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pytorch-image-models/results/benchmark-train-amp-nchw-pt...

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model,train_samples_per_sec,train_step_time,train_batch_size,train_img_size,param_count
tinynet_e,8879.06,56.99,512,106,2.04
mobilenetv3_small_050,6486.16,78.215,512,224,1.59
tf_mobilenetv3_small_minimal_100,6286.95,80.898,512,224,2.04
lcnet_035,5388.39,94.526,512,224,1.64
levit_128s,5340.79,94.942,512,224,7.78
mobilenetv3_small_075,5188.12,97.983,512,224,2.04
lcnet_050,4931.51,103.34,512,224,1.88
tf_mobilenetv3_small_075,4918.54,103.391,512,224,2.04
mobilenetv3_small_100,4776.47,106.481,512,224,2.54
tf_mobilenetv3_small_100,4548.9,111.828,512,224,2.54
tinynet_d,4535.94,112.125,512,152,2.34
mixer_s32_224,4002.68,127.361,512,224,19.1
levit_128,3906.35,129.937,512,224,9.21
vit_small_patch32_224,3720.28,136.814,512,224,22.88
lcnet_075,3708.14,137.591,512,224,2.36
vit_tiny_r_s16_p8_224,3450.55,147.535,512,224,6.34
regnetx_002,3409.48,149.489,512,224,2.68
levit_192,3369.4,150.83,512,224,10.95
mnasnet_small,3194.94,159.346,512,224,2.03
regnety_002,3152.93,161.41,512,224,3.16
lcnet_100,3112.12,164.023,512,224,2.95
mobilenetv2_035,3034.35,167.951,512,224,1.68
gernet_s,2945.06,173.156,512,224,8.17
gluon_resnet18_v1b,2722.13,187.746,512,224,11.69
resnet18,2720.28,187.878,512,224,11.69
swsl_resnet18,2718.44,187.99,512,224,11.69
ssl_resnet18,2711.89,188.46,512,224,11.69
mobilenetv2_050,2618.63,194.751,512,224,1.97
levit_256,2590.96,196.476,512,224,18.89
semnasnet_050,2528.95,201.569,512,224,2.08
regnetx_004,2522.75,201.894,512,224,5.16
mnasnet_050,2522.58,202.188,512,224,2.22
seresnet18,2507.84,203.663,512,224,11.78
ese_vovnet19b_slim_dw,2471.49,206.677,512,224,1.9
legacy_seresnet18,2441.93,209.163,512,224,11.78
tinynet_c,2430.81,209.624,512,184,2.46
tf_mobilenetv3_large_minimal_100,2297.77,222.108,512,224,3.92
lcnet_150,2274.7,224.596,512,224,4.5
levit_256d,2246.11,226.444,512,224,26.21
ghostnet_050,2164.08,235.253,512,224,2.59
mobilenetv3_large_075,2163.25,235.816,512,224,3.99
resnet18d,2077.18,246.121,512,224,11.71
tf_mobilenetv3_large_075,2064.86,247.051,512,224,3.99
regnetx_006,2039.62,250.217,512,224,6.2
ese_vovnet19b_slim,2002.06,255.364,512,224,3.17
mobilenetv3_rw,1974.38,258.462,512,224,5.48
mobilenetv3_large_100_miil,1968.34,259.245,512,224,5.48
mobilenetv3_large_100,1965.11,259.678,512,224,5.48
mnasnet_075,1898.08,268.968,512,224,3.17
mobilenetv2_075,1880.91,271.408,512,224,2.64
tf_mobilenetv3_large_100,1872.32,272.582,512,224,5.48
tf_efficientnetv2_b0,1868.24,272.852,512,224,7.14
resnetblur18,1851.92,276.12,512,224,11.69
regnety_004,1839.55,277.22,512,224,4.34
semnasnet_075,1812.64,281.537,512,224,2.91
regnety_006,1807.53,282.196,512,224,6.06
skresnet18,1781.57,286.76,512,224,11.96
mobilenetv2_100,1759.59,290.188,512,224,3.5
mnasnet_b1,1711.38,298.386,512,224,4.38
mnasnet_100,1703.75,299.741,512,224,4.38
vit_tiny_patch16_224,1703.5,299.738,512,224,5.72
deit_tiny_patch16_224,1700.58,300.234,512,224,5.72
tinynet_b,1695.36,300.958,512,188,3.73
hardcorenas_a,1688.73,302.486,512,224,5.26
hardcorenas_b,1681.38,303.598,512,224,5.18
deit_tiny_distilled_patch16_224,1676.33,304.592,512,224,5.91
regnetx_008,1660.21,307.58,512,224,7.26
semnasnet_100,1660.21,307.494,512,224,3.89
mnasnet_a1,1660.16,307.488,512,224,3.89
levit_384,1645.5,310.035,512,224,39.13
visformer_tiny,1629.45,313.55,512,224,10.32
gluon_resnet34_v1b,1628.8,313.768,512,224,21.8
tv_resnet34,1628.63,313.804,512,224,21.8
resnet34,1618.43,315.788,512,224,21.8
mixer_b32_224,1614.41,316.375,512,224,60.29
hardcorenas_c,1606.09,317.82,512,224,5.52
spnasnet_100,1581.9,322.7,512,224,4.42
hardcorenas_d,1573.64,324.168,512,224,7.5
pit_ti_distilled_224,1567.79,325.678,512,224,5.1
pit_ti_224,1567.05,325.843,512,224,4.85
vit_base_patch32_224,1566.16,326.106,512,224,88.22
vit_base_patch32_224_sam,1565.94,326.137,512,224,88.22
ghostnet_100,1561.28,326.61,512,224,5.18
regnety_008,1549.78,329.38,512,224,6.26
resmlp_12_distilled_224,1540.69,331.527,512,224,15.35
resmlp_12_224,1540.68,331.535,512,224,15.35
seresnet34,1491.24,342.456,512,224,21.96
nf_regnet_b0,1463.76,348.603,512,256,8.76
gernet_m,1452.99,351.696,512,224,21.14
legacy_seresnet34,1444.09,353.657,512,224,21.96
ese_vovnet19b_dw,1432.57,356.897,512,224,6.54
nf_resnet26,1427.35,358.203,512,224,16.0
tinynet_a,1409.24,362.071,512,192,6.19
dla46_c,1404.15,363.911,512,224,1.3
rexnetr_100,1384.43,276.261,384,224,4.88
mobilenetv2_110d,1383.76,276.51,384,224,4.52
efficientnet_lite0,1382.82,369.515,512,224,4.65
rexnet_100,1378.22,277.499,384,224,4.8
resnet34d,1368.6,373.438,512,224,21.82
hardcorenas_f,1363.96,374.257,512,224,8.2
xcit_nano_12_p16_224_dist,1357.57,375.351,512,224,3.05
xcit_nano_12_p16_224,1356.26,375.722,512,224,3.05
selecsls42,1352.83,377.829,512,224,30.35
ghostnet_130,1348.59,378.322,512,224,7.36
selecsls42b,1347.97,379.197,512,224,32.46
mixer_s16_224,1328.86,384.74,512,224,18.53
tf_efficientnet_lite0,1326.3,385.288,512,224,4.65
regnetz_005,1322.96,385.624,512,224,7.12
resnet26,1320.55,387.258,512,224,16.0
hardcorenas_e,1317.58,387.482,512,224,8.07
hrnet_w18_small,1302.47,391.734,512,224,13.19
pit_xs_distilled_224,1268.5,402.739,512,224,11.0
pit_xs_224,1268.42,402.775,512,224,10.62
fbnetc_100,1266.68,403.231,512,224,5.57
mnasnet_140,1263.67,404.387,512,224,7.12
mobilenetv2_140,1253.56,305.536,384,224,6.11
vit_small_patch32_384,1234.94,413.769,512,384,22.92
efficientnet_b0,1229.26,311.326,384,224,5.29
poolformer_s12,1218.66,419.43,512,224,11.92
semnasnet_140,1213.3,421.085,512,224,6.11
nf_seresnet26,1200.27,425.903,512,224,17.4
vit_tiny_r_s16_p8_384,1194.12,320.732,384,384,6.36
tf_efficientnetv2_b1,1189.33,321.432,384,240,8.14
gmixer_12_224,1181.89,432.408,512,224,12.7
repvgg_b0,1180.49,432.688,512,224,15.82
tf_efficientnet_b0_ap,1177.13,325.127,384,224,5.29
tf_efficientnet_b0,1176.58,325.256,384,224,5.29
tf_efficientnet_b0_ns,1176.09,325.406,384,224,5.29
efficientnet_b1_pruned,1160.78,439.616,512,240,6.33
selecsls60,1153.95,442.796,512,224,30.67
selecsls60b,1150.77,444.044,512,224,32.77
resnet26d,1125.05,454.584,512,224,16.01
nf_ecaresnet26,1118.2,457.322,512,224,16.0
mixnet_s,1099.59,464.39,512,224,4.13
rexnetr_130,1097.48,232.14,256,224,7.61
dla34,1070.28,477.798,512,224,15.74
dla46x_c,1057.9,483.219,512,224,1.07
rexnet_130,1047.2,243.344,256,224,7.56
regnetx_016,1042.62,490.182,512,224,9.19
tf_mixnet_s,1040.0,491.07,512,224,4.13
mobilenetv2_120d,1039.92,245.01,256,224,5.83
skresnet34,1030.78,495.577,512,224,22.28
dla60x_c,1018.3,501.873,512,224,1.32
ecaresnet50d_pruned,1010.79,505.611,512,224,19.94
gernet_l,1008.74,506.703,512,256,31.08
mobilevit_xxs,994.64,384.944,384,256,1.27
xcit_tiny_12_p16_224,994.0,513.339,512,224,6.72
xcit_tiny_12_p16_224_dist,993.15,513.793,512,224,6.72
efficientnet_b0_g16_evos,992.08,385.991,384,224,8.11
rexnetr_150,974.49,261.552,256,224,9.78
convnext_nano_hnf,957.8,400.126,384,224,15.59
crossvit_tiny_240,953.54,401.134,384,240,7.01
crossvit_9_240,948.17,403.562,384,240,8.55
rexnet_150,931.33,273.747,256,224,9.73
vit_base2_patch32_256,930.69,549.32,512,256,119.46
repvgg_a2,930.45,549.419,512,224,28.21
legacy_seresnext26_32x4d,924.87,552.965,512,224,16.79
regnety_016,921.92,553.59,512,224,11.2
efficientnet_lite1,920.32,277.193,256,240,5.42
gmlp_ti16_224,915.04,418.12,384,224,5.87
convit_tiny,914.83,418.772,384,224,5.71
efficientnet_es_pruned,914.62,559.049,512,224,5.44
crossvit_9_dagger_240,914.01,418.663,384,240,8.78
efficientnet_es,913.84,559.524,512,224,5.44
resnest14d,902.54,566.834,512,224,10.61
tf_efficientnet_es,895.9,570.736,512,224,5.44
vit_small_patch16_224,886.44,432.354,384,224,22.05
deit_small_patch16_224,886.38,432.371,384,224,22.05
resnetv2_50,885.9,577.167,512,224,25.55
tf_efficientnet_lite1,884.99,288.297,256,240,5.42
resnext26ts,882.6,434.57,384,256,10.3
resnet26t,880.32,581.109,512,256,16.01
nf_regnet_b1,876.86,582.443,512,288,10.22
tf_efficientnetv2_b2,873.82,291.458,256,260,10.1
nf_regnet_b2,872.25,585.395,512,272,14.31
deit_small_distilled_patch16_224,870.96,440.043,384,224,22.44
eca_resnext26ts,854.22,299.135,256,256,10.3
seresnext26ts,848.06,301.208,256,256,10.39
gluon_resnet50_v1b,836.3,458.36,384,224,25.56
swsl_resnet50,836.28,458.365,384,224,25.56
tv_resnet50,835.63,458.72,384,224,25.56
resnet50,833.11,460.106,384,224,25.56
botnet26t_256,831.36,461.332,384,256,12.49
ssl_resnet50,830.95,461.318,384,224,25.56
gcresnext26ts,830.68,307.354,256,256,10.48
seresnext26tn_32x4d,830.61,461.636,384,224,16.81
seresnext26t_32x4d,830.27,461.827,384,224,16.81
seresnext26d_32x4d,828.27,462.949,384,224,16.81
pit_s_224,823.52,309.982,256,224,23.46
vgg11,823.03,621.921,512,224,132.86
pit_s_distilled_224,820.99,310.896,256,224,24.04
halonet26t,808.46,474.411,384,256,12.48
eca_botnext26ts_256,804.84,317.488,256,256,10.59
vit_small_resnet26d_224,799.3,479.391,384,224,63.61
resnetv2_50t,795.78,642.594,512,224,25.57
ecaresnext26t_32x4d,794.24,482.933,384,224,15.41
resnetv2_50d,793.28,644.617,512,224,25.57
ecaresnext50t_32x4d,791.08,484.877,384,224,15.41
tresnet_m,787.35,647.607,512,224,31.39
vovnet39a,782.12,654.018,512,224,22.6
efficientnet_b0_gn,780.55,326.912,256,224,5.29
fbnetv3_d,780.39,326.274,256,256,10.31
eca_halonext26ts,780.25,327.496,256,256,10.76
fbnetv3_b,780.18,490.58,384,256,8.6
cspresnet50,779.41,491.838,384,256,21.62
ecaresnet101d_pruned,774.28,659.497,512,224,24.88
efficientnet_cc_b0_8e,770.73,497.068,384,224,24.01
gluon_resnet50_v1c,770.17,497.757,384,224,25.58
efficientnet_cc_b0_4e,768.45,498.536,384,224,13.31
ecaresnetlight,767.52,666.18,512,224,30.16
cspresnext50,767.32,499.601,384,224,20.57
mixnet_m,767.21,499.005,384,224,5.01
efficientnet_b2_pruned,763.33,333.903,256,260,8.31
resnet50t,754.86,507.852,384,224,25.57
gluon_resnet50_v1d,754.57,508.055,384,224,25.58
resnet50d,753.37,508.854,384,224,25.58
resmlp_24_224,752.46,338.709,256,224,30.02
resmlp_24_distilled_224,751.46,339.201,256,224,30.02
ese_vovnet39b,748.27,512.528,384,224,24.57
tf_efficientnet_cc_b0_8e,747.26,512.722,384,224,24.01
tf_efficientnet_cc_b0_4e,746.74,513.086,384,224,13.31
resnet32ts,744.48,343.29,256,256,17.96
visformer_small,743.67,515.696,384,224,40.22
legacy_seresnet50,743.56,515.327,384,224,28.09
dpn68b,738.91,518.504,384,224,12.61
selecsls84,736.93,693.544,512,224,50.95
resnet33ts,736.41,347.04,256,256,19.68
tf_mixnet_m,730.05,524.465,384,224,5.01
nf_seresnet50,727.19,526.873,384,224,28.09
rexnetr_200,725.21,263.618,192,224,16.52
res2net50_48w_2s,723.44,529.975,384,224,25.29
dpn68,721.43,531.156,384,224,12.61
lambda_resnet26t,720.18,532.596,384,256,10.96
seresnet50,719.22,532.776,384,224,28.09
tf_efficientnet_b1_ns,717.68,355.196,256,240,7.79
tf_efficientnet_b1,717.65,355.204,256,240,7.79
tf_efficientnet_b1_ap,717.6,355.242,256,240,7.79
eca_resnet33ts,713.27,358.233,256,256,19.68
bat_resnext26ts,709.94,359.448,256,256,10.73
seresnet33ts,708.46,360.554,256,256,19.78
resnetblur50,706.03,543.087,384,224,25.56
cspresnet50d,704.69,544.074,384,256,21.64
rexnet_200,702.3,272.253,192,224,16.37
eca_vovnet39b,698.49,732.369,512,224,22.6
cspresnet50w,698.43,548.944,384,256,28.12
dla60,695.38,551.258,384,224,22.04
efficientnet_b1,694.5,367.105,256,256,7.79
efficientnet_lite2,691.09,369.477,256,260,6.09
tv_densenet121,688.36,370.145,256,224,7.98
vgg11_bn,688.31,371.701,256,224,132.87
gcresnet33ts,687.54,371.346,256,256,19.88
densenet121,686.73,371.056,256,224,7.98
resnest26d,682.74,561.689,384,224,17.07
resnetaa50d,680.45,563.474,384,224,25.58
gluon_resnet50_v1s,673.44,569.389,384,224,25.68
hrnet_w18_small_v2,669.83,761.985,512,224,15.6
nf_ecaresnet50,669.55,572.548,384,224,25.56
tf_efficientnet_lite2,667.12,382.773,256,260,6.09
vit_base_resnet26d_224,663.97,577.082,384,224,101.4
vit_small_r26_s32_224,661.78,385.595,256,224,36.43
lambda_resnet26rpt_256,660.67,193.152,128,256,10.99
efficientnet_b0_g8_gn,657.99,387.987,256,224,6.56
seresnet50t,654.75,389.823,256,224,28.1
resnext50_32x4d,651.94,588.217,384,224,25.03
swsl_resnext50_32x4d,651.54,588.552,384,224,25.03
gluon_resnext50_32x4d,651.5,588.601,384,224,25.03
ssl_resnext50_32x4d,651.06,588.971,384,224,25.03
tv_resnext50_32x4d,651.04,589.025,384,224,25.03
haloregnetz_b,649.9,392.411,256,224,11.68
resnetrs50,647.82,591.571,384,224,35.69
regnetx_032,644.99,594.128,384,224,15.3
resnetblur50d,643.36,397.048,256,224,25.58
densenet121d,640.21,398.026,256,224,8.0
mobilevit_xs,636.32,300.601,192,256,2.32
res2net50_26w_4s,636.08,401.175,256,224,25.7
ese_vovnet57b,632.89,605.833,384,224,38.61
convnext_tiny_hnf,631.3,404.531,256,224,28.59
skresnet50,629.62,405.227,256,224,25.8
densenetblur121d,620.91,410.489,256,224,8.0
poolformer_s24,618.55,412.632,256,224,21.39
ecaresnet50d,617.9,413.387,256,224,25.58
gluon_inception_v3,602.04,636.443,384,299,23.83
tf_inception_v3,601.78,636.737,384,299,23.83
resnext50d_32x4d,599.81,425.968,256,224,25.05
adv_inception_v3,598.91,639.776,384,299,23.83
inception_v3,597.68,641.096,384,299,23.83
seresnetaa50d,595.51,428.742,256,224,28.11
sehalonet33ts,593.18,430.755,256,256,13.69
coat_lite_tiny,588.45,651.687,384,224,5.72
efficientnet_b3_pruned,588.04,433.698,256,300,9.86
mixnet_l,587.47,434.23,256,224,7.33
gmixer_24_224,586.46,435.043,256,224,24.72
gcresnet50t,584.74,436.344,256,256,25.9
vovnet57a,583.53,876.573,512,224,36.64
skresnet50d,581.8,438.63,256,224,25.82
resnetv2_50x1_bit_distilled,579.51,330.493,192,224,25.55
res2next50,576.25,443.0,256,224,24.67
seresnext50_32x4d,575.09,444.01,256,224,27.56
cspresnext50_iabn,574.6,666.024,384,256,20.57
legacy_seresnext50_32x4d,573.45,445.299,256,224,27.56
res2net50_14w_8s,572.23,445.23,256,224,25.06
gluon_seresnext50_32x4d,572.14,446.313,256,224,27.56
repvgg_b1g4,571.09,895.496,512,224,39.97
convnext_tiny,568.67,449.214,256,224,28.59
resnest50d_1s4x24d,568.37,449.124,256,224,25.68
vgg13,565.29,679.111,384,224,133.05
densenet169,564.44,451.109,256,224,14.15
coat_lite_mini,560.18,684.613,384,224,11.01
tf_mixnet_l,559.29,456.201,256,224,7.33
dla60_res2net,558.91,456.605,256,224,20.85
darknet53,555.4,460.146,256,256,41.61
dla60x,553.72,461.36,256,224,17.35
efficientnet_em,553.62,692.657,384,240,6.9
regnetx_040,551.95,694.615,384,224,22.12
tf_efficientnet_em,550.96,463.679,256,240,6.9
nf_resnet101,550.06,696.472,384,224,44.55
nf_regnet_b3,545.32,467.686,256,320,18.59
tf_efficientnet_b2_ns,542.89,352.148,192,260,9.11
tf_efficientnet_b2_ap,542.72,352.279,192,260,9.11
tf_efficientnet_b2,542.33,352.563,192,260,9.11
resnetv2_101,541.77,470.948,256,224,44.54
tf_efficientnetv2_b3,537.24,355.668,192,300,14.36
gcresnext50ts,536.7,356.26,192,256,15.67
nf_resnet50,535.99,715.561,384,288,25.56
xcit_small_12_p16_224_dist,535.18,476.598,256,224,26.25
xcit_small_12_p16_224,535.12,476.63,256,224,26.25
sebotnet33ts_256,533.03,239.342,128,256,13.7
efficientnetv2_rw_t,527.89,361.618,192,288,13.65
resnet101,526.2,484.988,256,224,44.55
twins_svt_small,526.18,484.993,256,224,24.06
tv_resnet101,525.84,485.332,256,224,44.55
resnet50_gn,525.26,364.696,192,224,25.56
gluon_resnet101_v1b,524.51,486.543,256,224,44.55
mobilevit_s,521.06,367.349,192,256,5.58
crossvit_small_240,519.76,367.784,192,240,26.86
xcit_tiny_24_p16_224,519.69,489.334,256,224,12.12
xcit_tiny_24_p16_224_dist,519.36,489.596,256,224,12.12
vit_base_r26_s32_224,518.41,369.094,192,224,101.38
mixer_b16_224,512.16,499.054,256,224,59.88
mixer_b16_224_miil,512.15,499.069,256,224,59.88
gmlp_s16_224,510.63,374.487,192,224,19.42
resnetv2_101d,506.75,503.627,256,224,44.56
vit_base_resnet50d_224,506.41,503.941,256,224,110.97
dla60_res2next,504.89,505.645,256,224,17.03
vit_base_patch32_384,503.41,507.725,256,384,88.3
repvgg_b1,499.68,1023.594,512,224,57.42
resmlp_36_distilled_224,499.65,382.104,192,224,44.69
resmlp_36_224,499.61,382.157,192,224,44.69
gluon_resnet101_v1c,499.33,511.143,256,224,44.57
vit_large_patch32_224,498.76,511.726,256,224,306.54
efficientnet_b2a,498.46,383.699,192,288,9.11
efficientnet_b2,498.23,383.892,192,288,9.11
semobilevit_s,498.08,384.196,192,256,5.74
wide_resnet50_2,492.85,518.616,256,224,68.88
gluon_resnet101_v1d,492.69,518.053,256,224,44.57
mixer_l32_224,486.84,392.903,192,224,206.94
efficientnet_cc_b1_8e,485.45,525.706,256,240,39.72
cspdarknet53,485.41,526.351,256,256,27.64
gc_efficientnetv2_rw_t,484.77,393.323,192,288,13.68
cait_xxs24_224,483.07,527.475,256,224,11.96
resnest50d,481.14,530.778,256,224,27.48
res2net50_26w_6s,478.7,533.037,256,224,37.05
crossvit_15_240,477.76,400.069,192,240,27.53
dla102,477.62,534.469,256,224,33.27
ecaresnet26t,476.78,536.378,256,320,16.01
regnetz_b16,474.17,403.475,192,288,9.72
tf_efficientnet_cc_b1_8e,473.85,538.615,256,240,39.72
xcit_nano_12_p16_384_dist,473.63,538.718,256,384,3.05
cspdarknet53_iabn,473.06,809.288,384,256,27.64
convnext_tiny_hnfd,470.51,543.084,256,224,28.63
vgg13_bn,465.58,549.581,256,224,133.05
vgg16,464.87,825.812,384,224,138.36
regnetx_080,463.41,827.528,384,224,39.57
crossvit_15_dagger_240,461.34,414.345,192,240,28.21
resnetaa101d,460.14,554.755,256,224,44.57
lambda_resnet50ts,459.6,416.745,192,256,21.54
halonet50ts,459.3,417.05,192,256,22.73
legacy_seresnet101,458.51,556.133,256,224,49.33
gluon_resnet101_v1s,457.44,558.089,256,224,44.67
densenet201,452.47,421.386,192,224,20.01
swin_tiny_patch4_window7_224,451.01,566.618,256,224,28.29
seresnet101,447.55,569.776,256,224,49.33
resnetblur101d,441.76,577.918,256,224,44.57
nf_seresnet101,440.27,579.119,256,224,49.33
mixnet_xl,435.11,586.493,256,224,11.9
twins_pcpvt_small,428.18,596.275,256,224,24.11
nfnet_l0,422.47,604.781,256,288,35.07
skresnext50_32x4d,418.8,609.905,256,224,27.48
swin_s3_tiny_224,418.5,457.809,192,224,28.33
gluon_resnext101_32x4d,418.3,610.447,256,224,44.18
swsl_resnext101_32x4d,418.28,610.459,256,224,44.18
ssl_resnext101_32x4d,418.21,610.626,256,224,44.18
resnext101_32x4d,418.12,610.73,256,224,44.18
vit_tiny_patch16_384,415.69,307.09,128,384,5.79
botnet50ts_256,415.68,306.991,128,256,22.74
poolformer_s36,413.64,462.249,192,224,30.86
ese_vovnet39b_evos,408.73,312.204,128,224,24.58
convit_small,408.52,468.993,192,224,27.78
res2net101_26w_4s,406.07,470.321,192,224,45.21
eca_nfnet_l0,404.15,632.409,256,288,24.14
efficientnet_lite3,403.71,315.975,128,300,8.2
halo2botnet50ts_256,403.26,316.425,128,256,22.64
tresnet_l,403.06,1266.831,512,224,55.99
resnet51q,399.11,480.193,192,288,35.7
nf_ecaresnet101,394.48,647.098,256,224,44.55
dla102x,393.78,486.022,192,224,26.31
vgg19,393.77,974.937,384,224,143.67
res2net50_26w_8s,393.74,485.439,192,224,48.4
lamhalobotnet50ts_256,392.54,325.068,128,256,22.57
regnetx_064,392.18,651.888,256,224,26.21
regnety_032,391.93,651.749,256,288,19.44
tf_efficientnet_lite3,390.65,326.582,128,300,8.2
vgg16_bn,389.79,656.438,256,224,138.37
xception,385.34,331.396,128,299,22.86
resnetv2_152,380.13,671.312,256,224,60.19
swin_v2_cr_tiny_224,379.43,504.758,192,224,28.33
ecaresnet101d,378.93,673.854,256,224,44.57
resnest50d_4s2x40d,378.25,675.481,256,224,30.42
repvgg_b2g4,377.89,1353.806,512,224,61.76
ese_vovnet99b,373.42,684.063,256,224,63.2
tv_resnet152,371.1,515.112,192,224,60.19
resnet152,371.02,515.239,192,224,60.19
convnext_small,370.63,516.315,192,224,50.22
xcit_nano_12_p8_224,370.09,689.984,256,224,3.05
xcit_nano_12_p8_224_dist,369.33,691.413,256,224,3.05
gluon_resnet152_v1b,369.24,517.744,192,224,60.19
nfnet_f0,367.34,695.748,256,256,71.49
gluon_seresnext101_32x4d,366.5,521.688,192,224,48.96
seresnext101_32x4d,366.15,522.18,192,224,48.96
legacy_seresnext101_32x4d,365.14,523.663,192,224,48.96
vit_base_patch16_224_miil,364.71,350.199,128,224,86.54
nest_tiny,363.32,351.416,128,224,17.06
resnetv2_152d,361.72,528.569,192,224,60.2
vit_small_resnet50d_s16_224,361.26,530.264,192,224,57.53
resnet61q,360.88,353.672,128,288,36.85
jx_nest_tiny,360.53,354.122,128,224,17.06
swin_v2_cr_tiny_ns_224,360.48,531.298,192,224,28.33
vit_base_patch16_224,359.03,355.693,128,224,86.57
vit_base_patch16_224_sam,358.97,355.726,128,224,86.57
ese_vovnet99b_iabn,358.47,1068.125,384,224,63.2
gluon_resnet152_v1c,358.0,534.017,192,224,60.21
deit_base_patch16_224,356.65,358.076,128,224,86.57
regnety_040,355.37,538.804,192,288,20.65
gluon_resnet152_v1d,353.37,541.005,192,224,60.21
regnety_040s_gn,351.45,362.7,128,224,20.65
deit_base_distilled_patch16_224,351.33,363.49,128,224,87.34
resnetv2_50d_frn,347.92,366.764,128,224,25.59
crossvit_18_240,347.71,366.132,128,240,43.27
xcit_tiny_12_p16_384_dist,343.61,557.009,192,384,6.72
xception41p,343.15,372.168,128,299,26.91
volo_d1_224,342.86,371.99,128,224,26.63
regnetv_040,340.89,374.038,128,288,20.64
hrnet_w18,340.14,747.884,256,224,21.3
repvgg_b2,339.58,1506.684,512,224,89.02
fbnetv3_g,338.81,375.801,128,288,16.62
crossvit_18_dagger_240,336.48,378.386,128,240,44.27
vgg19_bn,336.38,760.656,256,224,143.68
gluon_resnet152_v1s,335.54,569.962,192,224,60.32
dla169,331.7,576.335,192,224,53.39
densenet161,329.95,385.629,128,224,28.68
dm_nfnet_f0,329.15,776.517,256,256,71.49
coat_lite_small,327.59,584.625,192,224,19.84
resnetv2_50d_gn,326.94,390.7,128,288,25.57
beit_base_patch16_224,326.19,391.317,128,224,86.53
repvgg_b3g4,321.01,1195.136,384,224,83.83
tf_efficientnet_b3_ns,318.86,399.788,128,300,12.23
tf_efficientnet_b3,318.7,399.98,128,300,12.23
tf_efficientnet_b3_ap,318.42,400.336,128,300,12.23
legacy_seresnet152,315.73,604.891,192,224,66.82
dpn92,314.66,812.131,256,224,37.67
inception_v4,312.7,611.827,192,299,42.68
efficientnet_b3,312.0,408.597,128,320,12.23
efficientnet_b3a,311.95,408.654,128,320,12.23
twins_pcpvt_base,311.39,613.825,192,224,43.83
convmixer_1024_20_ks9_p14,310.04,824.873,256,224,24.38
regnetx_120,309.97,824.929,256,224,46.11
cait_xxs36_224,308.02,411.825,128,224,17.3
ecaresnet50t,306.62,416.516,128,320,25.57
hrnet_w32,305.43,623.994,192,224,41.23
seresnet152,303.38,418.64,128,224,66.82
twins_svt_base,303.13,420.211,128,224,56.07
regnetz_c16,302.01,422.387,128,320,13.46
hrnet_w30,301.1,845.453,256,224,37.71
tresnet_xl,294.8,1299.032,384,224,78.44
swin_small_patch4_window7_224,294.09,433.317,128,224,49.61
pit_b_224,291.77,328.073,96,224,73.76
xception41,291.75,437.519,128,299,26.97
regnety_120,291.47,657.427,192,224,51.82
pit_b_distilled_224,289.77,330.344,96,224,74.79
wide_resnet101_2,288.45,664.093,192,224,126.89
nf_regnet_b4,286.33,444.906,128,384,30.21
mixnet_xxl,281.29,453.113,128,224,23.96
poolformer_m36,278.5,457.747,128,224,56.17
xcit_small_24_p16_224_dist,276.84,459.031,128,224,47.67
repvgg_b3,276.53,1387.56,384,224,123.09
xcit_small_24_p16_224,275.37,461.371,128,224,47.67
convnext_small_in22ft1k,274.88,463.928,128,224,88.59
convnext_base,274.83,464.011,128,224,88.59
convnext_tiny_in22ft1k,273.31,466.623,128,224,88.59
convnext_base_in22ft1k,272.88,467.352,128,224,88.59
gluon_resnext101_64x4d,268.43,475.336,128,224,83.46
dla102x2,266.91,478.025,128,224,41.28
cait_s24_224,265.32,479.979,128,224,46.92
resnet200,265.02,479.979,128,224,64.67
vit_small_patch16_18x2_224,263.71,482.808,128,224,64.67
regnetx_160,261.64,732.791,192,224,54.28
xcit_tiny_12_p8_224_dist,261.1,488.495,128,224,6.71
xcit_tiny_12_p8_224,260.74,489.138,128,224,6.71
vit_small_patch16_36x1_224,259.32,367.632,96,224,64.67
xception65p,258.71,493.479,128,299,39.82
ens_adv_inception_resnet_v2,255.7,747.458,192,299,55.84
resnetv2_50d_evob,254.24,376.389,96,224,25.59
inception_resnet_v2,254.09,752.309,192,299,55.84
efficientnet_el,253.35,504.154,128,300,10.59
efficientnet_el_pruned,253.34,504.171,128,300,10.59
resnext101_32x8d,252.02,506.385,128,224,88.79
swsl_resnext101_32x8d,252.02,506.295,128,224,88.79
ssl_resnext101_32x8d,251.67,507.107,128,224,88.79
resnetrs101,251.09,507.486,128,288,63.62
ig_resnext101_32x8d,250.58,509.299,128,224,88.79
dpn98,249.31,511.881,128,224,61.57
tf_efficientnet_el,249.14,512.694,128,300,10.59
efficientnetv2_s,245.1,389.491,96,384,21.46
gluon_seresnext101_64x4d,243.69,523.04,128,224,88.23
tf_efficientnetv2_s,243.67,391.823,96,384,21.46
tf_efficientnetv2_s_in21ft1k,242.75,393.147,96,384,21.46
gmlp_b16_224,241.6,395.795,96,224,73.08
resnet101d,240.1,531.541,128,320,44.57
nest_small,238.81,400.33,96,224,38.35
resnest101e,237.62,536.114,128,256,48.28
jx_nest_small,237.34,402.863,96,224,38.35
swin_v2_cr_small_224,234.05,407.737,96,224,49.7
twins_svt_large,233.44,546.209,128,224,99.27
efficientnetv2_rw_s,232.97,272.53,64,384,23.94
regnety_064,232.53,548.809,128,288,30.58
crossvit_base_240,232.11,411.966,96,240,105.03
coat_tiny,230.73,552.729,128,224,5.5
swin_s3_small_224,227.28,420.551,96,224,49.74
swin_base_patch4_window7_224,225.83,564.975,128,224,87.77
vit_large_r50_s32_224,224.13,425.968,96,224,328.99
gluon_xception65,224.07,426.586,96,299,39.92
regnetv_064,223.77,570.349,128,288,30.58
xception65,222.29,429.965,96,299,39.92
hrnet_w40,221.98,860.248,192,224,57.56
twins_pcpvt_large,221.53,573.857,128,224,60.99
regnety_080,221.41,576.9,128,288,39.18
vit_small_r26_s32_384,217.53,292.946,64,384,36.47
convit_base,213.7,448.233,96,224,86.54
resnetv2_50d_evos,211.36,301.609,64,288,25.59
vit_small_patch16_384,211.21,302.185,64,384,22.2
tresnet_m_448,207.11,924.362,192,448,31.39
hrnet_w44,206.62,924.469,192,224,67.06
hrnet_w48,203.91,623.058,128,224,77.47
xcit_medium_24_p16_224_dist,201.77,472.474,96,224,84.4
efficientnet_lite4,201.72,315.945,64,380,13.01
regnetz_040,200.93,316.724,64,320,27.12
xcit_medium_24_p16_224,200.38,475.726,96,224,84.4
regnetz_040h,199.32,319.288,64,320,28.94
vit_base_r50_s16_224,198.49,320.852,64,224,98.66
volo_d2_224,198.45,481.736,96,224,58.68
regnetz_d8,197.22,322.887,64,320,23.37
regnetz_b16_evos,196.95,323.135,64,288,9.74
densenet264,196.71,484.156,96,224,72.69
coat_mini,196.35,649.865,128,224,10.34
tf_efficientnet_lite4,196.17,324.922,64,380,13.01
eca_nfnet_l1,189.49,673.644,128,320,41.41
dpn131,186.08,685.82,128,224,79.25
xcit_small_12_p16_384_dist,185.19,516.612,96,384,26.25
regnetz_d32,185.07,344.194,64,320,27.58
poolformer_m48,184.64,517.502,96,224,73.47
efficientnet_b3_gn,183.63,346.864,64,320,11.73
nest_base,179.17,355.564,64,224,67.72
jx_nest_base,178.25,357.393,64,224,67.72
xcit_tiny_24_p16_384_dist,178.08,535.75,96,384,12.12
swin_s3_base_224,176.4,360.127,64,224,71.13
swin_v2_cr_base_224,175.64,361.983,64,224,87.88
dpn107,174.69,731.058,128,224,86.92
resnet152d,172.77,553.323,96,320,60.21
efficientnet_b4,170.77,372.707,64,384,19.34
hrnet_w64,170.07,747.892,128,224,128.06
xception71,168.48,377.772,64,299,42.34
regnety_320,166.84,765.843,128,224,145.05
densenet264d_iabn,165.34,1156.78,192,224,72.74
halonet_h1,164.36,387.985,64,256,8.1
convnext_large_in22ft1k,162.57,588.815,96,224,197.77
convnext_large,162.19,590.164,96,224,197.77
tnt_s_patch16_224,160.48,795.734,128,224,23.76
tf_efficientnet_b4_ap,160.07,397.797,64,380,19.34
tf_efficientnet_b4,160.05,397.861,64,380,19.34
tf_efficientnet_b4_ns,159.86,398.285,64,380,19.34
mixer_l16_224,158.98,602.398,96,224,208.2
seresnet200d,156.82,607.841,96,256,71.86
efficientnet_b3_g8_gn,153.08,416.422,64,320,14.25
vit_large_patch32_384,148.01,430.862,64,384,306.63
regnetx_320,147.1,869.066,128,224,107.81
ecaresnet200d,146.51,433.421,64,256,64.69
seresnet152d,142.71,445.143,64,320,66.84
senet154,141.47,675.227,96,224,115.09
gluon_senet154,140.33,680.825,96,224,115.09
resnetrs152,140.22,453.07,64,320,86.62
resnetv2_50x1_bitm,140.19,341.567,48,448,25.55
xcit_small_12_p8_224,140.1,455.06,64,224,26.21
legacy_senet154,139.98,682.498,96,224,115.09
xcit_small_12_p8_224_dist,139.68,456.467,64,224,26.21
volo_d3_224,136.64,465.978,64,224,86.33
regnety_160,136.33,702.93,96,288,83.59
xcit_tiny_24_p8_224,135.22,706.664,96,224,12.11
xcit_tiny_24_p8_224_dist,135.04,707.588,96,224,12.11
swin_large_patch4_window7_224,134.46,474.195,64,224,196.53
tnt_b_patch16_224,128.28,746.509,96,224,65.41
seresnext101_32x8d,126.87,502.256,64,288,93.57
resnet200d,125.03,508.876,64,320,64.69
nfnet_f1,124.83,766.912,96,320,132.63
xcit_nano_12_p8_384_dist,124.74,511.323,64,384,3.05
resnext101_64x4d,122.53,781.921,96,288,83.46
xcit_large_24_p16_224,121.81,522.038,64,224,189.1
xcit_large_24_p16_224_dist,121.62,522.935,64,224,189.1
regnetz_c16_evos,121.42,393.457,48,320,13.49
efficientnetv2_m,119.95,397.043,48,416,54.14
seresnet269d,115.73,547.311,64,256,113.67
dm_nfnet_f1,111.52,571.621,64,320,132.63
nf_regnet_b5,111.52,571.237,64,456,49.74
swin_v2_cr_large_224,108.24,441.046,48,224,196.68
vit_large_patch16_224,107.89,443.324,48,224,304.33
convnext_xlarge_in22ft1k,105.95,602.3,64,224,350.2
vit_base_patch16_18x2_224,104.22,457.937,48,224,256.73
crossvit_15_dagger_408,103.66,306.843,32,408,28.5
efficientnetv2_rw_m,103.03,307.229,32,416,53.24
regnetz_e8,102.71,465.407,48,320,57.7
tresnet_l_448,102.02,1251.242,128,448,55.99
beit_large_patch16_224,100.02,477.913,48,224,304.43
ssl_resnext101_32x16d,99.42,964.104,96,224,194.03
ig_resnext101_32x16d,99.34,964.822,96,224,194.03
swsl_resnext101_32x16d,99.31,965.114,96,224,194.03
resnetrs200,98.78,481.487,48,320,93.21
xcit_small_24_p16_384_dist,94.29,505.743,48,384,47.67
convnext_small_384_in22ft1k,94.25,507.598,48,384,88.59
eca_nfnet_l2,93.98,678.342,64,384,56.72
convnext_tiny_384_in22ft1k,93.69,510.615,48,384,88.59
convnext_base_384_in22ft1k,93.6,511.079,48,384,88.59
vit_base_patch16_384,91.38,349.381,32,384,86.86
deit_base_patch16_384,91.25,349.874,32,384,86.86
swin_v2_cr_tiny_384,89.93,354.59,32,384,28.33
deit_base_distilled_patch16_384,89.45,356.909,32,384,87.63
tf_efficientnetv2_m,89.24,355.387,32,480,54.14
tf_efficientnetv2_m_in21ft1k,89.11,356.006,32,480,54.14
volo_d4_224,89.0,536.865,48,224,192.96
xcit_tiny_12_p8_384_dist,88.71,539.341,48,384,6.71
volo_d1_384,87.94,271.566,24,384,26.78
convmixer_768_32,87.33,1098.007,96,224,21.11
cait_xxs24_384,86.9,365.799,32,384,12.03
resnetv2_152x2_bit_teacher,86.51,367.584,32,224,236.34
resnetv2_101x1_bitm,85.93,370.849,32,448,44.54
regnetz_d8_evos,81.9,388.68,32,320,23.46
resnest200e,78.86,603.644,48,320,70.2
crossvit_18_dagger_408,78.2,304.877,24,408,44.61
beit_base_patch16_384,77.31,309.414,24,384,86.74
tresnet_xl_448,77.31,1238.041,96,448,78.44
efficientnet_b5,76.38,416.454,32,456,30.39
vit_large_patch14_224,76.22,418.295,32,224,304.2
tf_efficientnet_b5_ns,75.17,423.294,32,456,30.39
tf_efficientnet_b5,75.06,423.89,32,456,30.39
tf_efficientnet_b5_ap,74.91,424.757,32,456,30.39
vit_large_r50_s32_384,74.62,426.461,32,384,329.09
nfnet_f2,71.13,671.634,48,352,193.78
xcit_small_24_p8_224,70.93,447.831,32,224,47.63
xcit_small_24_p8_224_dist,70.82,448.457,32,224,47.63
xcit_medium_24_p16_384_dist,68.86,461.356,32,384,84.4
resmlp_big_24_distilled_224,67.63,471.604,32,224,129.14
resmlp_big_24_224,66.97,476.343,32,224,129.14
resmlp_big_24_224_in22ft1k,66.96,476.41,32,224,129.14
dm_nfnet_f2,63.38,754.059,48,352,193.78
ecaresnet269d,62.55,506.999,32,352,102.09
swin_base_patch4_window12_384,61.26,389.996,24,384,87.9
pnasnet5large,60.8,522.503,32,331,86.06
cait_xs24_384,60.18,396.29,24,384,26.67
resnetrs270,59.41,532.629,32,352,129.86
vit_base_patch8_224,58.54,272.507,16,224,86.58
nasnetalarge,58.23,544.595,32,331,88.75
volo_d5_224,57.67,551.667,32,224,295.46
cait_xxs36_384,57.1,416.606,24,384,17.37
convnext_large_384_in22ft1k,55.31,576.804,32,384,197.77
vit_base_resnet50_384,55.13,288.662,16,384,98.95
vit_base_r50_s16_384,55.08,288.922,16,384,98.95
swin_v2_cr_small_384,54.02,293.773,16,384,49.7
xcit_medium_24_p8_224,52.96,600.968,32,224,84.32
xcit_medium_24_p8_224_dist,52.91,601.478,32,224,84.32
ig_resnext101_32x32d,52.61,606.726,32,224,468.53
volo_d2_384,50.75,313.547,16,384,58.87
eca_nfnet_l3,50.5,630.136,32,448,72.04
convmixer_1536_20,49.92,960.799,48,224,51.63
xcit_small_12_p8_384_dist,47.77,500.692,24,384,26.21
tf_efficientnetv2_l_in21ft1k,47.35,333.533,16,480,118.52
efficientnetv2_l,47.16,334.995,16,480,118.52
tf_efficientnetv2_l,47.07,335.523,16,480,118.52
xcit_tiny_24_p8_384_dist,45.79,695.564,32,384,12.11
cait_s24_384,44.86,354.226,16,384,47.06
swin_v2_cr_huge_224,44.05,360.723,16,224,657.83
efficientnet_b6,42.26,375.764,16,528,43.04
xcit_large_24_p16_384_dist,41.96,568.582,24,384,189.1
tf_efficientnet_b6_ap,41.84,379.635,16,528,43.04
tf_efficientnet_b6,41.78,380.157,16,528,43.04
tf_efficientnet_b6_ns,41.7,380.74,16,528,43.04
swin_v2_cr_base_384,41.43,383.765,16,384,87.88
vit_huge_patch14_224,38.82,410.089,16,224,632.05
swin_large_patch4_window12_384,37.36,426.362,16,384,196.74
resnetrs350,37.22,637.051,24,384,163.96
nfnet_f3,35.3,675.657,24,416,254.92
convnext_xlarge_384_in22ft1k,34.59,460.906,16,384,350.2
resnest269e,33.49,709.738,24,416,110.93
dm_nfnet_f3,32.11,742.967,24,416,254.92
resnetv2_50x3_bitm,31.49,507.203,16,448,217.32
xcit_large_24_p8_224,31.1,511.188,16,224,188.93
xcit_large_24_p8_224_dist,31.08,511.4,16,224,188.93
resnetv2_152x2_bit_teacher_384,29.72,401.405,12,384,236.34
cait_s36_384,29.53,402.581,12,384,68.37
efficientnetv2_xl,28.84,410.429,12,512,208.12
tf_efficientnetv2_xl_in21ft1k,28.76,411.641,12,512,208.12
ig_resnext101_32x48d,27.57,578.926,16,224,828.41
vit_large_patch16_384,26.83,296.63,8,384,304.72
efficientnet_b7,25.65,308.317,8,600,66.35
tf_efficientnet_b7_ns,25.54,309.843,8,600,66.35
tf_efficientnet_b7,25.52,309.949,8,600,66.35
tf_efficientnet_b7_ap,25.49,310.429,8,600,66.35
resnetrs420,25.06,628.984,16,416,191.89
swin_v2_cr_large_384,24.48,324.319,8,384,196.68
xcit_small_24_p8_384_dist,24.12,494.319,12,384,47.63
beit_large_patch16_384,22.92,347.104,8,384,305.0
vit_giant_patch14_224,21.77,364.805,8,224,1012.61
resnetv2_152x2_bitm,21.5,369.846,8,448,236.34
volo_d3_448,21.39,278.066,6,448,86.63
nfnet_f4,18.65,638.182,12,512,316.07
resnetv2_101x3_bitm,17.49,455.806,8,448,387.93
xcit_medium_24_p8_384_dist,17.39,456.608,8,384,84.32
dm_nfnet_f4,16.87,705.913,12,512,316.07
volo_d4_448,15.85,376.008,6,448,193.41
tf_efficientnet_b8_ap,13.05,456.145,6,672,87.41
tf_efficientnet_b8,13.04,456.234,6,672,87.41
efficientnet_b8,13.01,457.314,6,672,87.41
nfnet_f5,12.16,651.359,8,544,377.21
cait_m36_384,11.39,523.115,6,384,271.22
dm_nfnet_f5,11.14,711.506,8,544,377.21
xcit_large_24_p8_384_dist,10.6,562.64,6,384,188.93
volo_d5_448,10.46,379.155,4,448,295.91
swin_v2_cr_huge_384,9.68,307.346,3,384,657.94
nfnet_f6,9.19,645.361,6,576,438.36
tf_efficientnet_l2_ns_475,9.01,438.204,4,475,480.31
beit_large_patch16_512,8.44,353.416,3,512,305.67
dm_nfnet_f6,8.42,705.117,6,576,438.36
volo_d5_512,6.78,291.864,2,512,296.09
nfnet_f7,6.51,605.721,4,608,499.5
cait_m48_448,4.62,428.106,2,448,356.46
resnetv2_152x4_bitm,4.47,445.366,2,480,936.53
tf_efficientnet_l2_ns,2.56,385.525,1,800,480.31
efficientnet_l2,2.55,385.937,1,800,480.31