model,infer_img_size,infer_batch_size,infer_samples_per_sec,infer_step_time,infer_gmacs,infer_macts,param_count
tinynet_e,106,1024.0,50604.03,20.225,0.03,0.69,2.04
mobilenetv3_small_050,224,1024.0,46069.42,22.217,0.03,0.92,1.59
lcnet_035,224,1024.0,41190.64,24.85,0.03,1.04,1.64
lcnet_050,224,1024.0,37663.82,27.178,0.05,1.26,1.88
mobilenetv3_small_075,224,1024.0,33398.64,30.649,0.05,1.3,2.04
efficientvit_m0,224,1024.0,32179.13,31.812,0.08,0.91,2.35
mobilenetv3_small_100,224,1024.0,29653.41,34.522,0.06,1.42,2.54
tf_mobilenetv3_small_minimal_100,224,1024.0,28352.57,36.106,0.06,1.41,2.04
tinynet_d,152,1024.0,27612.87,37.074,0.05,1.42,2.34
tf_mobilenetv3_small_075,224,1024.0,27505.95,37.218,0.05,1.3,2.04
tf_mobilenetv3_small_100,224,1024.0,24859.95,41.18,0.06,1.42,2.54
efficientvit_m1,224,1024.0,24836.87,41.219,0.17,1.33,2.98
lcnet_075,224,1024.0,24184.78,42.33,0.1,1.99,2.36
efficientvit_m2,224,1024.0,21907.95,46.731,0.2,1.47,4.19
mnasnet_small,224,1024.0,20764.95,49.303,0.07,2.16,2.03
levit_128s,224,1024.0,20669.44,49.531,0.31,1.88,7.78
lcnet_100,224,1024.0,19774.93,51.772,0.16,2.52,2.95
regnetx_002,224,1024.0,18945.55,54.04,0.2,2.16,2.68
resnet10t,176,1024.0,18840.28,54.342,0.7,1.51,5.44
efficientvit_m3,224,1024.0,18627.14,54.963,0.27,1.62,6.9
mobilenetv2_035,224,1024.0,18464.78,55.447,0.07,2.86,1.68
ghostnet_050,224,1024.0,17741.46,57.707,0.05,1.77,2.59
resnet18,160,1024.0,17592.15,58.198,0.93,1.27,11.69
regnety_002,224,1024.0,17571.32,58.267,0.2,2.17,3.16
levit_conv_128s,224,1024.0,17529.9,58.404,0.31,1.88,7.78
efficientvit_m4,224,1024.0,17446.52,58.683,0.3,1.7,8.8
repghostnet_050,224,1024.0,17090.91,59.904,0.05,2.02,2.31
efficientvit_b0,224,1024.0,16784.26,60.999,0.1,2.87,3.41
vit_tiny_r_s16_p8_224,224,1024.0,16479.31,62.128,0.43,1.85,6.34
vit_small_patch32_224,224,1024.0,15974.78,64.091,1.12,2.09,22.88
mnasnet_050,224,1024.0,15859.35,64.557,0.11,3.07,2.22
mobilenetv2_050,224,1024.0,14885.11,68.783,0.1,3.64,1.97
tinynet_c,184,1024.0,14726.2,69.525,0.11,2.87,2.46
pit_ti_224,224,1024.0,14628.51,69.989,0.5,2.75,4.85
pit_ti_distilled_224,224,1024.0,14546.3,70.385,0.51,2.77,5.1
semnasnet_050,224,1024.0,14351.42,71.341,0.11,3.44,2.08
levit_128,224,1024.0,14192.78,72.139,0.41,2.71,9.21
repghostnet_058,224,1024.0,13482.93,75.937,0.07,2.59,2.55
mixer_s32_224,224,1024.0,13082.53,78.262,1.0,2.28,19.1
cs3darknet_focus_s,256,1024.0,12838.86,79.748,0.69,2.7,3.27
regnetx_004,224,1024.0,12620.59,81.127,0.4,3.14,5.16
levit_conv_128,224,1024.0,12584.5,81.359,0.41,2.71,9.21
cs3darknet_s,256,1024.0,12531.56,81.703,0.72,2.97,3.28
lcnet_150,224,1024.0,12510.06,81.844,0.34,3.79,4.5
regnetx_004_tv,224,1024.0,12294.91,83.276,0.42,3.17,5.5
efficientvit_m5,224,1024.0,12067.16,84.847,0.53,2.41,12.47
mobilenetv3_large_075,224,1024.0,12041.45,85.029,0.16,4.0,3.99
levit_192,224,1024.0,11986.94,85.416,0.66,3.2,10.95
resnet10t,224,1024.0,11963.05,85.587,1.1,2.43,5.44
gernet_s,224,1024.0,11809.29,86.701,0.75,2.65,8.17
ese_vovnet19b_slim_dw,224,1024.0,11618.32,88.126,0.4,5.28,1.9
vit_tiny_patch16_224,224,1024.0,11270.42,90.846,1.08,4.12,5.72
deit_tiny_patch16_224,224,1024.0,11259.37,90.936,1.08,4.12,5.72
deit_tiny_distilled_patch16_224,224,1024.0,11217.54,91.275,1.09,4.15,5.91
repghostnet_080,224,1024.0,11079.58,92.412,0.1,3.22,3.28
mobilenetv3_rw,224,1024.0,10908.78,93.859,0.23,4.41,5.48
levit_conv_192,224,1024.0,10768.96,95.077,0.66,3.2,10.95
mobilenetv3_large_100,224,1024.0,10731.24,95.412,0.23,4.41,5.48
hardcorenas_a,224,1024.0,10620.31,96.408,0.23,4.38,5.26
tf_mobilenetv3_large_075,224,1024.0,10495.83,97.552,0.16,4.0,3.99
resnet14t,176,1024.0,10451.45,97.965,1.07,3.61,10.08
mnasnet_075,224,1024.0,10423.24,98.231,0.23,4.77,3.17
tf_mobilenetv3_large_minimal_100,224,1024.0,10369.07,98.745,0.22,4.4,3.92
resnet34,160,1024.0,10330.89,99.109,1.87,1.91,21.8
regnety_004,224,1024.0,9931.33,103.097,0.41,3.89,4.34
nf_regnet_b0,192,1024.0,9884.05,103.59,0.37,3.15,8.76
regnetx_006,224,1024.0,9823.29,104.232,0.61,3.98,6.2
hardcorenas_b,224,1024.0,9755.67,104.953,0.26,5.09,5.18
hardcorenas_c,224,1024.0,9572.88,106.958,0.28,5.01,5.52
ghostnet_100,224,1024.0,9528.83,107.453,0.15,3.55,5.18
tf_mobilenetv3_large_100,224,1024.0,9484.05,107.96,0.23,4.41,5.48
tinynet_b,188,1024.0,9358.37,109.409,0.21,4.44,3.73
mnasnet_100,224,1024.0,9357.9,109.416,0.33,5.46,4.38
tf_efficientnetv2_b0,192,1024.0,9316.15,109.906,0.54,3.51,7.14
repghostnet_100,224,1024.0,9303.14,110.06,0.15,3.98,4.07
mobilenetv2_075,224,1024.0,9280.78,110.325,0.22,5.86,2.64
resnet18,224,1024.0,9222.44,111.023,1.82,2.48,11.69
pit_xs_distilled_224,224,1024.0,9172.76,111.624,1.11,4.15,11.0
semnasnet_075,224,1024.0,9145.4,111.959,0.23,5.54,2.91
pit_xs_224,224,1024.0,9134.12,112.096,1.1,4.12,10.62
regnety_006,224,1024.0,9106.78,112.433,0.61,4.33,6.06
convnext_atto,224,1024.0,8993.29,113.851,0.55,3.81,3.7
hardcorenas_d,224,1024.0,8915.53,114.845,0.3,4.93,7.5
levit_256,224,1024.0,8893.96,115.124,1.13,4.23,18.89
seresnet18,224,1024.0,8718.39,117.442,1.82,2.49,11.78
convnext_atto_ols,224,1024.0,8549.03,119.769,0.58,4.11,3.7
mobilenetv2_100,224,1024.0,8479.08,120.757,0.31,6.68,3.5
legacy_seresnet18,224,1024.0,8452.0,121.144,1.82,2.49,11.78
spnasnet_100,224,1024.0,8438.72,121.334,0.35,6.03,4.42
repghostnet_111,224,1024.0,8382.7,122.146,0.18,4.38,4.54
semnasnet_100,224,1024.0,8351.88,122.597,0.32,6.23,3.89
dla46_c,224,1024.0,8209.51,124.721,0.58,4.5,1.3
repvgg_a0,224,1024.0,8124.8,126.024,1.52,3.59,9.11
levit_conv_256,224,1024.0,7997.32,128.032,1.13,4.23,18.89
edgenext_xx_small,256,1024.0,7955.06,128.711,0.26,3.33,1.33
regnetx_008,224,1024.0,7889.15,129.787,0.81,5.15,7.26
resnet18d,224,1024.0,7873.83,130.041,2.06,3.29,11.71
convnext_femto,224,1024.0,7867.13,130.151,0.79,4.57,5.22
ese_vovnet19b_slim,224,1024.0,7834.56,130.693,1.69,3.52,3.17
mobilevit_xxs,256,1024.0,7818.95,130.953,0.34,5.74,1.27
hardcorenas_f,224,1024.0,7811.68,131.075,0.35,5.57,8.2
hardcorenas_e,224,1024.0,7751.65,132.09,0.35,5.65,8.07
efficientnet_lite0,224,1024.0,7716.09,132.699,0.4,6.74,4.65
xcit_nano_12_p16_224,224,1024.0,7711.63,132.776,0.56,4.17,3.05
ghostnet_130,224,1024.0,7680.26,133.318,0.24,4.6,7.36
levit_256d,224,1024.0,7643.23,133.964,1.4,4.93,26.21
tf_efficientnetv2_b0,224,1024.0,7637.19,134.07,0.73,4.77,7.14
repghostnet_130,224,1024.0,7550.55,135.609,0.25,5.24,5.48
convnext_femto_ols,224,1024.0,7514.81,136.254,0.82,4.87,5.23
regnety_008,224,1024.0,7508.88,136.361,0.81,5.25,6.26
tinynet_a,192,1024.0,7458.0,137.291,0.35,5.41,6.19
fbnetc_100,224,1024.0,7362.02,139.082,0.4,6.51,5.57
tf_efficientnetv2_b1,192,1024.0,7241.64,141.394,0.76,4.59,8.14
crossvit_tiny_240,240,1024.0,7093.57,144.345,1.3,5.67,7.01
regnety_008_tv,224,1024.0,7067.28,144.882,0.84,5.42,6.43
mobilevitv2_050,256,1024.0,7057.9,145.075,0.48,8.04,1.37
crossvit_9_240,240,1024.0,6964.15,147.028,1.55,5.59,8.55
dla46x_c,224,1024.0,6837.04,149.761,0.54,5.66,1.07
tf_efficientnet_lite0,224,1024.0,6819.73,150.142,0.4,6.74,4.65
efficientnet_b0,224,1024.0,6721.47,152.337,0.4,6.75,5.29
rexnet_100,224,1024.0,6689.15,153.073,0.41,7.44,4.8
rexnetr_100,224,1024.0,6646.85,154.047,0.43,7.72,4.88
levit_conv_256d,224,1024.0,6618.0,154.719,1.4,4.93,26.21
repvit_m1,224,1024.0,6591.52,155.339,0.83,7.45,5.49
efficientnet_b1_pruned,240,1024.0,6583.2,155.537,0.4,6.21,6.33
repghostnet_150,224,1024.0,6564.41,155.982,0.32,6.0,6.58
mnasnet_140,224,1024.0,6559.1,156.108,0.6,7.71,7.12
efficientvit_b1,224,1024.0,6458.82,158.532,0.53,7.25,9.1
visformer_tiny,224,1024.0,6456.3,158.594,1.27,5.72,10.32
crossvit_9_dagger_240,240,1024.0,6436.13,159.091,1.68,6.03,8.78
resnet14t,224,1024.0,6404.13,159.886,1.69,5.8,10.08
dla60x_c,224,1024.0,6404.11,159.885,0.59,6.01,1.32
mobilenetv2_110d,224,1024.0,6387.15,160.311,0.45,8.71,4.52
ghostnetv2_100,224,1024.0,6375.73,160.599,0.18,4.55,6.16
regnetz_005,224,1024.0,6372.66,160.676,0.52,5.86,7.12
repvit_m0_9,224,1024.0,6295.33,162.649,0.83,7.45,5.49
edgenext_xx_small,288,1024.0,6241.41,164.053,0.33,4.21,1.33
fbnetv3_b,224,1024.0,6166.1,166.058,0.42,6.97,8.6
convnext_pico,224,1024.0,6145.95,166.603,1.37,6.1,9.05
cs3darknet_focus_m,256,1024.0,6145.46,166.616,1.98,4.89,9.3
pvt_v2_b0,224,1024.0,6126.38,167.135,0.53,7.01,3.67
tf_efficientnet_b0,224,1024.0,6026.91,169.894,0.4,6.75,5.29
nf_regnet_b0,256,1024.0,5970.36,171.503,0.64,5.58,8.76
resnetblur18,224,1024.0,5963.74,171.694,2.34,3.39,11.69
ese_vovnet19b_dw,224,1024.0,5956.2,171.911,1.34,8.25,6.54
hrnet_w18_small,224,1024.0,5950.21,172.083,1.61,5.72,13.19
resnet50,160,1024.0,5943.32,172.284,2.1,5.67,25.56
repvgg_a1,224,1024.0,5891.09,173.812,2.64,4.74,14.09
cs3darknet_m,256,1024.0,5871.36,174.395,2.08,5.28,9.31
convnext_pico_ols,224,1024.0,5852.38,174.961,1.43,6.5,9.06
vit_base_patch32_clip_224,224,1024.0,5768.1,177.517,4.37,4.19,88.22
tf_efficientnetv2_b2,208,1024.0,5753.76,177.96,1.06,6.0,10.1
vit_base_patch32_224,224,1024.0,5748.7,178.117,4.37,4.19,88.22
semnasnet_140,224,1024.0,5744.77,178.239,0.6,8.87,6.11
skresnet18,224,1024.0,5740.29,178.378,1.82,3.24,11.96
vit_tiny_r_s16_p8_384,384,1024.0,5663.72,180.79,1.25,5.39,6.36
resnet50d,160,1024.0,5651.35,181.185,2.22,6.08,25.58
resnet18,288,1024.0,5636.85,181.651,3.01,4.11,11.69
mobilenetv2_140,224,1024.0,5629.57,181.886,0.6,9.57,6.11
vit_small_patch32_384,384,1024.0,5499.31,186.195,3.26,6.07,22.92
convnext_atto,288,1024.0,5487.38,186.599,0.91,6.3,3.7
efficientnet_b0_gn,224,1024.0,5481.83,186.788,0.42,6.75,5.29
selecsls42,224,1024.0,5458.22,187.596,2.94,4.62,30.35
efficientnet_lite1,240,1024.0,5452.84,187.782,0.62,10.14,5.42
fbnetv3_d,224,1024.0,5449.6,187.893,0.52,8.5,10.31
pit_s_224,224,1024.0,5438.08,188.291,2.42,6.18,23.46
selecsls42b,224,1024.0,5414.81,189.1,2.98,4.62,32.46
resnet34,224,1024.0,5413.46,189.147,3.67,3.74,21.8
pit_s_distilled_224,224,1024.0,5407.14,189.368,2.45,6.22,24.04
efficientvit_b1,256,1024.0,5391.26,189.926,0.69,9.46,9.1
seresnet18,288,1024.0,5348.84,191.432,3.01,4.11,11.78
tf_efficientnetv2_b1,240,1024.0,5293.37,193.439,1.21,7.34,8.14
levit_384,224,1024.0,5286.23,193.7,2.36,6.26,39.13
convnextv2_atto,224,1024.0,5265.85,194.45,0.55,3.81,3.71
repvit_m1_0,224,1024.0,5259.32,194.683,1.13,8.69,7.3
seresnet50,160,1024.0,5236.4,195.543,2.1,5.69,28.09
convnext_atto_ols,288,1024.0,5201.4,196.86,0.96,6.8,3.7
gernet_m,224,1024.0,5195.05,197.1,3.02,5.24,21.14
fbnetv3_b,256,1024.0,5178.49,197.729,0.55,9.1,8.6
mixnet_s,224,1024.0,5129.76,199.608,0.25,6.25,4.13
repghostnet_200,224,1024.0,5125.91,199.759,0.54,7.96,9.8
vit_base_patch32_clip_quickgelu_224,224,1024.0,5125.16,199.787,4.37,4.19,87.85
seresnet34,224,1024.0,5104.13,200.612,3.67,3.74,21.96
repvit_m2,224,1024.0,5098.16,200.845,1.36,9.43,8.8
rexnetr_130,224,1024.0,5082.35,201.471,0.68,9.81,7.61
efficientnet_b0_g16_evos,224,1024.0,5016.04,204.134,1.01,7.42,8.11
ghostnetv2_130,224,1024.0,5011.79,204.307,0.28,5.9,8.96
edgenext_x_small,256,1024.0,4992.08,205.112,0.54,5.93,2.34
ecaresnet50t,160,1024.0,4989.39,205.225,2.21,6.04,25.57
tiny_vit_5m_224,224,1024.0,4963.53,206.293,1.18,9.32,12.08
rexnet_130,224,1024.0,4939.41,207.301,0.68,9.71,7.56
legacy_seresnet34,224,1024.0,4938.49,207.34,3.67,3.74,21.96
eva02_tiny_patch14_224,224,1024.0,4931.19,207.646,1.4,6.17,5.5
resnet34d,224,1024.0,4924.89,207.912,3.91,4.54,21.82
tf_efficientnet_lite1,240,1024.0,4918.8,208.17,0.62,10.14,5.42
mixer_b32_224,224,1024.0,4917.45,208.227,3.24,6.29,60.29
resnet50,176,1024.0,4914.58,208.348,2.62,6.92,25.56
resnetrs50,160,1024.0,4904.24,208.788,2.29,6.2,35.69
xcit_tiny_12_p16_224,224,1024.0,4900.19,208.961,1.24,6.29,6.72
repvit_m1_1,224,1024.0,4858.32,210.759,1.36,9.43,8.8
levit_conv_384,224,1024.0,4851.29,211.066,2.36,6.26,39.13
efficientnet_es_pruned,224,1024.0,4832.02,211.909,1.81,8.73,5.44
efficientnet_es,224,1024.0,4828.47,212.065,1.81,8.73,5.44
dla34,224,1024.0,4823.61,212.277,3.07,5.02,15.74
resnet26,224,1024.0,4806.46,213.036,2.36,7.35,16.0
resnet18d,288,1024.0,4806.17,213.049,3.41,5.43,11.71
resnext50_32x4d,160,1024.0,4797.48,213.435,2.17,7.35,25.03
tf_mixnet_s,224,1024.0,4783.68,214.05,0.25,6.25,4.13
convnext_femto,288,1024.0,4774.19,214.475,1.3,7.56,5.22
efficientnet_b1,224,1024.0,4707.45,217.516,0.59,9.36,7.79
gmlp_ti16_224,224,1024.0,4694.71,218.108,1.34,7.55,5.87
cs3darknet_focus_m,288,1024.0,4686.36,218.495,2.51,6.19,9.3
mobilenetv2_120d,224,1024.0,4673.25,219.108,0.69,11.97,5.83
selecsls60,224,1024.0,4656.74,219.885,3.59,5.52,30.67
selecsls60b,224,1024.0,4628.67,221.219,3.63,5.52,32.77
tf_efficientnet_es,224,1024.0,4617.85,221.737,1.81,8.73,5.44
resmlp_12_224,224,1024.0,4607.73,222.224,3.01,5.5,15.35
vit_small_patch16_224,224,1024.0,4586.65,223.246,4.25,8.25,22.05
deit_small_patch16_224,224,1024.0,4584.29,223.359,4.25,8.25,22.05
fbnetv3_d,256,1024.0,4567.33,224.19,0.68,11.1,10.31
gmixer_12_224,224,1024.0,4565.4,224.285,2.67,7.26,12.7
deit_small_distilled_patch16_224,224,1024.0,4564.97,224.306,4.27,8.29,22.44
convnext_femto_ols,288,1024.0,4561.96,224.454,1.35,8.06,5.23
efficientnet_b0_g8_gn,224,1024.0,4561.27,224.488,0.66,6.75,6.56
efficientnet_cc_b0_8e,224,1024.0,4542.29,225.426,0.42,9.42,24.01
efficientnet_cc_b0_4e,224,1024.0,4540.5,225.515,0.41,9.42,13.31
repvgg_b0,224,1024.0,4526.99,226.188,3.41,6.15,15.82
mixer_s16_224,224,1024.0,4518.8,226.598,3.79,5.97,18.53
cs3darknet_m,288,1024.0,4513.42,226.868,2.63,6.69,9.31
convnextv2_femto,224,1024.0,4509.16,227.082,0.79,4.57,5.23
regnetx_016,224,1024.0,4476.6,228.734,1.62,7.93,9.19
nf_regnet_b1,256,1024.0,4444.68,230.377,0.82,7.27,10.22
vit_base_patch32_clip_256,256,1024.0,4442.76,230.476,5.68,5.44,87.86
mobilevitv2_075,256,1024.0,4419.22,231.704,1.05,12.06,2.87
rexnetr_150,224,1024.0,4415.72,231.888,0.89,11.13,9.78
darknet17,256,1024.0,4402.14,232.603,3.26,7.18,14.3
resnet26d,224,1024.0,4396.77,232.887,2.6,8.15,16.01
resnetaa34d,224,1024.0,4381.9,233.677,4.43,5.07,21.82
efficientnet_b2_pruned,260,1024.0,4356.91,235.018,0.73,9.13,8.31
convnext_nano,224,1024.0,4340.39,235.913,2.46,8.37,15.59
ecaresnet50d_pruned,224,1024.0,4337.48,236.07,2.53,6.43,19.94
efficientformer_l1,224,1024.0,4271.29,239.728,1.3,5.53,12.29
nf_resnet26,224,1024.0,4216.31,242.856,2.41,7.35,16.0
deit3_small_patch16_224,224,1024.0,4203.29,243.607,4.25,8.25,22.06
nf_regnet_b2,240,1024.0,4197.9,243.92,0.97,7.23,14.31
tf_efficientnet_cc_b0_4e,224,1024.0,4196.5,244.002,0.41,9.42,13.31
tf_efficientnet_cc_b0_8e,224,1024.0,4190.23,244.367,0.42,9.42,24.01
regnety_016,224,1024.0,4161.97,246.026,1.63,8.04,11.2
rexnet_150,224,1024.0,4147.2,246.903,0.9,11.21,9.73
ghostnetv2_160,224,1024.0,4116.92,248.718,0.42,7.23,12.39
tiny_vit_11m_224,224,1024.0,4086.56,250.566,1.9,10.73,20.35
poolformer_s12,224,1024.0,4071.24,251.51,1.82,5.53,11.92
regnetz_005,288,1024.0,4056.8,252.404,0.86,9.68,7.12
efficientnet_lite2,260,1024.0,4046.71,253.034,0.89,12.9,6.09
darknet21,256,1024.0,4001.6,255.887,3.93,7.47,20.86
efficientvit_b1,288,1024.0,3997.55,256.145,0.87,11.96,9.1
resnext50_32x4d,176,1024.0,3992.51,256.47,2.71,8.97,25.03
edgenext_x_small,288,1024.0,3965.96,258.184,0.68,7.5,2.34
efficientnet_b1,256,1024.0,3961.36,258.486,0.77,12.22,7.79
convnext_nano_ols,224,1024.0,3944.64,259.582,2.65,9.38,15.65
resnest14d,224,1024.0,3932.19,260.404,2.76,7.33,10.61
tf_efficientnet_b1,240,1024.0,3922.37,261.055,0.71,10.88,7.79
flexivit_small,240,1024.0,3913.54,261.645,4.88,9.46,22.06
mobilevit_xs,256,768.0,3904.8,196.672,0.93,13.62,2.32
regnetz_b16,224,1024.0,3893.58,262.986,1.45,9.95,9.72
sedarknet21,256,1024.0,3874.2,264.302,3.93,7.47,20.95
resnext26ts,256,1024.0,3832.52,267.176,2.43,10.52,10.3
mobileone_s1,224,1024.0,3826.99,267.562,0.86,9.67,4.83
tf_efficientnetv2_b2,260,1024.0,3817.93,268.197,1.72,9.84,10.1
edgenext_small,256,1024.0,3770.23,271.588,1.26,9.07,5.59
convnext_pico,288,1024.0,3731.48,274.411,2.27,10.08,9.05
gernet_l,256,1024.0,3727.69,274.69,4.57,8.0,31.08
seresnext26ts,256,1024.0,3724.62,274.916,2.43,10.52,10.39
eca_resnext26ts,256,1024.0,3723.07,275.031,2.43,10.52,10.3
dpn48b,224,1024.0,3716.75,275.497,1.69,8.92,9.13
tf_efficientnet_lite2,260,1024.0,3695.32,277.096,0.89,12.9,6.09
gcresnext26ts,256,1024.0,3691.17,277.409,2.43,10.53,10.48
efficientnet_b2,256,1024.0,3671.26,278.912,0.89,12.81,9.11
nf_ecaresnet26,224,1024.0,3640.87,281.24,2.41,7.36,16.0
resnetblur18,288,1024.0,3639.91,281.314,3.87,5.6,11.69
nf_seresnet26,224,1024.0,3637.43,281.506,2.41,7.36,17.4
resnet101,160,1024.0,3616.15,283.164,4.0,8.28,44.55
vit_relpos_small_patch16_224,224,1024.0,3590.52,285.183,4.24,9.38,21.98
resnet26t,256,1024.0,3578.9,286.111,3.35,10.52,16.01
vit_srelpos_small_patch16_224,224,1024.0,3572.97,286.585,4.23,8.49,21.97
convnext_pico_ols,288,1024.0,3558.03,287.789,2.37,10.74,9.06
cs3darknet_focus_l,256,1024.0,3544.69,288.872,4.66,8.03,21.15
tf_efficientnetv2_b3,240,1024.0,3543.38,288.978,1.93,9.95,14.36
legacy_seresnext26_32x4d,224,1024.0,3516.72,291.169,2.49,9.39,16.79
pvt_v2_b1,224,1024.0,3507.87,291.903,2.04,14.01,14.01
repvit_m3,224,1024.0,3501.61,292.425,1.89,13.94,10.68
repvgg_a2,224,1024.0,3495.75,292.916,5.7,6.26,28.21
efficientnetv2_rw_t,224,1024.0,3486.59,293.686,1.93,9.94,13.65
ecaresnet101d_pruned,224,1024.0,3483.13,293.977,3.48,7.69,24.88
ese_vovnet19b_dw,288,1024.0,3478.51,294.369,2.22,13.63,6.54
mixnet_m,224,1024.0,3474.22,294.731,0.36,8.19,5.01
edgenext_small_rw,256,1024.0,3458.08,296.106,1.58,9.51,7.83
convnextv2_pico,224,1024.0,3458.0,296.113,1.37,6.1,9.07
gc_efficientnetv2_rw_t,224,1024.0,3445.15,297.218,1.94,9.97,13.68
cs3darknet_l,256,1024.0,3414.99,299.845,4.86,8.55,21.16
efficientnet_b3_pruned,300,1024.0,3412.19,300.09,1.04,11.86,9.86
nf_regnet_b1,288,1024.0,3373.08,303.57,1.02,9.2,10.22
tf_mixnet_m,224,1024.0,3353.29,305.361,0.36,8.19,5.01
convit_tiny,224,1024.0,3342.83,306.316,1.26,7.94,5.71
eca_botnext26ts_256,256,1024.0,3341.38,306.449,2.46,11.6,10.59
ecaresnext50t_32x4d,224,1024.0,3327.77,307.703,2.7,10.09,15.41
ecaresnext26t_32x4d,224,1024.0,3321.66,308.269,2.7,10.09,15.41
resnet34,288,1024.0,3320.08,308.416,6.07,6.18,21.8
seresnext26t_32x4d,224,1024.0,3319.26,308.491,2.7,10.09,16.81
vit_tiny_patch16_384,384,1024.0,3311.59,309.206,3.16,12.08,5.79
vit_base_patch32_plus_256,256,1024.0,3301.22,310.177,7.7,6.35,119.48
seresnext26d_32x4d,224,1024.0,3300.83,310.214,2.73,10.19,16.81
skresnet34,224,1024.0,3294.57,310.803,3.67,5.13,22.28
mobilevitv2_100,256,768.0,3290.58,233.384,1.84,16.08,4.9
vit_relpos_small_patch16_rpn_224,224,1024.0,3279.29,312.245,4.24,9.38,21.97
eca_halonext26ts,256,1024.0,3270.39,313.1,2.44,11.46,10.76
coatnet_pico_rw_224,224,1024.0,3250.74,314.993,1.96,12.91,10.85
rexnetr_200,224,768.0,3238.38,237.146,1.59,15.11,16.52
ecaresnet26t,256,1024.0,3228.23,317.19,3.35,10.53,16.01
ecaresnetlight,224,1024.0,3222.96,317.708,4.11,8.42,30.16
coatnext_nano_rw_224,224,1024.0,3218.47,318.153,2.36,10.68,14.7
cs3sedarknet_l,256,1024.0,3218.11,318.188,4.86,8.56,21.91
coat_lite_tiny,224,1024.0,3216.35,318.362,1.6,11.65,5.72
nf_regnet_b2,272,1024.0,3205.43,319.447,1.22,9.27,14.31
convnextv2_atto,288,1024.0,3199.9,319.999,0.91,6.3,3.71
vit_small_r26_s32_224,224,1024.0,3174.89,322.52,3.54,9.44,36.43
botnet26t_256,256,1024.0,3173.81,322.63,3.32,11.98,12.49
resnetv2_50,224,1024.0,3170.95,322.919,4.11,11.11,25.55
fastvit_t8,256,1024.0,3164.9,323.538,0.7,8.63,4.03
crossvit_small_240,240,1024.0,3164.86,323.541,5.09,11.34,26.86
bat_resnext26ts,256,1024.0,3139.26,326.18,2.53,12.51,10.73
seresnet34,288,1024.0,3136.77,326.439,6.07,6.18,21.96
halonet26t,256,1024.0,3132.55,326.879,3.19,11.69,12.48
lambda_resnet26t,256,1024.0,3123.88,327.786,3.02,11.87,10.96
rexnet_200,224,768.0,3120.89,246.073,1.56,14.91,16.37
vit_small_resnet26d_224,224,1024.0,3106.26,329.645,5.04,10.65,63.61
hrnet_w18_small_v2,224,1024.0,3095.42,330.8,2.62,9.65,15.6
mobileone_s2,224,1024.0,3085.91,331.82,1.34,11.55,7.88
vit_relpos_base_patch32_plus_rpn_256,256,1024.0,3081.88,332.247,7.59,6.63,119.42
tresnet_m,224,1024.0,3073.78,333.129,5.75,7.31,31.39
resnet32ts,256,1024.0,3072.91,333.224,4.63,11.58,17.96
coatnet_nano_cc_224,224,1024.0,3066.72,333.896,2.13,13.1,13.76
resnet101,176,1024.0,3047.24,336.031,4.92,10.08,44.55
resnet33ts,256,1024.0,3032.6,337.653,4.76,11.66,19.68
efficientvit_b2,224,1024.0,3030.14,337.927,1.6,14.62,24.33
resnet50,224,1024.0,3021.24,338.922,4.11,11.11,25.56
coat_lite_mini,224,1024.0,3021.22,338.925,2.0,12.25,11.01
resnet34d,288,1024.0,3013.98,339.739,6.47,7.51,21.82
cspresnet50,256,1024.0,3012.57,339.898,4.54,11.5,21.62
resnetv2_50t,224,1024.0,3011.73,339.991,4.32,11.82,25.57
dpn68b,224,1024.0,3008.58,340.347,2.35,10.47,12.61
coatnet_nano_rw_224,224,1024.0,3001.39,341.165,2.29,13.29,15.14
dpn68,224,1024.0,3001.33,341.17,2.35,10.47,12.61
resnetv2_50d,224,1024.0,2992.98,342.12,4.35,11.92,25.57
convnext_tiny,224,1024.0,2986.71,342.841,4.47,13.44,28.59
levit_512,224,1024.0,2974.0,344.305,5.64,10.22,95.17
dla60,224,1024.0,2959.44,345.999,4.26,10.16,22.04
fbnetv3_g,240,1024.0,2957.87,346.184,1.28,14.87,16.62
tf_efficientnet_b2,260,1024.0,2957.04,346.28,1.02,13.83,9.11
efficientnet_em,240,1024.0,2948.76,347.254,3.04,14.34,6.9
crossvit_15_240,240,1024.0,2948.65,347.266,5.17,12.01,27.53
eca_resnet33ts,256,1024.0,2945.18,347.676,4.76,11.66,19.68
seresnet33ts,256,1024.0,2940.4,348.24,4.76,11.66,19.78
regnetx_032,224,1024.0,2932.49,349.18,3.2,11.37,15.3
gcresnet33ts,256,1024.0,2919.42,350.744,4.76,11.68,19.88
mobileone_s0,224,1024.0,2911.68,351.675,1.09,15.48,5.29
resnet50t,224,1024.0,2893.61,353.872,4.32,11.82,25.57
resnet50c,224,1024.0,2893.38,353.9,4.35,11.92,25.58
repvit_m1_5,224,1024.0,2891.53,354.126,2.31,15.7,14.64
selecsls84,224,1024.0,2891.52,354.128,5.9,7.57,50.95
efficientnet_cc_b1_8e,240,1024.0,2883.89,355.064,0.75,15.44,39.72
haloregnetz_b,224,1024.0,2883.33,355.134,1.97,11.94,11.68
vgg11,224,1024.0,2881.16,355.4,7.61,7.44,132.86
resnet50d,224,1024.0,2872.03,356.53,4.35,11.92,25.58
resnest26d,224,1024.0,2863.53,357.59,3.64,9.97,17.07
tf_efficientnet_em,240,1024.0,2860.98,357.908,3.04,14.34,6.9
visformer_small,224,1024.0,2837.73,360.841,4.88,11.43,40.22
cspresnet50w,256,1024.0,2834.78,361.216,5.04,12.19,28.12
vovnet39a,224,1024.0,2834.5,361.252,7.09,6.73,22.6
wide_resnet50_2,176,1024.0,2833.12,361.428,7.29,8.97,68.88
cspresnet50d,256,1024.0,2828.94,361.963,4.86,12.55,21.64
resnet26,288,1024.0,2826.83,362.233,3.9,12.15,16.0
resnext26ts,288,1024.0,2826.2,362.312,3.07,13.31,10.3
efficientnet_b2,288,1024.0,2822.88,362.739,1.12,16.2,9.11
regnetv_040,224,1024.0,2785.35,367.627,4.0,12.29,20.64
levit_512d,224,1024.0,2784.75,367.707,5.85,11.3,92.5
levit_conv_512,224,1024.0,2781.3,368.162,5.64,10.22,95.17
deit3_medium_patch16_224,224,1024.0,2780.75,368.235,7.53,10.99,38.85
crossvit_15_dagger_240,240,1024.0,2776.34,368.82,5.5,12.68,28.21
regnety_040,224,1024.0,2768.62,369.849,4.0,12.29,20.65
legacy_seresnet50,224,1024.0,2766.98,370.066,3.88,10.6,28.09
eca_resnext26ts,288,1024.0,2756.51,371.473,3.07,13.32,10.3
seresnext26ts,288,1024.0,2751.54,372.144,3.07,13.32,10.39
regnety_032,224,1024.0,2744.75,373.065,3.2,11.26,19.44
convnext_tiny_hnf,224,1024.0,2744.61,373.082,4.47,13.44,28.59
convnextv2_femto,288,1024.0,2744.25,373.131,1.3,7.56,5.23
eca_vovnet39b,224,1024.0,2742.23,373.408,7.09,6.74,22.6
resnetv2_50x1_bit,224,1024.0,2741.57,373.497,4.23,11.11,25.55
gcresnext26ts,288,1024.0,2728.39,375.302,3.07,13.33,10.48
resnetaa50,224,1024.0,2728.16,375.334,5.15,11.64,25.56
densenet121,224,1024.0,2725.3,375.726,2.87,6.9,7.98
ese_vovnet39b,224,1024.0,2723.97,375.912,7.09,6.74,24.57
mixnet_l,224,1024.0,2712.93,377.44,0.58,10.84,7.33
tf_efficientnet_cc_b1_8e,240,1024.0,2710.75,377.745,0.75,15.44,39.72
mobilevit_s,256,768.0,2698.84,284.557,1.86,17.03,5.58
cs3darknet_focus_l,288,1024.0,2695.52,379.878,5.9,10.16,21.15
seresnet50,224,1024.0,2693.22,380.203,4.11,11.13,28.09
xcit_nano_12_p16_384,384,1024.0,2679.82,382.104,1.64,12.14,3.05
resnetaa34d,288,1024.0,2675.02,382.79,7.33,8.38,21.82
twins_svt_small,224,1024.0,2670.35,383.458,2.82,10.7,24.06
ecaresnet50d_pruned,288,1024.0,2662.19,384.634,4.19,10.61,19.94
convnext_nano,288,1024.0,2634.79,388.635,4.06,13.84,15.59
resnet50_gn,224,1024.0,2631.91,389.06,4.14,11.11,25.56
resnetv2_50d_gn,224,1024.0,2623.43,390.317,4.38,11.92,25.57
xcit_tiny_24_p16_224,224,1024.0,2616.39,391.368,2.34,11.82,12.12
tf_mixnet_l,224,1024.0,2615.89,391.443,0.58,10.84,7.33
res2net50_48w_2s,224,1024.0,2611.06,392.166,4.18,11.72,25.29
gcvit_xxtiny,224,1024.0,2608.34,392.574,2.14,15.36,12.0
cs3darknet_l,288,1024.0,2607.33,392.728,6.16,10.83,21.16
resnetaa50d,224,1024.0,2596.72,394.332,5.39,12.44,25.58
vgg11_bn,224,1024.0,2590.27,395.315,7.62,7.44,132.87
vit_base_resnet26d_224,224,1024.0,2580.41,396.822,6.93,12.34,101.4
vit_relpos_medium_patch16_cls_224,224,1024.0,2579.62,396.946,7.55,13.3,38.76
ecaresnet50t,224,1024.0,2579.62,396.946,4.32,11.83,25.57
coatnet_rmlp_nano_rw_224,224,1024.0,2579.38,396.984,2.51,18.21,15.15
davit_tiny,224,1024.0,2578.68,397.091,4.47,17.08,28.36
seresnet50t,224,1024.0,2574.91,397.672,4.32,11.83,28.1
resnet26d,288,1024.0,2569.96,398.438,4.29,13.48,16.01
mobilevitv2_125,256,768.0,2568.23,299.03,2.86,20.1,7.48
nf_regnet_b3,288,1024.0,2563.17,399.494,1.67,11.84,18.59
ecaresnet50d,224,1024.0,2560.76,399.87,4.35,11.93,25.58
levit_conv_512d,224,1024.0,2557.63,400.359,5.85,11.3,92.5
resnet152,160,1024.0,2531.48,404.495,5.9,11.51,60.19
efficientvit_b2,256,1024.0,2531.18,404.544,2.09,19.03,24.33
mobileone_s3,224,1024.0,2513.71,407.355,1.94,13.85,10.17
resnetrs50,224,1024.0,2512.05,407.624,4.48,12.14,35.69
twins_pcpvt_small,224,1024.0,2506.77,408.482,3.68,15.51,24.11
resnetblur50,224,1024.0,2495.43,410.338,5.16,12.02,25.56
poolformerv2_s12,224,1024.0,2489.38,411.337,1.83,5.53,11.89
convnextv2_nano,224,1024.0,2480.83,412.755,2.46,8.37,15.62
regnetx_040,224,1024.0,2478.03,413.222,3.99,12.2,22.12
eca_nfnet_l0,224,1024.0,2476.91,413.407,4.35,10.47,24.14
gcresnext50ts,256,1024.0,2473.39,413.995,3.75,15.46,15.67
nfnet_l0,224,1024.0,2472.84,414.088,4.36,10.47,35.07
tiny_vit_21m_224,224,1024.0,2468.7,414.781,4.08,15.96,33.22
cs3sedarknet_l,288,1024.0,2463.79,415.609,6.16,10.83,21.91
resnet50s,224,1024.0,2456.52,416.838,5.47,13.52,25.68
dla60x,224,1024.0,2437.95,420.012,3.54,13.8,17.35
densenetblur121d,224,1024.0,2433.6,420.765,3.11,7.9,8.0
edgenext_small,320,1024.0,2424.08,422.414,1.97,14.16,5.59
resnext50_32x4d,224,1024.0,2410.12,424.862,4.26,14.4,25.03
inception_next_tiny,224,1024.0,2404.04,425.937,4.19,11.98,28.06
convnext_nano_ols,288,1024.0,2397.01,427.188,4.38,15.5,15.65
vit_relpos_medium_patch16_224,224,1024.0,2394.54,427.629,7.5,12.13,38.75
efficientnet_lite3,300,512.0,2392.78,213.967,1.65,21.85,8.2
vit_srelpos_medium_patch16_224,224,1024.0,2386.54,429.062,7.49,11.32,38.74
regnetz_c16,256,1024.0,2383.36,429.635,2.51,16.57,13.46
resnetblur50d,224,1024.0,2382.64,429.765,5.4,12.82,25.58
vit_base_r26_s32_224,224,1024.0,2381.88,429.901,6.76,11.54,101.38
gcresnet50t,256,1024.0,2372.96,431.518,5.42,14.67,25.9
regnety_040_sgn,224,1024.0,2371.57,431.77,4.03,12.29,20.65
res2net50_26w_4s,224,1024.0,2359.62,433.957,4.28,12.61,25.7
vovnet57a,224,1024.0,2357.12,434.416,8.95,7.52,36.64
resmlp_24_224,224,1024.0,2350.19,435.697,5.96,10.91,30.02
maxvit_pico_rw_256,256,768.0,2346.84,327.238,1.68,18.77,7.46
inception_v3,299,1024.0,2346.46,436.391,5.73,8.97,23.83
maxvit_rmlp_pico_rw_256,256,768.0,2343.0,327.774,1.69,21.32,7.52
seresnetaa50d,224,1024.0,2333.21,438.87,5.4,12.46,28.11
focalnet_tiny_srf,224,1024.0,2331.81,439.132,4.42,16.32,28.43
cspresnext50,256,1024.0,2330.62,439.358,4.05,15.86,20.57
res2net50_14w_8s,224,1024.0,2327.89,439.871,4.21,13.28,25.06
dla60_res2net,224,1024.0,2327.26,439.99,4.15,12.34,20.85
coatnet_0_rw_224,224,1024.0,2319.62,441.438,4.23,15.1,27.44
regnetz_b16,288,1024.0,2318.51,441.651,2.39,16.43,9.72
gmixer_24_224,224,1024.0,2315.73,442.182,5.28,14.45,24.72
resnext50d_32x4d,224,1024.0,2305.65,444.116,4.5,15.2,25.05
lambda_resnet26rpt_256,256,768.0,2282.36,336.484,3.16,11.87,10.99
ese_vovnet57b,224,1024.0,2279.9,449.132,8.95,7.52,38.61
resnest50d_1s4x24d,224,1024.0,2278.75,449.357,4.43,13.57,25.68
dla60_res2next,224,1024.0,2268.77,451.333,3.49,13.17,17.03
sehalonet33ts,256,1024.0,2262.52,452.582,3.55,14.7,13.69
res2net50d,224,1024.0,2256.17,453.855,4.52,13.41,25.72
vit_medium_patch16_gap_240,240,1024.0,2253.27,454.439,8.6,12.57,44.4
res2next50,224,1024.0,2251.4,454.817,4.2,13.71,24.67
resnet32ts,288,1024.0,2244.87,456.139,5.86,14.65,17.96
edgenext_base,256,1024.0,2239.63,457.204,3.85,15.58,18.51
efficientvit_l1,224,1024.0,2235.54,458.043,5.27,15.85,52.65
skresnet50,224,1024.0,2226.66,459.87,4.11,12.5,25.8
nfnet_f0,192,1024.0,2226.44,459.916,7.21,10.16,71.49
tf_efficientnetv2_b3,300,1024.0,2226.35,459.935,3.04,15.74,14.36
efficientnetv2_rw_t,288,1024.0,2225.5,460.11,3.19,16.42,13.65
nf_ecaresnet50,224,1024.0,2219.3,461.395,4.21,11.13,25.56
darknetaa53,256,1024.0,2219.0,461.459,7.97,12.39,36.02
densenet169,224,1024.0,2218.3,461.604,3.4,7.3,14.15
nf_seresnet50,224,1024.0,2217.49,461.772,4.21,11.13,28.09
edgenext_small_rw,320,1024.0,2214.15,462.468,2.46,14.85,7.83
resnet33ts,288,1024.0,2214.09,462.482,6.02,14.75,19.68
xcit_small_12_p16_224,224,1024.0,2207.67,463.826,4.82,12.57,26.25
focalnet_tiny_lrf,224,1024.0,2205.41,464.301,4.49,17.76,28.65
resnet51q,256,1024.0,2195.84,466.325,6.38,16.55,35.7
repvgg_b1g4,224,1024.0,2195.75,466.344,8.15,10.64,39.97
seresnext50_32x4d,224,1024.0,2188.04,467.986,4.26,14.42,27.56
vit_relpos_medium_patch16_rpn_224,224,1024.0,2187.29,468.147,7.5,12.13,38.73
cs3darknet_focus_x,256,1024.0,2185.7,468.489,8.03,10.69,35.02
legacy_seresnext50_32x4d,224,1024.0,2184.4,468.766,4.26,14.42,27.56
tf_efficientnet_lite3,300,512.0,2178.27,235.039,1.65,21.85,8.2
resnet26t,320,1024.0,2173.03,471.22,5.24,16.44,16.01
gc_efficientnetv2_rw_t,288,1024.0,2170.84,471.696,3.2,16.45,13.68
gmlp_s16_224,224,1024.0,2161.42,473.752,4.42,15.1,19.42
seresnet33ts,288,1024.0,2156.33,474.868,6.02,14.76,19.78
eca_resnet33ts,288,1024.0,2152.27,475.765,6.02,14.76,19.68
fastvit_t12,256,1024.0,2151.9,475.846,1.42,12.42,7.55
nf_regnet_b3,320,1024.0,2148.66,476.564,2.05,14.61,18.59
eva02_small_patch14_224,224,1024.0,2144.78,477.426,5.53,12.34,21.62
resnet152,176,1024.0,2139.0,478.716,7.22,13.99,60.19
vit_medium_patch16_reg4_gap_256,256,1024.0,2137.51,479.051,9.93,14.51,38.87
gcresnet33ts,288,1024.0,2134.49,479.728,6.02,14.78,19.88
skresnet50d,224,1024.0,2133.34,479.986,4.36,13.31,25.82
ecaresnet101d_pruned,288,1024.0,2128.45,481.09,5.75,12.71,24.88
fbnetv3_g,288,1024.0,2127.74,481.25,1.77,21.09,16.62
vit_medium_patch16_reg4_256,256,1024.0,2119.83,483.047,9.97,14.56,38.87
eva02_tiny_patch14_336,336,1024.0,2106.54,486.094,3.14,13.85,5.76
convnextv2_pico,288,1024.0,2101.04,487.367,2.27,10.08,9.07
nf_resnet50,256,1024.0,2100.31,487.536,5.46,14.52,25.56
resnetrs101,192,1024.0,2100.21,487.558,6.04,12.7,63.62
poolformer_s24,224,1024.0,2099.97,487.615,3.41,10.68,21.39
pvt_v2_b2,224,1024.0,2099.92,487.626,3.9,24.96,25.36
efficientnet_b3,288,512.0,2089.91,244.977,1.63,21.49,12.23
cs3sedarknet_xdw,256,1024.0,2078.01,492.768,5.97,17.18,21.6
darknet53,256,1024.0,2077.03,493.0,9.31,12.39,41.61
ecaresnet50t,256,1024.0,2076.41,493.149,5.64,15.45,25.57
cs3darknet_x,256,1024.0,2060.02,497.071,8.38,11.35,35.05
xcit_nano_12_p8_224,224,1024.0,2059.06,497.302,2.16,15.71,3.05
mobilevitv2_150,256,512.0,2058.61,248.702,4.09,24.11,10.59
rexnetr_300,224,1024.0,2042.01,501.455,3.39,22.16,34.81
lambda_resnet50ts,256,1024.0,2041.61,501.552,5.07,17.48,21.54
fastvit_s12,256,1024.0,2028.81,504.718,1.82,13.67,9.47
coatnet_rmlp_0_rw_224,224,1024.0,2024.25,505.855,4.52,21.26,27.45
gcvit_xtiny,224,1024.0,2023.42,506.063,2.93,20.26,19.98
fastvit_sa12,256,1024.0,2022.28,506.347,1.96,13.83,11.58
crossvit_18_240,240,1024.0,2014.44,508.318,8.21,16.14,43.27
vit_medium_patch16_gap_256,256,1024.0,1996.45,512.899,9.78,14.29,38.86
resnet61q,256,1024.0,1996.22,512.958,7.8,17.01,36.85
coatnet_bn_0_rw_224,224,1024.0,1985.64,515.69,4.48,18.41,27.44
vit_base_patch32_384,384,1024.0,1984.44,516.005,12.67,12.14,88.3
vit_base_patch32_clip_384,384,1024.0,1981.44,516.784,12.67,12.14,88.3
cspdarknet53,256,1024.0,1981.04,516.888,6.57,16.81,27.64
sebotnet33ts_256,256,512.0,1977.98,258.841,3.89,17.46,13.7
ecaresnet26t,320,1024.0,1973.79,518.786,5.24,16.44,16.01
vit_base_resnet50d_224,224,1024.0,1971.35,519.428,8.68,16.1,110.97
cs3sedarknet_x,256,1024.0,1962.3,521.825,8.38,11.35,35.4
regnetx_080,224,1024.0,1962.04,521.894,8.02,14.06,39.57
seresnext26t_32x4d,288,1024.0,1950.77,524.91,4.46,16.68,16.81
mixnet_xl,224,1024.0,1948.29,525.576,0.93,14.57,11.9
resnest50d,224,1024.0,1945.36,526.368,5.4,14.36,27.48
seresnext26d_32x4d,288,1024.0,1940.04,527.813,4.51,16.85,16.81
coatnet_0_224,224,512.0,1939.29,264.004,4.43,21.14,25.04
swin_tiny_patch4_window7_224,224,1024.0,1938.74,528.165,4.51,17.06,28.29
resnetv2_101,224,1024.0,1935.15,529.146,7.83,16.23,44.54
regnetx_064,224,1024.0,1933.12,529.703,6.49,16.37,26.21
dla102,224,1024.0,1924.77,531.998,7.19,14.18,33.27
crossvit_18_dagger_240,240,1024.0,1921.19,532.991,8.65,16.91,44.27
rexnetr_200,288,512.0,1914.7,267.396,2.62,24.96,16.52
rexnet_300,224,1024.0,1911.46,535.706,3.44,22.4,34.71
nest_tiny,224,1024.0,1908.27,536.601,5.24,14.75,17.06
dm_nfnet_f0,192,1024.0,1907.3,536.873,7.21,10.16,71.49
ecaresnetlight,288,1024.0,1897.75,539.574,6.79,13.91,30.16
maxxvit_rmlp_nano_rw_256,256,768.0,1897.05,404.83,4.17,21.53,16.78
resnet101,224,1024.0,1885.15,543.183,7.83,16.23,44.55
nest_tiny_jx,224,1024.0,1884.26,543.437,5.24,14.75,17.06
pvt_v2_b2_li,224,1024.0,1882.78,543.863,3.77,25.04,22.55
vit_large_patch32_224,224,1024.0,1869.82,547.632,15.27,11.11,305.51
vgg13,224,1024.0,1868.34,548.068,11.31,12.25,133.05
resnetv2_101d,224,1024.0,1865.75,548.827,8.07,17.04,44.56
efficientformer_l3,224,1024.0,1865.63,548.865,3.93,12.01,31.41
resnetv2_50,288,1024.0,1863.99,549.347,6.79,18.37,25.55
mobileone_s4,224,1024.0,1856.33,551.615,3.04,17.74,14.95
res2net50_26w_6s,224,1024.0,1853.01,552.603,6.33,15.28,37.05
efficientvit_b2,288,1024.0,1851.14,553.16,2.64,24.03,24.33
lamhalobotnet50ts_256,256,1024.0,1841.89,555.938,5.02,18.44,22.57
maxvit_nano_rw_256,256,768.0,1833.65,418.827,4.26,25.76,15.45
maxvit_rmlp_nano_rw_256,256,768.0,1832.13,419.175,4.28,27.4,15.5
convnext_small,224,1024.0,1829.72,559.636,8.71,21.56,50.22
resnet101c,224,1024.0,1824.57,561.217,8.08,17.04,44.57
convnext_tiny,288,1024.0,1817.02,563.549,7.39,22.21,28.59
resnet101d,224,1024.0,1816.61,563.677,8.08,17.04,44.57
gcresnext50ts,288,1024.0,1802.21,568.181,4.75,19.57,15.67
efficientnetv2_s,288,1024.0,1800.9,568.595,4.75,20.13,21.46
pit_b_distilled_224,224,1024.0,1798.47,569.363,10.63,16.67,74.79
resnet50,288,1024.0,1790.94,571.757,6.8,18.37,25.56
twins_pcpvt_base,224,1024.0,1774.55,577.037,6.46,21.35,43.83
halonet50ts,256,1024.0,1772.89,577.576,5.3,19.2,22.73
dpn68b,288,1024.0,1770.85,578.24,3.89,17.3,12.61
pit_b_224,224,1024.0,1769.93,578.542,10.56,16.6,73.76
hrnet_w18_ssld,224,1024.0,1769.77,578.594,4.32,16.31,21.3
swin_s3_tiny_224,224,1024.0,1768.18,579.114,4.64,19.13,28.33
efficientvit_l2,224,1024.0,1765.89,579.866,6.97,19.58,63.71
hrnet_w18,224,1024.0,1763.75,580.57,4.32,16.31,21.3
coat_lite_small,224,1024.0,1746.27,586.38,3.96,22.09,19.84
repvgg_b1,224,1024.0,1745.5,586.64,13.16,10.64,57.42
wide_resnet50_2,224,1024.0,1744.59,586.947,11.43,14.4,68.88
efficientnet_b3,320,512.0,1740.17,294.213,2.01,26.52,12.23
gcresnet50t,288,1024.0,1734.6,590.328,6.86,18.57,25.9
densenet201,224,1024.0,1731.46,591.397,4.34,7.85,20.01
tresnet_v2_l,224,1024.0,1730.52,591.717,8.85,16.34,46.17
tf_efficientnet_b3,300,512.0,1724.68,296.856,1.87,23.83,12.23
efficientnetv2_rw_s,288,1024.0,1722.48,594.481,4.91,21.41,23.94
darknetaa53,288,1024.0,1719.51,595.509,10.08,15.68,36.02
maxxvitv2_nano_rw_256,256,768.0,1706.28,450.091,6.12,19.66,23.7
resnetaa101d,224,1024.0,1701.55,601.792,9.12,17.56,44.57
xcit_tiny_12_p16_384,384,1024.0,1700.55,602.144,3.64,18.25,6.72
cait_xxs24_224,224,1024.0,1698.66,602.815,2.53,20.29,11.96
resnet50t,288,1024.0,1694.77,604.2,7.14,19.53,25.57
legacy_seresnet101,224,1024.0,1693.62,604.611,7.61,15.74,49.33
cs3edgenet_x,256,1024.0,1692.79,604.907,11.53,12.92,47.82
resnet50d,288,1024.0,1684.01,608.061,7.19,19.7,25.58
mobilevitv2_175,256,512.0,1675.38,305.592,5.54,28.13,14.25
regnetv_064,224,1024.0,1674.09,611.663,6.39,16.41,30.58
resnetv2_101x1_bit,224,1024.0,1672.61,612.204,8.04,16.23,44.54
efficientnet_b3_gn,288,512.0,1669.75,306.623,1.74,23.35,11.73
ese_vovnet39b,288,768.0,1667.87,460.459,11.71,11.13,24.57
regnety_032,288,1024.0,1666.89,614.307,5.29,18.61,19.44
seresnet101,224,1024.0,1666.33,614.509,7.84,16.27,49.33
regnety_064,224,1024.0,1666.11,614.593,6.39,16.41,30.58
convnext_tiny_hnf,288,1024.0,1663.94,615.393,7.39,22.21,28.59
regnetv_040,288,1024.0,1658.56,617.391,6.6,20.3,20.64
regnety_040,288,1024.0,1648.75,621.064,6.61,20.3,20.65
regnety_080,224,1024.0,1645.74,622.202,8.0,17.97,39.18
resnet101s,224,1024.0,1640.53,624.176,9.19,18.64,44.67
mixer_b16_224,224,1024.0,1627.76,629.075,12.62,14.53,59.88
dla102x,224,1024.0,1623.56,630.698,5.89,19.42,26.31
nf_resnet101,224,1024.0,1622.48,631.12,8.01,16.23,44.55
swinv2_cr_tiny_224,224,1024.0,1621.28,631.59,4.66,28.45,28.33
ecaresnet101d,224,1024.0,1619.0,632.477,8.08,17.07,44.57
convnextv2_tiny,224,1024.0,1618.49,632.676,4.47,13.44,28.64
darknet53,288,1024.0,1615.64,633.795,11.78,15.68,41.61
wide_resnet101_2,176,1024.0,1615.25,633.945,14.31,13.18,126.89
repvit_m2_3,224,1024.0,1614.73,634.149,4.57,26.21,23.69
resnetaa50,288,1024.0,1610.23,635.923,8.52,19.24,25.56
resnetblur101d,224,1024.0,1609.76,636.109,9.12,17.94,44.57
efficientvit_b3,224,1024.0,1609.54,636.196,3.99,26.9,48.65
regnetz_d32,256,1024.0,1603.03,638.779,5.98,23.74,27.58
regnetz_b16_evos,224,1024.0,1602.47,639.001,1.43,9.95,9.74
ese_vovnet39b_evos,224,1024.0,1599.88,640.036,7.07,6.74,24.58
davit_small,224,1024.0,1599.81,640.066,8.69,27.54,49.75
seresnet50,288,1024.0,1595.89,641.637,6.8,18.39,28.09
cs3se_edgenet_x,256,1024.0,1593.53,642.587,11.53,12.94,50.72
nf_regnet_b4,320,1024.0,1592.57,642.975,3.29,19.88,30.21
swinv2_cr_tiny_ns_224,224,1024.0,1590.7,643.731,4.66,28.45,28.33
sequencer2d_s,224,1024.0,1586.65,645.372,4.96,11.31,27.65
tf_efficientnetv2_s,300,1024.0,1583.75,646.555,5.35,22.73,21.46
densenet121,288,1024.0,1581.16,647.615,4.74,11.41,7.98
resnet51q,288,1024.0,1581.05,647.659,8.07,20.94,35.7
regnetz_d8,256,1024.0,1580.57,647.855,3.97,23.74,23.37
resmlp_36_224,224,1024.0,1577.5,649.116,8.91,16.33,44.69
mixer_l32_224,224,1024.0,1577.26,649.215,11.27,19.86,206.94
regnetz_040,256,1024.0,1574.58,650.32,4.06,24.19,27.12
vit_base_patch16_224_miil,224,1024.0,1574.06,650.535,16.88,16.5,94.4
botnet50ts_256,256,512.0,1573.5,325.38,5.54,22.23,22.74
resnet50_gn,288,1024.0,1570.23,652.122,6.85,18.37,25.56
vit_base_patch16_clip_224,224,1024.0,1569.93,652.248,16.87,16.49,86.57
cs3darknet_x,288,1024.0,1569.68,652.352,10.6,14.36,35.05
deit_base_distilled_patch16_224,224,1024.0,1568.26,652.942,16.95,16.58,87.34
vit_base_patch16_224,224,1024.0,1568.03,653.038,16.87,16.49,86.57
deit_base_patch16_224,224,1024.0,1567.8,653.131,16.87,16.49,86.57
regnetz_040_h,256,1024.0,1564.2,654.638,4.12,24.29,28.94
resnetv2_50d_gn,288,1024.0,1555.81,658.164,7.24,19.7,25.57
resnetv2_50d_frn,224,1024.0,1553.07,659.326,4.33,11.92,25.59
tresnet_l,224,1024.0,1528.92,669.739,10.9,11.9,55.99
regnety_080_tv,224,1024.0,1528.54,669.91,8.51,19.73,39.38
resnetaa50d,288,1024.0,1524.48,671.692,8.92,20.57,25.58
nf_resnet50,288,1024.0,1524.41,671.724,6.88,18.37,25.56
caformer_s18,224,1024.0,1522.76,672.449,3.9,15.18,26.34
resnext101_32x8d,176,1024.0,1521.82,672.868,10.33,19.37,88.79
seresnet50t,288,1024.0,1518.59,674.299,7.14,19.55,28.1
ecaresnet50t,288,1024.0,1518.21,674.465,7.14,19.55,25.57
mvitv2_tiny,224,1024.0,1518.01,674.556,4.7,21.16,24.17
resnet101d,256,1024.0,1517.18,674.926,10.55,22.25,44.57
pvt_v2_b3,224,1024.0,1516.27,675.326,6.71,33.8,45.24
maxvit_tiny_rw_224,224,768.0,1513.7,507.357,4.93,28.54,29.06
ecaresnet50d,288,1024.0,1510.36,677.975,7.19,19.72,25.58
convnextv2_nano,288,768.0,1503.98,510.637,4.06,13.84,15.62
halo2botnet50ts_256,256,1024.0,1499.3,682.975,5.02,21.78,22.64
cs3sedarknet_x,288,1024.0,1498.9,683.158,10.6,14.37,35.4
res2net50_26w_8s,224,1024.0,1498.8,683.201,8.37,17.95,48.4
resnext101_32x4d,224,1024.0,1496.35,684.32,8.01,21.23,44.18
deit3_base_patch16_224,224,1024.0,1488.08,688.122,16.87,16.49,86.59
regnetz_c16,320,1024.0,1478.43,692.615,3.92,25.88,13.46
resnest50d_4s2x40d,224,1024.0,1478.06,692.785,4.4,17.94,30.42
resnetblur50,288,1024.0,1477.0,693.285,8.52,19.87,25.56
skresnext50_32x4d,224,1024.0,1470.18,696.502,4.5,17.18,27.48
efficientvit_l2,256,1024.0,1466.16,698.41,9.09,25.49,63.71
eca_nfnet_l0,288,1024.0,1463.28,699.787,7.12,17.29,24.14
mobilevitv2_200,256,768.0,1462.66,525.062,7.22,32.15,18.45
nfnet_l0,288,1024.0,1461.21,700.775,7.13,17.29,35.07
resnet61q,288,1024.0,1460.17,701.277,9.87,21.52,36.85
vit_base_patch32_clip_448,448,1024.0,1456.81,702.892,17.21,16.49,88.34
vit_small_patch16_36x1_224,224,1024.0,1454.45,704.036,12.63,24.59,64.67
vit_small_resnet50d_s16_224,224,1024.0,1451.55,705.439,13.0,21.12,57.53
beit_base_patch16_224,224,1024.0,1443.54,709.354,16.87,16.49,86.53
res2net101_26w_4s,224,1024.0,1442.54,709.848,8.1,18.45,45.21
vit_base_patch16_siglip_224,224,1024.0,1439.5,711.343,17.02,16.71,92.88
vit_base_patch16_gap_224,224,1024.0,1436.45,712.857,16.78,16.41,86.57
regnety_040_sgn,288,1024.0,1436.16,712.999,6.67,20.3,20.65
beitv2_base_patch16_224,224,1024.0,1436.01,713.075,16.87,16.49,86.53
convit_small,224,1024.0,1431.38,715.383,5.76,17.87,27.78
edgenext_base,320,1024.0,1423.6,719.289,6.01,24.32,18.51
convformer_s18,224,1024.0,1421.81,720.197,3.96,15.82,26.77
focalnet_small_srf,224,1024.0,1419.82,721.204,8.62,26.26,49.89
densenetblur121d,288,1024.0,1416.47,722.914,5.14,13.06,8.0
poolformer_s36,224,1024.0,1415.39,723.463,5.0,15.82,30.86
resnetv2_50d_evos,224,1024.0,1415.09,723.614,4.33,11.92,25.59
coatnet_rmlp_1_rw_224,224,1024.0,1413.05,724.664,7.44,28.08,41.69
res2net101d,224,1024.0,1406.68,727.943,8.35,19.25,45.23
legacy_xception,299,1024.0,1405.99,728.302,8.4,35.83,22.86
vit_small_patch16_18x2_224,224,1024.0,1405.24,728.689,12.63,24.59,64.67
resnetblur50d,288,1024.0,1403.3,729.695,8.92,21.19,25.58
resnext50_32x4d,288,1024.0,1402.5,730.115,7.04,23.81,25.03
inception_next_small,224,1024.0,1397.1,732.931,8.36,19.27,49.37
repvgg_b2g4,224,1024.0,1392.83,735.183,12.63,12.9,61.76
gcvit_tiny,224,1024.0,1390.57,736.376,4.79,29.82,28.22
vit_relpos_base_patch16_clsgap_224,224,1024.0,1386.7,738.433,16.88,17.72,86.43
vit_base_patch16_clip_quickgelu_224,224,1024.0,1384.47,739.621,16.87,16.49,86.19
vit_relpos_base_patch16_cls_224,224,1024.0,1384.18,739.775,16.88,17.72,86.43
dpn92,224,1024.0,1380.04,741.995,6.54,18.21,37.67
seresnetaa50d,288,1024.0,1379.8,742.125,8.92,20.59,28.11
vit_small_patch16_384,384,1024.0,1379.23,742.429,12.45,24.15,22.2
nf_ecaresnet101,224,1024.0,1375.27,744.569,8.01,16.27,44.55
nf_seresnet101,224,1024.0,1370.83,746.983,8.02,16.27,49.33
efficientnet_b3_gn,320,384.0,1366.12,281.077,2.14,28.83,11.73
vgg16_bn,224,1024.0,1361.56,752.067,15.5,13.56,138.37
flexivit_base,240,1024.0,1360.19,752.822,19.35,18.92,86.59
efficientformerv2_s0,224,1024.0,1357.83,754.133,0.41,5.3,3.6
resnetv2_152,224,1024.0,1356.74,754.735,11.55,22.56,60.19
seresnext101_32x4d,224,1024.0,1356.08,755.105,8.02,21.26,48.96
legacy_seresnext101_32x4d,224,1024.0,1355.29,755.543,8.02,21.26,48.96
efficientnet_b3_g8_gn,288,768.0,1342.01,572.264,2.59,23.35,14.25
efficientvit_b3,256,768.0,1340.35,572.972,5.2,35.01,48.65
efficientnet_b4,320,512.0,1338.46,382.52,3.13,34.76,19.34
nfnet_f0,256,1024.0,1336.25,766.311,12.62,18.05,71.49
resnext50d_32x4d,288,1024.0,1335.71,766.62,7.44,25.13,25.05
focalnet_small_lrf,224,1024.0,1333.55,767.863,8.74,28.61,50.34
resnet152,224,1024.0,1331.42,769.094,11.56,22.56,60.19
ese_vovnet99b,224,1024.0,1328.91,770.544,16.51,11.27,63.2
resnetv2_152d,224,1024.0,1322.45,774.307,11.8,23.36,60.2
regnetx_120,224,1024.0,1317.68,777.11,12.13,21.37,46.11
hrnet_w32,224,1024.0,1308.75,782.414,8.97,22.02,41.23
xception41p,299,512.0,1308.08,391.403,9.25,39.86,26.91
vit_relpos_base_patch16_224,224,1024.0,1306.59,783.71,16.8,17.63,86.43
xcit_tiny_12_p8_224,224,1024.0,1306.3,783.883,4.81,23.6,6.71
coatnet_1_rw_224,224,1024.0,1303.02,785.857,7.63,27.22,41.72
resnet152c,224,1024.0,1301.97,786.489,11.8,23.36,60.21
coatnet_rmlp_1_rw2_224,224,1024.0,1300.63,787.299,7.71,32.74,41.72
twins_pcpvt_large,224,1024.0,1297.56,789.162,9.53,30.21,60.99
maxvit_tiny_tf_224,224,768.0,1297.26,592.007,5.42,31.21,30.92
resnet152d,224,1024.0,1296.94,789.538,11.8,23.36,60.21
cs3edgenet_x,288,1024.0,1296.8,789.626,14.59,16.36,47.82
vit_base_patch16_xp_224,224,1024.0,1295.7,790.295,16.85,16.49,86.51
poolformerv2_s24,224,1024.0,1287.82,795.129,3.42,10.68,21.34
dla169,224,1024.0,1280.41,799.732,11.6,20.2,53.39
efficientnet_el_pruned,300,1024.0,1280.32,799.789,8.0,30.7,10.59
efficientnet_el,300,1024.0,1279.02,800.603,8.0,30.7,10.59
seresnext50_32x4d,288,1024.0,1276.82,801.978,7.04,23.82,27.56
hrnet_w30,224,1024.0,1276.63,802.098,8.15,21.21,37.71
deit3_small_patch16_384,384,1024.0,1274.41,803.494,12.45,24.15,22.21
ecaresnet50t,320,1024.0,1274.01,803.751,8.82,24.13,25.57
maxxvit_rmlp_tiny_rw_256,256,768.0,1269.37,605.011,6.36,32.69,29.64
volo_d1_224,224,1024.0,1269.05,806.894,6.94,24.43,26.63
vgg19,224,1024.0,1264.63,809.714,19.63,14.86,143.67
convnext_base,224,1024.0,1259.04,813.306,15.38,28.75,88.59
rexnetr_300,288,512.0,1257.05,407.293,5.59,36.61,34.81
vit_base_patch16_rpn_224,224,1024.0,1255.24,815.771,16.78,16.41,86.54
densenet161,224,1024.0,1254.96,815.95,7.79,11.06,28.68
efficientformerv2_s1,224,1024.0,1251.09,818.477,0.67,7.66,6.19
regnety_120,224,1024.0,1250.69,818.739,12.14,21.38,51.82
twins_svt_base,224,1024.0,1249.89,819.258,8.36,20.42,56.07
tf_efficientnet_el,300,1024.0,1249.79,819.323,8.0,30.7,10.59
sequencer2d_m,224,1024.0,1238.3,826.927,6.55,14.26,38.31
nest_small,224,1024.0,1229.99,832.512,9.41,22.88,38.35
maxvit_tiny_rw_256,256,768.0,1229.06,624.855,6.44,37.27,29.07
maxvit_rmlp_tiny_rw_256,256,768.0,1228.3,625.245,6.47,39.84,29.15
repvgg_b2,224,1024.0,1219.54,839.651,20.45,12.9,89.02
nest_small_jx,224,1024.0,1219.36,839.775,9.41,22.88,38.35
mixnet_xxl,224,768.0,1211.88,633.716,2.04,23.43,23.96
resnet152s,224,1024.0,1205.05,849.747,12.92,24.96,60.32
swin_small_patch4_window7_224,224,1024.0,1202.25,851.724,8.77,27.47,49.61
inception_v4,299,1024.0,1191.21,859.617,12.28,15.09,42.68
swinv2_tiny_window8_256,256,1024.0,1191.2,859.622,5.96,24.57,28.35
legacy_seresnet152,224,1024.0,1187.19,862.527,11.33,22.08,66.82
coatnet_1_224,224,512.0,1184.08,432.392,8.28,31.3,42.23
xcit_small_24_p16_224,224,1024.0,1178.16,869.138,9.1,23.63,47.67
vit_relpos_base_patch16_rpn_224,224,1024.0,1177.44,869.665,16.8,17.63,86.41
eca_nfnet_l1,256,1024.0,1175.13,871.38,9.62,22.04,41.41
seresnet152,224,1024.0,1173.43,872.64,11.57,22.61,66.82
maxvit_tiny_pm_256,256,768.0,1169.83,656.496,6.31,40.82,30.09
crossvit_base_240,240,1024.0,1165.77,878.374,20.13,22.67,105.03
efficientnet_lite4,380,384.0,1155.38,332.349,4.04,45.66,13.01
xception41,299,512.0,1153.48,443.864,9.28,39.86,26.97
regnetx_160,224,1024.0,1153.37,887.82,15.99,25.52,54.28
vgg19_bn,224,1024.0,1151.34,889.391,19.66,14.86,143.68
cait_xxs36_224,224,1024.0,1139.1,898.942,3.77,30.34,17.3
tresnet_xl,224,1024.0,1138.98,899.04,15.2,15.34,78.44
tnt_s_patch16_224,224,1024.0,1134.46,902.62,5.24,24.37,23.76
davit_base,224,1024.0,1133.31,903.534,15.36,36.72,87.95
dm_nfnet_f0,256,1024.0,1132.28,904.361,12.62,18.05,71.49
resnetv2_101,288,1024.0,1131.44,905.029,12.94,26.83,44.54
mvitv2_small_cls,224,1024.0,1129.19,906.833,7.04,28.17,34.87
mvitv2_small,224,1024.0,1128.19,907.64,7.0,28.08,34.87
coat_tiny,224,1024.0,1126.07,909.345,4.35,27.2,5.5
convmixer_1024_20_ks9_p14,224,1024.0,1123.31,911.577,5.55,5.51,24.38
vit_base_patch16_reg8_gap_256,256,1024.0,1115.77,917.744,22.6,22.09,86.62
fastvit_sa24,256,1024.0,1114.43,918.841,3.79,23.92,21.55
repvgg_b3g4,224,1024.0,1113.37,919.717,17.89,15.1,83.83
convnext_small,288,1024.0,1110.94,921.731,14.39,35.65,50.22
vit_base_patch16_siglip_256,256,1024.0,1108.01,924.168,22.23,21.83,92.93
resnet101,288,1024.0,1104.31,927.267,12.95,26.83,44.55
dla102x2,224,1024.0,1104.21,927.342,9.34,29.91,41.28
pvt_v2_b4,224,1024.0,1101.67,929.481,9.83,48.14,62.56
vit_large_r50_s32_224,224,1024.0,1091.33,938.289,19.45,22.22,328.99
eva02_base_patch16_clip_224,224,1024.0,1090.31,939.167,16.9,18.91,86.26
vgg13_bn,224,1024.0,1090.15,939.306,11.33,12.25,133.05
resnet152d,256,1024.0,1089.57,939.806,15.41,30.51,60.21
nf_regnet_b4,384,1024.0,1089.51,939.86,4.7,28.61,30.21
efficientnet_b3_g8_gn,320,768.0,1085.43,707.541,3.2,28.83,14.25
vit_small_r26_s32_384,384,1024.0,1083.82,944.797,10.24,27.67,36.47
efficientvit_l2,288,1024.0,1083.69,944.906,11.51,32.19,63.71
efficientnetv2_s,384,1024.0,1081.44,946.869,8.44,35.77,21.46
tf_efficientnet_lite4,380,384.0,1073.72,357.628,4.04,45.66,13.01
pvt_v2_b5,224,1024.0,1068.28,958.536,11.39,44.23,81.96
hrnet_w18_ssld,288,1024.0,1066.01,960.575,7.14,26.96,21.3
tf_efficientnetv2_s,384,1024.0,1054.1,971.431,8.44,35.77,21.46
regnety_160,224,1024.0,1046.76,978.242,15.96,23.04,83.59
samvit_base_patch16_224,224,1024.0,1027.37,996.713,16.83,17.2,86.46
convnext_tiny,384,768.0,1026.31,748.299,13.14,39.48,28.59
wide_resnet50_2,288,1024.0,1025.91,998.129,18.89,23.81,68.88
efficientnetv2_rw_s,384,1024.0,1024.66,999.343,8.72,38.03,23.94
vgg16,224,1024.0,1020.44,1003.475,15.47,13.56,138.36
cs3se_edgenet_x,320,1024.0,1009.45,1014.397,18.01,20.21,50.72
vit_base_patch16_plus_240,240,1024.0,1002.7,1021.234,26.31,22.07,117.56
swinv2_cr_small_224,224,1024.0,1001.72,1022.232,9.07,50.27,49.7
dpn98,224,1024.0,998.61,1025.406,11.73,25.2,61.57
efficientvit_b3,288,768.0,996.43,770.744,6.58,44.2,48.65
resnetaa101d,288,1024.0,996.18,1027.911,15.07,29.03,44.57
wide_resnet101_2,224,1024.0,994.0,1030.164,22.8,21.23,126.89
regnetz_d32,320,1024.0,994.0,1030.165,9.33,37.08,27.58
swinv2_cr_small_ns_224,224,1024.0,991.13,1033.149,9.08,50.27,49.7
focalnet_base_srf,224,1024.0,990.91,1033.385,15.28,35.01,88.15
convnextv2_small,224,1024.0,989.67,1034.674,8.71,21.56,50.32
resnet200,224,1024.0,987.28,1037.18,15.07,32.19,64.67
convnextv2_tiny,288,768.0,983.87,780.578,7.39,22.21,28.64
seresnet101,288,1024.0,983.64,1041.016,12.95,26.87,49.33
vit_small_patch8_224,224,1024.0,981.8,1042.968,16.76,32.86,21.67
regnetz_d8,320,1024.0,980.9,1043.922,6.19,37.08,23.37
regnety_080,288,1024.0,977.86,1047.177,13.22,29.69,39.18
inception_next_base,224,1024.0,977.1,1047.988,14.85,25.69,86.67
vit_base_r50_s16_224,224,1024.0,974.47,1050.816,20.94,27.88,97.89
resnest101e,256,1024.0,968.0,1057.838,13.38,28.66,48.28
convnext_base,256,1024.0,965.93,1060.101,20.09,37.55,88.59
regnetz_c16_evos,256,768.0,965.5,795.429,2.48,16.57,13.49
regnetz_040,320,512.0,964.02,531.096,6.35,37.78,27.12
poolformer_m36,224,1024.0,963.9,1062.337,8.8,22.02,56.17
regnetz_b16_evos,288,768.0,961.28,798.923,2.36,16.43,9.74
inception_resnet_v2,299,1024.0,958.82,1067.962,13.18,25.06,55.84
regnetz_040_h,320,512.0,958.46,534.182,6.43,37.94,28.94
seresnet152d,256,1024.0,956.44,1070.629,15.42,30.56,66.84
ecaresnet101d,288,1024.0,951.62,1076.05,13.35,28.19,44.57
regnety_064,288,1024.0,949.24,1078.741,10.56,27.11,30.58
resnetrs152,256,1024.0,948.32,1079.798,15.59,30.83,86.62
resnext101_64x4d,224,1024.0,947.79,1080.397,15.52,31.21,83.46
regnetv_064,288,1024.0,947.23,1081.038,10.55,27.11,30.58
xception65p,299,512.0,944.43,542.118,13.91,52.48,39.82
resnetblur101d,288,1024.0,942.52,1086.438,15.07,29.65,44.57
resnetrs101,288,1024.0,941.79,1087.277,13.56,28.53,63.62
focalnet_base_lrf,224,1024.0,941.31,1087.831,15.43,38.13,88.75
resnext101_32x8d,224,1024.0,939.44,1090.002,16.48,31.21,88.79
repvgg_b3,224,1024.0,933.91,1096.448,29.16,15.1,123.09
hrnet_w40,224,1024.0,931.96,1098.75,12.75,25.29,57.56
nfnet_f1,224,1024.0,924.88,1107.159,17.87,22.94,132.63
eva02_small_patch14_336,336,1024.0,923.99,1108.223,12.41,27.7,22.13
resnet101d,320,1024.0,923.18,1109.193,16.48,34.77,44.57
xcit_tiny_24_p16_384,384,1024.0,910.96,1124.082,6.87,34.29,12.12
efficientnet_b4,384,384.0,908.88,422.486,4.51,50.04,19.34
cait_s24_224,224,1024.0,904.24,1132.424,9.35,40.58,46.92
mobilevitv2_150,384,256.0,899.17,284.697,9.2,54.25,10.59
maxvit_rmlp_small_rw_224,224,768.0,898.81,854.449,10.48,42.44,64.9
coat_mini,224,1024.0,894.78,1144.406,6.82,33.68,10.34
coat_lite_medium,224,1024.0,892.4,1147.459,9.81,40.06,44.57
efficientnetv2_m,320,1024.0,889.26,1151.505,11.01,39.97,54.14
seresnext101_64x4d,224,1024.0,888.73,1152.196,15.53,31.25,88.23
gmlp_b16_224,224,1024.0,884.5,1157.706,15.78,30.21,73.08
seresnext101_32x8d,224,1024.0,883.56,1158.934,16.48,31.25,93.57
swin_s3_small_224,224,768.0,879.87,872.841,9.43,37.84,49.74
vit_relpos_base_patch16_plus_240,240,1024.0,875.04,1170.215,26.21,23.41,117.38
efficientformer_l7,224,1024.0,873.11,1172.808,10.17,24.45,82.23
nest_base,224,1024.0,870.02,1176.974,16.71,30.51,67.72
poolformerv2_s36,224,1024.0,869.16,1178.141,5.01,15.82,30.79
maxvit_small_tf_224,224,512.0,868.0,589.85,11.39,46.31,68.93
seresnext101d_32x8d,224,1024.0,866.35,1181.949,16.72,32.05,93.59
nest_base_jx,224,1024.0,862.67,1187.001,16.71,30.51,67.72
levit_384_s8,224,512.0,854.68,599.045,9.98,35.86,39.12
regnetz_e8,256,1024.0,853.36,1199.952,9.91,40.94,57.7
swin_base_patch4_window7_224,224,1024.0,852.78,1200.762,15.47,36.63,87.77
coatnet_2_rw_224,224,512.0,852.23,600.767,14.55,39.37,73.87
tf_efficientnet_b4,380,384.0,851.5,450.956,4.49,49.49,19.34
gcvit_small,224,1024.0,841.82,1216.401,8.57,41.61,51.09
convnextv2_nano,384,512.0,841.68,608.3,7.22,24.61,15.62
resnetv2_50d_evos,288,1024.0,840.21,1218.735,7.15,19.7,25.59
levit_conv_384_s8,224,512.0,839.77,609.68,9.98,35.86,39.12
xception65,299,512.0,839.39,609.953,13.96,52.48,39.92
hrnet_w44,224,1024.0,835.38,1225.779,14.94,26.92,67.06
crossvit_15_dagger_408,408,1024.0,833.7,1228.252,16.07,37.0,28.5
tiny_vit_21m_384,384,512.0,827.46,618.747,11.94,46.84,21.23
twins_svt_large,224,1024.0,824.23,1242.353,14.84,27.23,99.27
seresnextaa101d_32x8d,224,1024.0,820.77,1247.602,17.25,34.16,93.59
xcit_medium_24_p16_224,224,1024.0,820.51,1247.988,16.13,31.71,84.4
eva02_base_patch14_224,224,1024.0,819.51,1249.51,22.0,24.67,85.76
coatnet_rmlp_2_rw_224,224,512.0,814.13,628.885,14.64,44.94,73.88
hrnet_w48_ssld,224,1024.0,812.33,1260.551,17.34,28.56,77.47
hrnet_w48,224,1024.0,811.26,1262.228,17.34,28.56,77.47
caformer_s36,224,1024.0,810.13,1263.986,7.55,29.29,39.3
tresnet_m,448,1024.0,809.9,1264.343,22.99,29.21,31.39
resnet200d,256,1024.0,803.17,1274.938,20.0,43.09,64.69
sequencer2d_l,224,1024.0,802.78,1275.557,9.74,22.12,54.3
maxxvit_rmlp_small_rw_256,256,768.0,801.57,958.106,14.21,47.76,66.01
swinv2_base_window12_192,192,1024.0,799.54,1280.724,11.9,39.72,109.28
dm_nfnet_f1,224,1024.0,798.67,1282.118,17.87,22.94,132.63
coatnet_2_224,224,512.0,796.89,642.486,15.94,42.41,74.68
vit_medium_patch16_gap_384,384,1024.0,795.07,1287.922,22.01,32.15,39.03
mvitv2_base_cls,224,1024.0,791.15,1294.298,10.23,40.65,65.44
mvitv2_base,224,1024.0,785.87,1303.007,10.16,40.5,51.47
efficientnetv2_rw_m,320,1024.0,785.27,1303.997,12.72,47.14,53.24
resnet152,288,1024.0,781.77,1309.827,19.11,37.28,60.19
swinv2_tiny_window16_256,256,512.0,775.64,660.087,6.68,39.02,28.35
fastvit_sa36,256,1024.0,768.44,1332.545,5.62,34.02,31.53
xcit_small_12_p16_384,384,1024.0,764.7,1339.074,14.14,36.5,26.25
convnext_base,288,1024.0,763.36,1341.427,25.43,47.53,88.59
convformer_s36,224,1024.0,754.92,1356.424,7.67,30.5,40.01
regnety_120,288,768.0,738.36,1040.13,20.06,35.34,51.82
swinv2_small_window8_256,256,1024.0,737.99,1387.548,11.58,40.14,49.73
dpn131,224,1024.0,732.6,1397.744,16.09,32.97,79.25
swinv2_cr_small_ns_256,256,1024.0,731.79,1399.291,12.07,76.21,49.7
mobilevitv2_175,384,256.0,731.75,349.838,12.47,63.29,14.25
convit_base,224,1024.0,730.43,1401.91,17.52,31.77,86.54
resnetv2_50x1_bit,448,512.0,729.61,701.734,16.62,44.46,25.55
poolformer_m48,224,1024.0,727.01,1408.491,11.59,29.17,73.47
maxvit_rmlp_small_rw_256,256,768.0,724.69,1059.745,13.69,55.48,64.9
tnt_b_patch16_224,224,1024.0,721.67,1418.912,14.09,39.01,65.41
eca_nfnet_l1,320,1024.0,720.22,1421.77,14.92,34.42,41.41
swinv2_cr_base_224,224,1024.0,716.89,1428.383,15.86,59.66,87.88
swin_s3_base_224,224,1024.0,715.81,1430.534,13.69,48.26,71.13
volo_d2_224,224,1024.0,711.4,1439.408,14.34,41.34,58.68
swinv2_cr_base_ns_224,224,1024.0,711.07,1440.068,15.86,59.66,87.88
convnextv2_base,224,768.0,708.71,1083.64,15.38,28.75,88.72
densenet264d,224,1024.0,697.85,1467.348,13.57,14.0,72.74
ecaresnet200d,256,1024.0,697.3,1468.506,20.0,43.15,64.69
seresnet200d,256,1024.0,696.92,1469.301,20.01,43.15,71.86
nf_regnet_b5,384,1024.0,694.76,1473.879,7.95,42.9,49.74
seresnet152,288,1024.0,693.47,1476.616,19.11,37.34,66.82
resnetrs200,256,1024.0,693.26,1477.057,20.18,43.42,93.21
coat_small,224,1024.0,689.68,1484.732,12.61,44.25,21.69
convnext_large,224,1024.0,686.69,1491.207,34.4,43.13,197.77
xcit_tiny_24_p8_224,224,1024.0,684.2,1496.615,9.21,45.38,12.11
efficientvit_l3,224,1024.0,667.4,1534.307,27.62,39.16,246.04
dpn107,224,1024.0,666.43,1536.527,18.38,33.46,86.92
resnet152d,320,1024.0,664.6,1540.768,24.08,47.67,60.21
senet154,224,1024.0,664.59,1540.791,20.77,38.69,115.09
legacy_senet154,224,1024.0,663.62,1543.045,20.77,38.69,115.09
efficientformerv2_s2,224,1024.0,658.11,1555.962,1.27,11.77,12.71
maxxvitv2_rmlp_base_rw_224,224,768.0,650.48,1180.654,23.88,54.39,116.09
xcit_nano_12_p8_384,384,1024.0,649.92,1575.56,6.34,46.06,3.05
xception71,299,512.0,649.47,788.325,18.09,69.92,42.34
vit_large_patch32_384,384,1024.0,643.51,1591.268,44.28,32.22,306.63
mobilevitv2_200,384,256.0,640.82,399.48,16.24,72.34,18.45
davit_large,224,1024.0,630.01,1625.361,34.37,55.08,196.81
hrnet_w64,224,1024.0,629.26,1627.299,28.97,35.09,128.06
convnext_small,384,768.0,628.81,1221.341,25.58,63.37,50.22
regnetz_d8_evos,256,1024.0,626.83,1633.604,4.5,24.92,23.46
regnety_160,288,768.0,626.54,1225.759,26.37,38.07,83.59
convnext_base,320,768.0,617.04,1244.641,31.39,58.68,88.59
fastvit_ma36,256,1024.0,615.75,1662.995,7.85,40.39,44.07
tf_efficientnetv2_m,384,1024.0,614.24,1667.09,15.85,57.52,54.14
gcvit_base,224,1024.0,612.92,1670.669,14.87,55.48,90.32
regnety_320,224,1024.0,612.34,1672.272,32.34,30.26,145.05
efficientvit_l2,384,768.0,610.03,1258.949,20.45,57.01,63.71
poolformerv2_m36,224,1024.0,609.2,1680.886,8.81,22.02,56.08
regnetz_c16_evos,320,512.0,608.23,841.78,3.86,25.88,13.49
resnetv2_50x3_bit,224,768.0,585.49,1311.719,37.06,33.34,217.32
seresnet152d,320,1024.0,585.32,1749.453,24.09,47.72,66.84
xcit_small_12_p8_224,224,1024.0,584.75,1751.159,18.69,47.19,26.21
resnet200,288,1024.0,584.49,1751.952,24.91,53.21,64.67
resnetrs152,320,1024.0,580.71,1763.336,24.34,48.14,86.62
caformer_m36,224,1024.0,580.7,1763.373,12.75,40.61,56.2
resnext101_64x4d,288,1024.0,579.65,1766.578,25.66,51.59,83.46
levit_conv_512_s8,224,256.0,579.33,441.879,21.82,52.28,74.05
crossvit_18_dagger_408,408,1024.0,578.67,1769.56,25.31,49.38,44.61
levit_512_s8,224,256.0,564.15,453.77,21.82,52.28,74.05
convnextv2_tiny,384,384.0,553.95,693.189,13.14,39.48,28.64
convformer_m36,224,1024.0,546.86,1872.507,12.89,42.05,57.05
efficientnet_b5,416,256.0,546.68,468.268,8.27,80.68,30.39
seresnet269d,256,1024.0,545.35,1877.679,26.59,53.6,113.67
efficientvit_l3,256,768.0,542.99,1414.373,36.06,50.98,246.04
seresnext101_32x8d,288,1024.0,537.9,1903.669,27.24,51.63,93.57
efficientnetv2_m,416,1024.0,531.24,1927.549,18.6,67.5,54.14
resnetrs270,256,1024.0,529.33,1934.515,27.06,55.84,129.86
maxvit_rmlp_base_rw_224,224,768.0,529.1,1451.502,22.63,79.3,116.14
swinv2_base_window8_256,256,1024.0,528.71,1936.775,20.37,52.59,87.92
regnetz_e8,320,768.0,528.46,1453.264,15.46,63.94,57.7
seresnext101d_32x8d,288,1024.0,527.36,1941.726,27.64,52.95,93.59
convnext_large_mlp,256,768.0,525.72,1460.834,44.94,56.33,200.13
nfnet_f2,256,1024.0,524.14,1953.657,33.76,41.85,193.78
halonet_h1,256,256.0,522.84,489.621,3.0,51.17,8.1
regnetx_320,224,1024.0,522.6,1959.408,31.81,36.3,107.81
mixer_l16_224,224,1024.0,520.22,1968.376,44.6,41.69,208.2
resnext101_32x16d,224,1024.0,519.8,1969.975,36.27,51.18,194.03
eca_nfnet_l2,320,1024.0,509.51,2009.758,20.95,47.43,56.72
ecaresnet200d,288,1024.0,503.74,2032.793,25.31,54.59,64.69
seresnet200d,288,1024.0,503.36,2034.329,25.32,54.6,71.86
caformer_s18,384,512.0,501.38,1021.162,11.45,44.61,26.34
volo_d3_224,224,1024.0,497.87,2056.757,20.78,60.09,86.33
resnet200d,320,1024.0,493.82,2073.621,31.25,67.33,64.69
swin_large_patch4_window7_224,224,768.0,492.35,1559.852,34.53,54.94,196.53
vit_base_patch16_18x2_224,224,1024.0,492.32,2079.918,50.37,49.17,256.73
deit_base_patch16_384,384,1024.0,491.82,2082.046,49.4,48.3,86.86
vit_base_patch16_clip_384,384,1024.0,491.74,2082.405,49.41,48.3,86.86
vit_base_patch16_384,384,1024.0,491.42,2083.727,49.4,48.3,86.86
deit_base_distilled_patch16_384,384,1024.0,491.32,2084.164,49.49,48.39,87.63
hrnet_w48_ssld,288,1024.0,490.92,2085.876,28.66,47.21,77.47
eva_large_patch14_196,196,1024.0,490.45,2087.863,59.66,43.77,304.14
maxvit_base_tf_224,224,512.0,488.88,1047.285,23.52,81.67,119.47
efficientnet_b5,448,256.0,488.83,523.691,9.59,93.56,30.39
vit_large_patch16_224,224,1024.0,488.5,2096.219,59.7,43.77,304.33
swinv2_small_window16_256,256,512.0,486.59,1052.215,12.82,66.29,49.73
swinv2_large_window12_192,192,768.0,485.58,1581.6,26.17,56.53,228.77
convformer_s18,384,512.0,484.08,1057.663,11.63,46.49,26.77
seresnextaa101d_32x8d,288,1024.0,479.96,2133.497,28.51,56.44,93.59
coatnet_3_rw_224,224,256.0,478.44,535.067,32.63,59.07,181.81
coatnet_rmlp_3_rw_224,224,256.0,477.75,535.833,32.75,64.7,165.15
xcit_large_24_p16_224,224,1024.0,472.07,2169.166,35.86,47.26,189.1
vit_small_patch14_dinov2,518,1024.0,469.29,2181.987,29.46,57.34,22.06
deit3_base_patch16_384,384,1024.0,466.88,2193.286,49.4,48.3,86.88
deit3_large_patch16_224,224,1024.0,466.56,2194.777,59.7,43.77,304.37
efficientnetv2_rw_m,416,768.0,466.5,1646.281,21.49,79.62,53.24
nfnet_f1,320,1024.0,466.35,2195.774,35.97,46.77,132.63
nf_regnet_b5,456,768.0,464.5,1653.385,11.7,61.95,49.74
coatnet_3_224,224,256.0,464.1,551.594,35.72,63.61,166.97
vit_small_patch14_reg4_dinov2,518,1024.0,460.4,2224.119,29.55,57.51,22.06
poolformerv2_m48,224,1024.0,459.37,2229.113,11.59,29.17,73.35
beitv2_large_patch16_224,224,1024.0,452.16,2264.697,59.7,43.77,304.43
beit_large_patch16_224,224,1024.0,452.15,2264.716,59.7,43.77,304.43
resnetv2_101x1_bit,448,512.0,451.35,1134.365,31.65,64.93,44.54
dm_nfnet_f2,256,1024.0,451.22,2269.395,33.76,41.85,193.78
vit_base_patch16_siglip_384,384,1024.0,448.34,2283.991,50.0,49.11,93.18
resnetv2_152x2_bit,224,1024.0,441.5,2319.35,46.95,45.11,236.34
convnext_xlarge,224,768.0,435.62,1762.988,60.98,57.5,350.2
maxvit_tiny_tf_384,384,256.0,434.99,588.503,16.0,94.22,30.98
efficientformerv2_l,224,1024.0,431.02,2375.769,2.59,18.54,26.32
convnext_base,384,512.0,430.72,1188.698,45.21,84.49,88.59
convnextv2_base,288,512.0,429.59,1191.832,25.43,47.53,88.72
resnetrs200,320,1024.0,428.05,2392.217,31.51,67.81,93.21
flexivit_large,240,1024.0,424.67,2411.279,68.48,50.22,304.36
convnextv2_large,224,512.0,423.49,1208.977,34.4,43.13,197.96
xcit_tiny_12_p8_384,384,1024.0,423.2,2419.661,14.12,69.12,6.71
swinv2_cr_large_224,224,768.0,422.05,1819.675,35.1,78.42,196.68
caformer_b36,224,768.0,419.19,1832.111,22.5,54.14,98.75
swinv2_cr_tiny_384,384,256.0,419.04,610.909,15.34,161.01,28.33
tf_efficientnet_b5,456,256.0,418.1,612.278,10.46,98.86,30.39
convnext_large,288,512.0,415.42,1232.482,56.87,71.29,197.77
davit_huge,224,512.0,410.45,1247.402,60.93,73.44,348.92
maxxvitv2_rmlp_large_rw_224,224,768.0,409.41,1875.861,43.69,75.4,215.42
tiny_vit_21m_512,512,384.0,408.26,940.575,21.23,83.26,21.27
xcit_small_24_p16_384,384,1024.0,408.08,2509.308,26.72,68.57,47.67
tf_efficientnetv2_m,480,768.0,405.02,1896.185,24.76,89.84,54.14
tresnet_l,448,1024.0,403.56,2537.407,43.59,47.56,55.99
beit_base_patch16_384,384,1024.0,401.76,2548.786,49.4,48.3,86.74
convformer_b36,224,768.0,396.81,1935.431,22.69,56.06,99.88
regnetz_d8_evos,320,768.0,395.82,1940.285,7.03,38.92,23.46
seresnextaa101d_32x8d,320,1024.0,395.0,2592.386,35.19,69.67,93.59
seresnet269d,288,1024.0,393.84,2600.059,33.65,67.81,113.67
dm_nfnet_f1,320,1024.0,393.6,2601.642,35.97,46.77,132.63
regnety_160,384,384.0,378.47,1014.589,46.87,67.67,83.59
vit_large_r50_s32_384,384,1024.0,372.96,2745.589,56.4,64.88,329.09
regnety_640,224,768.0,362.45,2118.906,64.16,42.5,281.38
eca_nfnet_l2,384,768.0,361.66,2123.504,30.05,68.28,56.72
vit_large_patch14_224,224,1024.0,359.79,2846.069,77.83,57.11,304.2
vit_large_patch14_clip_224,224,1024.0,359.08,2851.744,77.83,57.11,304.2
swinv2_base_window12to16_192to256,256,384.0,358.35,1071.569,22.02,84.71,87.92
swinv2_base_window16_256,256,384.0,358.25,1071.869,22.02,84.71,87.92
vit_large_patch16_siglip_256,256,1024.0,351.53,2912.942,78.12,57.42,315.96
vit_base_patch8_224,224,1024.0,350.95,2917.813,66.87,65.71,86.58
efficientvit_l3,320,512.0,346.1,1479.341,56.32,79.34,246.04
efficientnetv2_l,384,1024.0,342.83,2986.92,36.1,101.16,118.52
tf_efficientnetv2_l,384,1024.0,338.97,3020.897,36.1,101.16,118.52
ecaresnet269d,320,1024.0,337.13,3037.39,41.53,83.69,102.09
resnest200e,320,1024.0,336.33,3044.627,35.69,82.78,70.2
maxvit_large_tf_224,224,384.0,336.26,1141.954,42.99,109.57,211.79
convnext_large_mlp,320,512.0,336.03,1523.669,70.21,88.02,200.13
inception_next_base,384,512.0,335.9,1524.27,43.64,75.48,86.67
resnetv2_101x3_bit,224,768.0,334.56,2295.509,71.23,48.7,387.93
eca_nfnet_l3,352,768.0,328.62,2337.043,32.57,73.12,72.04
vit_large_patch14_clip_quickgelu_224,224,1024.0,324.15,3159.023,77.83,57.11,303.97
repvgg_d2se,320,1024.0,320.2,3197.943,74.57,46.82,133.33
vit_base_r50_s16_384,384,1024.0,317.01,3230.175,61.29,81.77,98.95
volo_d4_224,224,1024.0,317.0,3230.22,44.34,80.22,192.96
volo_d1_384,384,512.0,314.1,1630.023,22.75,108.55,26.78
vit_large_patch14_xp_224,224,1024.0,309.84,3304.92,77.77,57.11,304.06
convmixer_768_32,224,1024.0,308.6,3318.227,19.55,25.95,21.11
xcit_small_24_p8_224,224,1024.0,305.72,3349.464,35.81,90.77,47.63
resnetrs350,288,1024.0,304.48,3363.098,43.67,87.09,163.96
nasnetalarge,331,384.0,300.79,1276.642,23.89,90.56,88.75
coat_lite_medium_384,384,512.0,299.62,1708.831,28.73,116.7,44.57
tresnet_xl,448,768.0,296.15,2593.304,60.77,61.31,78.44
maxvit_small_tf_384,384,192.0,288.16,666.295,33.58,139.86,69.02
pnasnet5large,331,384.0,287.26,1336.778,25.04,92.89,86.06
xcit_medium_24_p16_384,384,1024.0,282.76,3621.451,47.39,91.63,84.4
ecaresnet269d,352,1024.0,281.17,3641.867,50.25,101.25,102.09
coatnet_4_224,224,256.0,280.04,914.128,60.81,98.85,275.43
cait_xxs24_384,384,1024.0,277.04,3696.16,9.63,122.65,12.03
coatnet_rmlp_2_rw_384,384,192.0,273.87,701.059,43.04,132.57,73.88
resnetrs270,352,1024.0,271.91,3765.914,51.13,105.48,129.86
nfnet_f2,352,768.0,270.88,2835.244,63.22,79.06,193.78
caformer_s36,384,512.0,266.29,1922.686,22.2,86.08,39.3
convnext_xlarge,288,512.0,263.75,1941.25,100.8,95.05,350.2
swinv2_cr_small_384,384,256.0,258.42,990.618,29.7,298.03,49.7
efficientnet_b6,528,128.0,257.57,496.944,19.4,167.39,43.04
convformer_s36,384,512.0,257.36,1989.401,22.54,89.62,40.01
convnextv2_large,288,256.0,256.91,996.448,56.87,71.29,197.96
eva02_large_patch14_224,224,1024.0,256.79,3987.739,77.9,65.52,303.27
eva02_large_patch14_clip_224,224,1024.0,253.51,4039.312,77.93,65.52,304.11
resnext101_32x32d,224,512.0,253.0,2023.672,87.29,91.12,468.53
maxvit_tiny_tf_512,512,192.0,249.39,769.864,28.66,172.66,31.05
tf_efficientnet_b6,528,128.0,247.44,517.29,19.4,167.39,43.04
nfnet_f3,320,1024.0,247.37,4139.575,68.77,83.93,254.92
mvitv2_large_cls,224,768.0,246.55,3114.926,42.17,111.69,234.58
vit_so400m_patch14_siglip_224,224,1024.0,246.49,4154.292,106.18,70.45,427.68
efficientnetv2_xl,384,1024.0,244.46,4188.739,52.81,139.2,208.12
mvitv2_large,224,512.0,242.6,2110.485,43.87,112.02,217.99
convnextv2_base,384,256.0,242.26,1056.699,45.21,84.49,88.72
vit_base_patch16_siglip_512,512,512.0,241.2,2122.705,88.89,87.3,93.52
convnext_large,384,384.0,234.69,1636.209,101.1,126.74,197.77
convnext_large_mlp,384,384.0,234.65,1636.476,101.11,126.74,200.13
dm_nfnet_f2,352,768.0,234.38,3276.685,63.22,79.06,193.78
tf_efficientnetv2_xl,384,1024.0,230.18,4448.679,52.81,139.2,208.12
efficientnetv2_l,480,512.0,229.94,2226.68,56.4,157.99,118.52
tf_efficientnetv2_l,480,512.0,227.38,2251.742,56.4,157.99,118.52
swin_base_patch4_window12_384,384,256.0,226.65,1129.483,47.19,134.78,87.9
regnety_320,384,384.0,225.95,1699.504,95.0,88.87,145.05
resnetrs420,320,1024.0,221.8,4616.729,64.2,126.56,191.89
xcit_tiny_24_p8_384,384,1024.0,221.03,4632.753,27.05,132.94,12.11
efficientvit_l3,384,384.0,220.15,1744.25,81.08,114.02,246.04
swinv2_large_window12to16_192to256,256,256.0,218.91,1169.41,47.81,121.53,196.74
maxxvitv2_rmlp_base_rw_384,384,384.0,215.87,1778.825,70.18,160.22,116.09
resmlp_big_24_224,224,1024.0,214.65,4770.604,100.23,87.31,129.14
dm_nfnet_f3,320,1024.0,212.33,4822.62,68.77,83.93,254.92
volo_d5_224,224,1024.0,212.3,4823.349,72.4,118.11,295.46
xcit_medium_24_p8_224,224,1024.0,210.35,4868.038,63.52,121.22,84.32
seresnextaa201d_32x8d,320,1024.0,207.05,4945.752,70.22,138.71,149.39
eca_nfnet_l3,448,512.0,204.74,2500.737,52.55,118.4,72.04
xcit_small_12_p8_384,384,512.0,195.78,2615.134,54.92,138.25,26.21
cait_xs24_384,384,768.0,193.45,3970.037,19.28,183.98,26.67
caformer_m36,384,256.0,191.51,1336.728,37.45,119.33,56.2
focalnet_huge_fl3,224,384.0,190.45,2016.221,118.26,104.8,745.28
eva02_base_patch14_448,448,512.0,189.13,2707.053,87.74,98.4,87.12
maxvit_xlarge_tf_224,224,256.0,188.97,1354.682,96.49,164.37,506.99
convformer_m36,384,384.0,186.96,2053.847,37.87,123.56,57.05
cait_xxs36_384,384,1024.0,185.14,5531.038,14.35,183.7,17.37
swinv2_cr_base_384,384,256.0,184.66,1386.338,50.57,333.68,87.88
resnetrs350,384,1024.0,184.39,5553.562,77.59,154.74,163.96
regnety_1280,224,512.0,182.89,2799.45,127.66,71.58,644.81
swinv2_cr_huge_224,224,384.0,181.27,2118.357,115.97,121.08,657.83
vit_huge_patch14_clip_224,224,1024.0,179.25,5712.71,161.99,95.07,632.05
vit_huge_patch14_224,224,1024.0,179.24,5713.082,161.99,95.07,630.76
volo_d2_384,384,384.0,177.67,2161.247,46.17,184.51,58.87
maxvit_rmlp_base_rw_384,384,384.0,177.21,2166.875,66.51,233.79,116.14
vit_base_patch14_dinov2,518,512.0,175.93,2910.275,117.11,114.68,86.58
vit_huge_patch14_gap_224,224,1024.0,175.35,5839.715,161.36,94.7,630.76
vit_base_patch14_reg4_dinov2,518,512.0,175.34,2920.066,117.45,115.02,86.58
convnextv2_huge,224,256.0,174.19,1469.676,115.0,79.07,660.29
deit3_huge_patch14_224,224,1024.0,172.49,5936.531,161.99,95.07,632.13
convmixer_1536_20,224,1024.0,172.27,5944.074,48.68,33.03,51.63
vit_huge_patch14_clip_quickgelu_224,224,1024.0,165.12,6201.386,161.99,95.07,632.08
maxvit_small_tf_512,512,96.0,163.95,585.546,60.02,256.36,69.13
maxvit_base_tf_384,384,192.0,162.75,1179.72,69.34,247.75,119.65
xcit_large_24_p16_384,384,1024.0,162.01,6320.659,105.34,137.15,189.1
resnetv2_152x2_bit,384,384.0,160.06,2399.153,136.16,132.56,236.34
vit_huge_patch14_xp_224,224,1024.0,159.21,6431.544,161.88,95.07,631.8
resnest269e,416,512.0,159.04,3219.278,77.69,171.98,110.93
eva_large_patch14_336,336,768.0,155.41,4941.906,174.74,128.21,304.53
vit_large_patch14_clip_336,336,768.0,155.09,4951.819,174.74,128.21,304.53
vit_large_patch16_384,384,768.0,154.94,4956.737,174.85,128.21,304.72
convnext_xxlarge,256,384.0,152.35,2520.42,198.09,124.45,846.47
davit_giant,224,384.0,151.56,2533.626,192.34,138.2,1406.47
resnetv2_50x3_bit,448,192.0,150.44,1276.251,145.7,133.37,217.32
coatnet_5_224,224,192.0,149.61,1283.336,142.72,143.69,687.47
efficientnetv2_xl,512,512.0,149.15,3432.877,93.85,247.32,208.12
cait_s24_384,384,512.0,148.91,3438.219,32.17,245.3,47.06
convnext_xlarge,384,256.0,148.61,1722.573,179.2,168.99,350.2
tf_efficientnetv2_xl,512,512.0,148.0,3459.525,93.85,247.32,208.12
efficientnet_b7,600,96.0,147.91,649.053,38.33,289.94,66.35
deit3_large_patch16_384,384,1024.0,147.79,6928.856,174.85,128.21,304.76
seresnextaa201d_32x8d,384,768.0,147.05,5222.537,101.11,199.72,149.39
nfnet_f3,416,512.0,146.71,3489.974,115.58,141.78,254.92
vit_giant_patch16_gap_224,224,1024.0,145.38,7043.632,198.14,103.64,1011.37
convnextv2_large,384,192.0,144.92,1324.86,101.1,126.74,197.96
resnetv2_152x4_bit,224,512.0,144.91,3533.266,186.9,90.22,936.53
vit_large_patch16_siglip_384,384,768.0,144.23,5324.878,175.76,129.18,316.28
tf_efficientnet_b7,600,96.0,143.48,669.058,38.33,289.94,66.35
nfnet_f4,384,768.0,142.67,5383.101,122.14,147.57,316.07
vit_large_patch14_clip_quickgelu_336,336,768.0,140.95,5448.604,174.74,128.21,304.29
caformer_b36,384,256.0,138.42,1849.458,66.12,159.11,98.75
swin_large_patch4_window12_384,384,128.0,135.49,944.717,104.08,202.16,196.74
convformer_b36,384,256.0,135.29,1892.221,66.67,164.75,99.88
resnetrs420,416,1024.0,130.11,7870.213,108.45,213.79,191.89
beit_large_patch16_384,384,768.0,129.31,5939.365,174.84,128.21,305.0
dm_nfnet_f3,416,512.0,127.57,4013.328,115.58,141.78,254.92
regnety_640,384,256.0,126.8,2018.836,188.47,124.83,281.38
dm_nfnet_f4,384,768.0,123.05,6241.189,122.14,147.57,316.07
focalnet_huge_fl4,224,512.0,122.81,4169.023,118.9,113.34,686.46
xcit_large_24_p8_224,224,512.0,120.1,4263.036,141.22,181.53,188.93
resnetv2_152x2_bit,448,256.0,117.91,2171.109,184.99,180.43,236.34
eva_giant_patch14_224,224,1024.0,116.71,8773.739,259.74,135.89,1012.56
eva_giant_patch14_clip_224,224,1024.0,116.64,8779.464,259.74,135.89,1012.59
vit_giant_patch14_224,224,1024.0,114.18,8968.21,259.74,135.89,1012.61
vit_giant_patch14_clip_224,224,1024.0,114.09,8975.383,259.74,135.89,1012.65
swinv2_cr_large_384,384,128.0,112.81,1134.666,108.96,404.96,196.68
maxvit_large_tf_384,384,128.0,111.17,1151.411,126.61,332.3,212.03
eva02_large_patch14_clip_336,336,1024.0,110.28,9285.405,174.97,147.1,304.43
mvitv2_huge_cls,224,384.0,107.61,3568.518,120.67,243.63,694.8
convnextv2_huge,288,128.0,105.35,1214.957,190.1,130.7,660.29
xcit_small_24_p8_384,384,512.0,102.73,4983.926,105.23,265.87,47.63
nfnet_f5,416,512.0,100.11,5114.164,170.71,204.56,377.21
cait_s36_384,384,512.0,99.61,5140.29,47.99,367.39,68.37
swinv2_base_window12to24_192to384,384,96.0,96.35,996.364,55.25,280.36,87.92
efficientnet_b8,672,96.0,95.78,1002.248,63.48,442.89,87.41
focalnet_large_fl3,384,384.0,94.47,4064.948,105.06,168.04,239.13
tf_efficientnet_b8,672,96.0,93.18,1030.252,63.48,442.89,87.41
maxvit_base_tf_512,512,96.0,92.2,1041.169,123.93,456.26,119.88
focalnet_large_fl4,384,256.0,90.17,2839.222,105.2,181.78,239.32
resnetv2_101x3_bit,448,192.0,87.88,2184.819,280.33,194.78,387.93
dm_nfnet_f5,416,512.0,86.64,5909.833,170.71,204.56,377.21
nfnet_f4,512,384.0,81.51,4711.211,216.26,262.26,316.07
volo_d3_448,448,192.0,76.74,2501.831,96.33,446.83,86.63
vit_so400m_patch14_siglip_384,384,512.0,75.92,6743.556,302.34,200.62,428.23
nfnet_f6,448,512.0,75.59,6773.482,229.7,273.62,438.36
vit_huge_patch14_clip_336,336,768.0,75.49,10173.683,363.7,213.44,632.46
xcit_medium_24_p8_384,384,384.0,71.15,5396.903,186.67,354.69,84.32
dm_nfnet_f4,512,384.0,69.56,5520.408,216.26,262.26,316.07
vit_gigantic_patch14_224,224,512.0,66.18,7736.423,473.4,204.12,1844.44
vit_gigantic_patch14_clip_224,224,512.0,66.18,7735.92,473.41,204.12,1844.91
focalnet_xlarge_fl3,384,256.0,66.07,3874.786,185.61,223.99,408.79
dm_nfnet_f6,448,512.0,65.28,7842.994,229.7,273.62,438.36
maxvit_large_tf_512,512,64.0,63.68,1005.087,225.96,611.85,212.33
focalnet_xlarge_fl4,384,192.0,63.39,3028.979,185.79,242.31,409.03
maxvit_xlarge_tf_384,384,96.0,63.2,1518.995,283.86,498.45,475.32
regnety_1280,384,128.0,62.14,2059.919,374.99,210.2,644.81
beit_large_patch16_512,512,256.0,61.47,4164.41,310.6,227.76,305.67
convnextv2_huge,384,96.0,60.73,1580.79,337.96,232.35,660.29
swinv2_large_window12to24_192to384,384,48.0,60.6,792.119,116.15,407.83,196.74
eva02_large_patch14_448,448,512.0,59.6,8591.147,310.69,261.32,305.08
tf_efficientnet_l2,475,128.0,59.14,2164.439,172.11,609.89,480.31
nfnet_f5,544,384.0,58.55,6558.595,290.97,349.71,377.21
vit_huge_patch14_clip_378,378,512.0,58.17,8801.788,460.13,270.04,632.68
volo_d4_448,448,192.0,57.2,3356.883,197.13,527.35,193.41
nfnet_f7,480,384.0,57.05,6730.663,300.08,355.86,499.5
vit_large_patch14_dinov2,518,384.0,56.81,6759.458,414.89,304.42,304.37
vit_large_patch14_reg4_dinov2,518,384.0,56.51,6795.142,416.1,305.31,304.37
vit_huge_patch14_clip_quickgelu_378,378,384.0,53.9,7123.722,460.13,270.04,632.68
swinv2_cr_giant_224,224,192.0,52.42,3662.593,483.85,309.15,2598.76
dm_nfnet_f5,544,384.0,50.82,7555.977,290.97,349.71,377.21
eva_giant_patch14_336,336,512.0,49.6,10322.486,583.14,305.1,1013.01
swinv2_cr_huge_384,384,64.0,48.85,1310.056,352.04,583.18,657.94
nfnet_f6,576,256.0,45.99,5566.397,378.69,452.2,438.36
xcit_large_24_p8_384,384,256.0,40.54,6315.135,415.0,531.74,188.93
volo_d5_448,448,192.0,39.97,4803.918,315.06,737.92,295.91
dm_nfnet_f6,576,256.0,39.68,6452.4,378.69,452.2,438.36
nfnet_f7,608,256.0,35.92,7127.91,480.39,570.85,499.5
maxvit_xlarge_tf_512,512,48.0,35.73,1343.449,505.95,917.77,475.77
regnety_2560,384,96.0,35.19,2728.299,747.83,296.49,1282.6
convnextv2_huge,512,48.0,34.07,1408.989,600.81,413.07,660.29
cait_m36_384,384,256.0,32.53,7868.895,173.11,734.79,271.22
resnetv2_152x4_bit,480,128.0,32.31,3961.512,844.84,414.26,936.53
volo_d5_512,512,96.0,27.94,3435.72,425.09,1105.37,296.09
samvit_base_patch16,1024,12.0,23.01,521.487,371.55,403.08,89.67
efficientnet_l2,800,32.0,22.53,1420.616,479.12,1707.39,480.31
tf_efficientnet_l2,800,32.0,22.12,1446.454,479.12,1707.39,480.31
vit_giant_patch14_dinov2,518,192.0,17.14,11200.639,1553.56,871.89,1136.48
vit_giant_patch14_reg4_dinov2,518,128.0,17.05,7505.847,1558.09,874.43,1136.48
swinv2_cr_giant_384,384,32.0,15.01,2131.256,1450.71,1394.86,2598.76
eva_giant_patch14_560,560,192.0,15.01,12792.976,1618.04,846.56,1014.45
cait_m48_448,448,128.0,13.76,9299.464,329.4,1708.21,356.46
samvit_large_patch16,1024,8.0,10.25,780.237,1317.08,1055.58,308.28
samvit_huge_patch16,1024,6.0,6.31,950.475,2741.59,1727.57,637.03
eva02_enormous_patch14_clip_224,224,,,,1132.46,497.58,4350.56
vit_huge_patch16_gap_448,448,,,,544.7,636.83,631.67