughput=464, Memory=7.6G2024.1082.5
HybridNet-S + MAPResolution=224x224, Parameters=37M, Throughput=512, Memory=14.6G, Pretraining=MAP2024.1082.5
LP-FT + Weight-space ensembleBackbone=CLIP ViT-B/162024.1182.4
LP-FT + Weight-space ensembleBackbone=ViT-B/16, Ensemble=Weight-space2024.1182.4
Supervised (He et al., 2021)Arch.=ViT-B, Eff. epoch=300, Fine-tuning resolution=2242023.0182.3
E2E-FT + VRFBackbone=CLIP ViT-B/162024.1182.3
E2E-FT + VRFBackbone=ViT-B/16, Method=Variance Reduction Fine-tuning2024.1182.3
E2E-FT + Output-space ensembleBackbone=CLIP ViT-B/162024.1182.2
E2E-FT + Output-space ensembleBackbone=ViT-B/16, Ensemble=Output-space2024.1182.2
ConvNext-TParams (M)=28.62024.0182.1
ConvNext-SParams (M)=50.22024.0182.1
LP-FT + Output-space ensembleBackbone=CLIP ViT-B/162024.1182.1
LP-FT + VRFBackbone=CLIP ViT-B/162024.1182.1
LP-FT + Output-space ensembleBackbone=ViT-B/16, Ensemble=Output-space2024.1182.1
LP-FT + VRFBackbone=ViT-B/16, Method=Variance Reduction Fine-tuning2024.1182.1
ConvNeXt-TResolution=224x224, Parameters=29M, Throughput=701, Memory=8.3G2024.1082.1
RVT-SParams (M)=23.32024.0181.9
XCIT-S12Params (M)=26.32024.0181.9
M2PT-PointSetting=From-scratch, Evaluation Protocol=tune acc, Backbone=ViT-B2024.0181.9
EfficientNet-B3Resolution=300x300, Parameters=12M, Throughput=496, Memory=19.7G2024.1081.6
DAT-AugReg-ViTParams (M)=862024.0181.5
LP-FTBackbone=CLIP ViT-B/162024.1181.5
LP-FTBackbone=ViT-B/16, Protocol=Linear-probing then fine-tuning2024.1181.5
E2E-FTBackbone=CLIP ViT-B/162024.1181.3
E2E-FTBackbone=ViT-B/16, Protocol=End-to-end fine-tuning2024.1181.3
HybridNet-SResolution=224x224, Parameters=37M, Throughput=512, Memory=14.6G2024.1081.3
Swin-TParams (M)=28.32024.0181.2
MambaR-SResolution=224x224, Parameters=28M, Throughput=608, Memory=9.9G2024.1081.1
iBOTEvaluation Protocol=Fine-tuning2026.0280.72
Vim-SResolution=224x224, Parameters=26M, Throughput=612, Memory=9.4G2024.1080.5
STELLAREvaluation Protocol=Fine-tuning2026.0280.05
DINOEvaluation Protocol=Fine-tuning2026.0279.58
Linear classifierBackbone=CLIP ViT-B/162024.1179.3
Linear classifierBackbone=ViT-B/16, Protocol=Linear probing2024.1179.3
HybridNet-T + MAPResolution=224x224, Parameters=12M, Throughput=910, Memory=7.6G, Pretraining=MAP2024.1078.6