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

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model,train_samples_per_sec,train_step_time,train_batch_size,train_img_size,param_count
tinynet_e,10725.36,46.047,512,106,2.04
mobilenetv3_small_050,9864.52,50.786,512,224,1.59
lcnet_035,9593.72,52.888,512,224,1.64
lcnet_050,8283.82,61.296,512,224,1.88
tf_mobilenetv3_small_minimal_100,8178.73,62.055,512,224,2.04
tinynet_d,7987.22,63.336,512,152,2.34
mobilenetv3_small_075,7734.29,65.482,512,224,2.04
mobilenetv3_small_100,7481.49,67.702,512,224,2.54
tf_mobilenetv3_small_075,7093.89,71.455,512,224,2.04
tf_mobilenetv3_small_100,6879.11,73.705,512,224,2.54
levit_128s,6303.14,80.293,512,224,7.78
lcnet_075,5742.95,88.676,512,224,2.36
lcnet_100,5331.75,95.531,512,224,2.95
mixer_s32_224,4714.36,108.029,512,224,19.1
mnasnet_small,4652.19,109.156,512,224,2.03
mnasnet_050,4534.41,112.14,512,224,2.22
levit_128,4434.56,114.332,512,224,9.21
vit_small_patch32_224,4334.06,117.284,512,224,22.88
mobilenetv2_035,4197.24,121.203,512,224,1.68
tinynet_c,4165.97,121.921,512,184,2.46
gernet_s,4117.74,123.649,512,224,8.17
semnasnet_050,4027.14,126.223,512,224,2.08
vit_tiny_r_s16_p8_224,3857.49,131.88,512,224,6.34
levit_192,3823.94,132.765,512,224,10.95
lcnet_150,3663.02,139.3,512,224,4.5
resnet18,3584.19,142.504,512,224,11.69
gluon_resnet18_v1b,3584.07,142.508,512,224,11.69
swsl_resnet18,3583.72,142.531,512,224,11.69
ssl_resnet18,3558.1,143.543,512,224,11.69
mobilenetv2_050,3541.93,143.76,512,224,1.97
mobilenetv3_large_075,3343.71,152.255,512,224,3.99
ese_vovnet19b_slim_dw,3243.14,157.395,512,224,1.9
tf_mobilenetv3_large_minimal_100,3227.09,157.922,512,224,3.92
seresnet18,3222.19,158.398,512,224,11.78
legacy_seresnet18,3130.77,163.021,512,224,11.78
tf_mobilenetv3_large_075,3109.15,163.824,512,224,3.99
mnasnet_075,3102.76,164.235,512,224,3.17
ghostnet_050,3069.54,165.437,512,224,2.59
mobilenetv3_rw,3020.36,168.644,512,224,5.48
mobilenetv3_large_100,2997.0,169.969,512,224,5.48
mobilenetv3_large_100_miil,2996.51,169.991,512,224,5.48
levit_256,2923.52,174.041,512,224,18.89
hardcorenas_a,2875.54,177.351,512,224,5.26
resnet18d,2830.02,180.547,512,224,11.71
mnasnet_b1,2826.42,180.324,512,224,4.38
mnasnet_100,2810.01,181.39,512,224,4.38
tf_mobilenetv3_large_100,2800.51,181.961,512,224,5.48
tinynet_b,2773.33,183.58,512,188,3.73
hardcorenas_b,2665.39,191.158,512,224,5.18
semnasnet_075,2649.51,192.342,512,224,2.91
hardcorenas_c,2643.17,192.764,512,224,5.52
ese_vovnet19b_slim,2613.26,195.551,512,224,3.17
mobilenetv2_075,2538.45,200.896,512,224,2.64
tf_efficientnetv2_b0,2507.59,202.986,512,224,7.14
spnasnet_100,2504.82,203.411,512,224,4.42
levit_256d,2485.6,204.456,512,224,26.21
hardcorenas_d,2483.8,204.983,512,224,7.5
semnasnet_100,2411.15,211.44,512,224,3.89
mnasnet_a1,2396.96,212.676,512,224,3.89
mobilenetv2_100,2381.65,214.209,512,224,3.5
regnetx_002,2371.97,215.169,512,224,2.68
tinynet_a,2274.6,223.875,512,192,6.19
regnety_002,2255.16,226.095,512,224,3.16
ghostnet_100,2251.56,226.062,512,224,5.18
fbnetc_100,2248.09,226.804,512,224,5.57
deit_tiny_patch16_224,2233.8,228.385,512,224,5.72
vit_tiny_patch16_224,2229.44,228.819,512,224,5.72
efficientnet_lite0,2209.28,231.003,512,224,4.65
hardcorenas_f,2207.45,230.839,512,224,8.2
deit_tiny_distilled_patch16_224,2193.62,232.567,512,224,5.91
hardcorenas_e,2183.35,233.392,512,224,8.07
xcit_nano_12_p16_224_dist,2148.4,236.588,512,224,3.05
xcit_nano_12_p16_224,2147.35,236.626,512,224,3.05
tv_resnet34,2081.13,245.45,512,224,21.8
resnet34,2080.93,245.474,512,224,21.8
gluon_resnet34_v1b,2070.75,246.674,512,224,21.8
pit_ti_distilled_224,2069.0,246.563,512,224,5.1
pit_ti_224,2067.14,246.798,512,224,4.85
tf_efficientnet_lite0,2051.57,248.83,512,224,4.65
skresnet18,2011.18,253.956,512,224,11.96
resnet26,1965.66,259.994,512,224,16.0
resnetblur18,1945.89,262.773,512,224,11.69
gernet_m,1920.15,265.947,512,224,21.14
ese_vovnet19b_dw,1905.39,268.216,512,224,6.54
nf_resnet26,1877.61,272.201,512,224,16.0
hrnet_w18_small,1858.6,274.127,512,224,13.19
seresnet34,1854.8,275.134,512,224,21.96
mnasnet_140,1835.61,278.136,512,224,7.12
legacy_seresnet34,1814.57,281.284,512,224,21.96
efficientnet_b0,1800.57,212.181,384,224,5.29
levit_384,1799.63,283.374,512,224,39.13
resnet34d,1799.03,284.0,512,224,21.82
mobilenetv2_110d,1768.64,216.1,384,224,4.52
rexnetr_100,1759.23,217.141,384,224,4.88
selecsls42,1754.3,291.22,512,224,30.35
selecsls42b,1748.59,292.176,512,224,32.46
mixer_b32_224,1728.02,295.478,512,224,60.29
tf_efficientnet_b0_ns,1702.0,224.532,384,224,5.29
tf_efficientnet_b0_ap,1700.69,224.751,384,224,5.29
tf_efficientnet_b0,1700.24,224.78,384,224,5.29
mixer_s16_224,1649.18,309.899,512,224,18.53
semnasnet_140,1640.99,311.119,512,224,6.11
tf_efficientnet_es,1622.88,314.744,512,224,5.44
efficientnet_es,1618.83,315.528,512,224,5.44
efficientnet_es_pruned,1616.07,316.054,512,224,5.44
vit_base_patch32_224_sam,1613.76,316.429,512,224,88.22
vit_base_patch32_224,1612.96,316.587,512,224,88.22
resnet26d,1609.37,317.63,512,224,16.01
tf_efficientnetv2_b1,1607.05,237.525,384,240,8.14
ghostnet_130,1600.19,318.63,512,224,7.36
pit_xs_distilled_224,1591.2,320.859,512,224,11.0
pit_xs_224,1589.39,321.258,512,224,10.62
repvgg_b0,1586.15,321.714,512,224,15.82
resmlp_12_224,1552.02,329.099,512,224,15.35
resmlp_12_distilled_224,1551.98,329.119,512,224,15.35
gmixer_12_224,1551.47,329.195,512,224,12.7
mobilenetv2_140,1539.46,248.646,384,224,6.11
mobilevit_xxs,1515.36,252.293,384,256,1.27
selecsls60,1486.56,343.544,512,224,30.67
selecsls60b,1480.82,344.867,512,224,32.77
nf_seresnet26,1471.47,347.302,512,224,17.4
xcit_tiny_12_p16_224,1422.37,358.218,512,224,6.72
xcit_tiny_12_p16_224_dist,1420.76,358.558,512,224,6.72
efficientnet_lite1,1418.67,179.483,256,240,5.42
vit_small_patch32_384,1414.68,361.045,512,384,22.92
efficientnet_b1_pruned,1384.32,368.407,512,240,6.33
gmlp_ti16_224,1378.39,276.995,384,224,5.87
dla46_c,1367.99,373.533,512,224,1.3
nf_ecaresnet26,1361.11,375.605,512,224,16.0
poolformer_s12,1359.83,375.831,512,224,11.92
rexnetr_130,1350.37,188.438,256,224,7.61
tf_efficientnet_lite1,1343.78,189.557,256,240,5.42
crossvit_tiny_240,1320.33,386.159,512,240,7.01
mobilenetv2_120d,1309.71,194.276,256,224,5.83
resnetv2_50,1296.0,394.281,512,224,25.55
gernet_l,1283.32,398.106,512,256,31.08
rexnet_100,1277.92,299.324,384,224,4.8
crossvit_9_240,1236.5,309.16,384,240,8.55
resnet26t,1227.85,416.475,512,256,16.01
ssl_resnet50,1223.5,417.643,512,224,25.56
resnet50,1222.61,417.956,512,224,25.56
tv_resnet50,1222.03,418.147,512,224,25.56
swsl_resnet50,1222.0,418.189,512,224,25.56
gluon_resnet50_v1b,1221.97,418.181,512,224,25.56
crossvit_9_dagger_240,1195.59,319.731,384,240,8.78
vit_tiny_r_s16_p8_384,1193.45,320.912,384,384,6.36
rexnetr_150,1185.63,214.799,256,224,9.78
fbnetv3_b,1184.86,322.487,384,256,8.6
botnet26t_256,1168.73,327.971,384,256,12.49
tf_efficientnetv2_b2,1157.41,219.649,256,260,10.1
regnetx_004,1150.82,443.834,512,224,5.16
repvgg_a2,1142.14,447.42,512,224,28.21
skresnet34,1140.48,447.803,512,224,22.28
resnetv2_50t,1134.35,450.541,512,224,25.57
fbnetv3_d,1133.65,223.966,256,256,10.31
resnetv2_50d,1131.93,451.499,512,224,25.57
gluon_resnet50_v1c,1131.41,338.54,384,224,25.58
halonet26t,1122.34,341.57,384,256,12.48
convit_tiny,1108.09,461.02,512,224,5.71
efficientnet_lite2,1096.26,232.544,256,260,6.09
dla34,1094.33,467.287,512,224,15.74
convnext_nano_hnf,1075.54,356.227,384,224,15.59
resnet50d,1070.21,357.929,384,224,25.58
gluon_resnet50_v1d,1070.13,357.997,384,224,25.58
resnet50t,1068.62,358.508,384,224,25.57
mixnet_s,1051.2,485.837,512,224,4.13
legacy_seresnext26_32x4d,1051.18,486.414,512,224,16.79
tf_efficientnet_lite2,1045.58,243.879,256,260,6.09
vit_small_resnet26d_224,1042.37,367.395,384,224,63.61
deit_small_patch16_224,1032.62,371.017,384,224,22.05
vit_small_patch16_224,1027.63,372.823,384,224,22.05
regnety_004,1027.25,497.255,512,224,4.34
tf_efficientnet_b1_ns,1026.16,247.955,256,240,7.79
tf_efficientnet_b1_ap,1026.11,248.006,256,240,7.79
tf_efficientnet_b1,1025.11,248.193,256,240,7.79
resnet32ts,1021.77,249.96,256,256,17.96
deit_small_distilled_patch16_224,1010.79,379.058,384,224,22.44
resnet33ts,1009.39,252.998,256,256,19.68
res2net50_48w_2s,1006.25,380.82,384,224,25.29
vovnet39a,1004.46,509.092,512,224,22.6
seresnext26d_32x4d,1002.27,382.471,384,224,16.81
seresnext26t_32x4d,1001.74,382.665,384,224,16.81
seresnext26tn_32x4d,1001.47,382.779,384,224,16.81
legacy_seresnet50,993.86,385.256,384,224,28.09
tf_efficientnet_em,979.63,260.356,256,240,6.9
efficientnet_em,978.46,260.687,256,240,6.9
dla46x_c,973.77,525.047,512,224,1.07
eca_resnet33ts,964.39,264.788,256,256,19.68
pit_s_224,961.0,265.507,256,224,23.46
pit_s_distilled_224,960.14,265.718,256,224,24.04
tf_mixnet_s,958.59,532.877,512,224,4.13
seresnet50,956.87,400.165,384,224,28.09
efficientnet_b1,954.91,266.596,256,256,7.79
seresnet33ts,954.85,267.313,256,256,19.78
ecaresnetlight,952.86,536.422,512,224,30.16
vit_base2_patch32_256,950.48,537.853,512,256,119.46
ese_vovnet39b,947.73,539.578,512,224,24.57
ecaresnext50t_32x4d,947.69,404.65,384,224,15.41
ecaresnext26t_32x4d,947.22,404.844,384,224,15.41
dla60,945.45,405.196,384,224,22.04
gluon_resnet50_v1s,943.31,406.227,384,224,25.68
resnetaa50d,941.94,406.82,384,224,25.58
eca_vovnet39b,939.18,544.514,512,224,22.6
vgg11,930.6,550.023,512,224,132.86
gcresnet33ts,927.58,274.995,256,256,19.88
lambda_resnet26rpt_256,921.55,207.755,192,256,10.99
dla60x_c,921.01,554.951,512,224,1.32
ecaresnet50d_pruned,911.85,560.565,512,224,19.94
resnetblur50,909.58,421.362,384,224,25.56
mobilevit_xs,909.51,210.0,192,256,2.32
cspresnet50,906.79,422.612,384,256,21.62
rexnetr_200,896.75,212.966,192,224,16.52
coat_lite_tiny,890.79,430.193,384,224,5.72
nf_seresnet50,886.81,431.807,384,224,28.09
dpn68b,878.29,436.039,384,224,12.61
selecsls84,872.56,585.545,512,224,50.95
twins_svt_small,868.85,440.366,384,224,24.06
hrnet_w18_small_v2,867.42,587.948,512,224,15.6
seresnet50t,865.51,442.504,384,224,28.1
cspresnext50,862.61,444.309,384,224,20.57
resnetrs50,861.96,444.354,384,224,35.69
cspresnet50w,860.12,445.567,384,256,28.12
cspresnet50d,849.09,451.363,384,256,21.64
densenet121,845.28,301.077,256,224,7.98
tv_densenet121,845.28,301.063,256,224,7.98
rexnet_150,842.23,302.82,256,224,9.73
tv_resnext50_32x4d,836.18,458.41,384,224,25.03
swsl_resnext50_32x4d,836.09,458.464,384,224,25.03
res2net50_26w_4s,835.77,458.208,384,224,25.7
coat_lite_mini,833.77,459.672,384,224,11.01
vit_base_resnet26d_224,833.37,459.491,384,224,101.4
resnext50_32x4d,832.87,460.244,384,224,25.03
ssl_resnext50_32x4d,832.34,460.521,384,224,25.03
dpn68,831.95,460.44,384,224,12.61
gluon_resnext50_32x4d,831.77,460.799,384,224,25.03
vovnet57a,828.64,616.994,512,224,36.64
efficientnet_b2_pruned,825.77,308.457,256,260,8.31
resnetblur50d,818.48,311.928,256,224,25.58
skresnet50,810.12,472.628,384,224,25.8
tf_efficientnet_b2_ap,809.72,235.646,192,260,9.11
tf_efficientnet_b2_ns,809.32,235.717,192,260,9.11
tf_efficientnet_b2,809.06,235.843,192,260,9.11
vgg11_bn,805.38,476.555,384,224,132.87
densenet121d,805.31,316.045,256,224,8.0
nf_ecaresnet50,804.89,476.102,384,224,25.56
rexnet_130,801.42,318.304,256,224,7.56
ecaresnet50d,793.07,483.245,384,224,25.58
ese_vovnet57b,790.94,484.567,384,224,38.61
regnetx_006,790.56,646.782,512,224,6.2
gcresnet50t,788.09,323.372,256,256,25.9
regnety_006,787.76,648.873,512,224,6.06
convnext_tiny,781.17,326.737,256,224,28.59
tf_inception_v3,774.78,494.217,384,299,23.83
gluon_inception_v3,774.48,494.404,384,299,23.83
seresnetaa50d,773.82,329.682,256,224,28.11
inception_v3,772.99,495.38,384,299,23.83
adv_inception_v3,769.85,497.351,384,299,23.83
resmlp_24_distilled_224,767.92,331.893,256,224,30.02
resnext50d_32x4d,765.61,333.516,256,224,25.05
resmlp_24_224,762.25,334.383,256,224,30.02
gmixer_24_224,759.72,335.461,256,224,24.72
resnetv2_101,757.49,336.449,256,224,44.54
res2net50_14w_8s,756.34,336.303,256,224,25.06
xcit_nano_12_p16_384_dist,754.95,337.338,256,384,3.05
sehalonet33ts,749.52,340.746,256,256,13.69
densenetblur121d,739.98,344.167,256,224,8.0
dla60_res2net,736.45,346.205,256,224,20.85
skresnet50d,736.23,346.324,256,224,25.82
mobilevit_s,734.66,260.236,192,256,5.58
gluon_resnet101_v1b,731.02,348.601,256,224,44.55
tv_resnet101,727.65,350.31,256,224,44.55
resnet101,727.5,350.369,256,224,44.55
xcit_tiny_24_p16_224,726.25,349.143,256,224,12.12
xcit_tiny_24_p16_224_dist,725.28,349.489,256,224,12.12
efficientnet_b2,724.21,263.654,192,288,9.11
twins_pcpvt_small,724.17,351.883,256,224,24.11
efficientnet_b2a,723.56,263.856,192,288,9.11
ecaresnet101d_pruned,714.19,715.116,512,224,24.88
nf_resnet50,710.87,539.322,384,288,25.56
nf_resnet101,707.69,540.968,384,224,44.55
seresnext50_32x4d,706.91,361.01,256,224,27.56
gluon_seresnext50_32x4d,706.58,361.114,256,224,27.56
efficientnet_b0_gn,705.84,361.599,256,224,5.29
legacy_seresnext50_32x4d,704.96,362.028,256,224,27.56
nf_regnet_b0,703.19,726.933,512,256,8.76
darknet53,701.97,363.892,256,256,41.61
resnetv2_101d,699.92,364.177,256,224,44.56
densenet169,698.35,364.121,256,224,14.15
gluon_resnet101_v1c,697.85,365.313,256,224,44.57
dla60x,694.54,367.645,256,224,17.35
poolformer_s24,690.11,369.675,256,224,21.39
semobilevit_s,684.71,279.143,192,256,5.74
efficientnetv2_rw_t,684.48,278.424,192,288,13.65
vit_small_r26_s32_224,682.34,373.878,256,224,36.43
convnext_tiny_hnf,681.83,374.501,256,224,28.59
gluon_resnet101_v1d,674.08,378.237,256,224,44.57
tf_efficientnetv2_b3,670.7,284.467,192,300,14.36
xcit_small_12_p16_224,670.22,380.208,256,224,26.25
xcit_small_12_p16_224_dist,669.97,380.26,256,224,26.25
sebotnet33ts_256,666.38,191.3,128,256,13.7
rexnet_200,665.99,287.162,192,224,16.37
vgg13,663.21,578.818,384,224,133.05
regnety_008,661.82,772.637,512,224,6.26
wide_resnet50_2,661.04,580.088,384,224,68.88
dla102,650.38,392.047,256,224,33.27
gmlp_s16_224,648.9,294.316,192,224,19.42
vit_base_resnet50d_224,646.39,394.444,256,224,110.97
swin_tiny_patch4_window7_224,639.35,399.428,256,224,28.29
ecaresnet26t,628.75,406.586,256,320,16.01
repvgg_b1,627.31,815.089,512,224,57.42
gluon_resnet101_v1s,624.3,408.497,256,224,44.67
crossvit_small_240,624.04,408.587,256,240,26.86
resnetaa101d,621.23,410.532,256,224,44.57
eca_botnext26ts_256,618.03,413.613,256,256,10.59
resnext26ts,615.62,623.252,384,256,10.3
gc_efficientnetv2_rw_t,605.04,314.593,192,288,13.68
eca_halonext26ts,604.41,422.932,256,256,10.76
seresnext26ts,598.53,427.051,256,256,10.39
eca_resnext26ts,598.25,427.346,256,256,10.3
convnext_tiny_hnfd,592.58,430.992,256,224,28.63
regnetx_008,591.8,864.35,512,224,7.26
resnetv2_50x1_bit_distilled,589.64,324.794,192,224,25.55
legacy_seresnet101,588.41,432.899,256,224,49.33
gcresnext26ts,585.17,436.656,256,256,10.48
halonet50ts,584.39,327.573,192,256,22.73
xcit_nano_12_p8_224,583.42,437.05,256,224,3.05
cait_xxs24_224,582.93,436.673,256,224,11.96
xcit_nano_12_p8_224_dist,581.01,438.848,256,224,3.05
mixer_b16_224,580.44,440.268,256,224,59.88
mixer_b16_224_miil,579.94,440.653,256,224,59.88
swin_s3_tiny_224,578.76,441.339,256,224,28.33
seresnet101,574.05,443.691,256,224,49.33
mixnet_m,573.23,891.634,512,224,5.01
res2net50_26w_6s,569.28,447.908,256,224,37.05
vgg13_bn,568.79,449.813,256,224,133.05
crossvit_15_240,568.46,335.957,192,240,27.53
resnetblur101d,567.71,449.352,256,224,44.57
cspdarknet53,565.64,451.547,256,256,27.64
efficientnet_lite3,563.01,226.244,128,300,8.2
tf_efficientnet_lite3,561.05,227.067,128,300,8.2
crossvit_15_dagger_240,549.96,347.22,192,240,28.21
resnext101_32x4d,548.6,465.031,256,224,44.18
tf_mixnet_m,547.03,700.438,384,224,5.01
swsl_resnext101_32x4d,546.13,467.192,256,224,44.18
gluon_resnext101_32x4d,545.31,467.899,256,224,44.18
ssl_resnext101_32x4d,545.31,467.944,256,224,44.18
densenet201,539.32,353.029,192,224,20.01
vgg16,536.49,715.548,384,224,138.36
bat_resnext26ts,533.44,478.688,256,256,10.73
nf_seresnet101,532.2,478.733,256,224,49.33
vit_base_r26_s32_224,528.57,361.981,192,224,101.38
resnetv2_152,524.49,485.916,256,224,60.19
botnet50ts_256,524.41,243.109,128,256,22.74
res2net101_26w_4s,523.46,486.536,256,224,45.21
efficientnet_b3_pruned,519.43,491.117,256,300,9.86
vit_base_patch32_384,517.32,494.013,256,384,88.3
vit_large_patch32_224,511.41,498.976,256,224,306.54
halo2botnet50ts_256,510.64,375.017,192,256,22.64
mixer_l32_224,510.1,374.908,192,224,206.94
swin_v2_cr_tiny_224,506.89,377.55,192,224,28.33
resmlp_36_distilled_224,505.72,377.435,192,224,44.69
resmlp_36_224,505.39,377.735,192,224,44.69
vit_tiny_patch16_384,503.94,253.174,128,384,5.79
res2next50,502.84,507.818,256,224,24.67
dla102x,501.98,380.938,192,224,26.31
swin_v2_cr_tiny_ns_224,501.36,381.688,192,224,28.33
resnet152,499.83,381.783,192,224,60.19
gluon_resnet152_v1b,499.79,381.933,192,224,60.19
tv_resnet152,496.47,384.401,192,224,60.19
xception,494.06,258.29,128,299,22.86
visformer_tiny,491.83,1040.332,512,224,10.32
mixnet_l,488.23,784.993,384,224,7.33
gluon_resnet152_v1c,485.58,393.139,192,224,60.21
resnet50_gn,484.73,395.256,192,224,25.56
resnetv2_152d,484.59,393.938,192,224,60.2
twins_pcpvt_base,480.18,397.102,192,224,43.83
nest_tiny,477.31,267.267,128,224,17.06
res2net50_26w_8s,476.93,534.581,256,224,48.4
ecaresnet101d,475.58,536.508,256,224,44.57
convnext_small,473.89,403.445,192,224,50.22
gluon_resnet152_v1d,473.52,403.216,192,224,60.21
tf_mixnet_l,470.86,542.123,256,224,7.33
jx_nest_tiny,470.71,271.015,128,224,17.06
vgg16_bn,469.97,544.386,256,224,138.37
nf_ecaresnet101,465.87,547.628,256,224,44.55
coat_lite_small,463.34,412.922,192,224,19.84
poolformer_s36,458.24,417.134,192,224,30.86
efficientnet_el,455.42,279.993,128,300,10.59
efficientnet_el_pruned,454.32,280.643,128,300,10.59
vgg19,451.86,849.574,384,224,143.67
convit_small,450.19,425.458,192,224,27.78
fbnetv3_g,449.02,283.045,128,288,16.62
ese_vovnet99b,448.97,568.658,256,224,63.2
seresnext101_32x4d,448.16,426.163,192,224,48.96
gluon_seresnext101_32x4d,447.49,426.94,192,224,48.96
gluon_resnet152_v1s,446.73,427.49,192,224,60.32
legacy_seresnext101_32x4d,446.01,428.263,192,224,48.96
nf_regnet_b3,442.03,577.378,256,320,18.59
tf_efficientnet_el,441.61,288.785,128,300,10.59
ese_vovnet39b_evos,439.23,290.493,128,224,24.58
dla60_res2next,437.89,583.208,256,224,17.03
volo_d1_224,437.25,437.756,192,224,26.63
dla169,436.98,436.866,192,224,53.39
skresnext50_32x4d,435.09,586.972,256,224,27.48
hrnet_w32,433.46,438.263,192,224,41.23
vit_small_resnet50d_s16_224,432.94,442.239,192,224,57.53
twins_svt_base,429.83,444.617,192,224,56.07
hrnet_w18,419.32,605.846,256,224,21.3
crossvit_18_240,400.15,317.858,128,240,43.27
vgg19_bn,399.74,640.035,256,224,143.68
ecaresnet50t,399.44,319.549,128,320,25.57
inception_v4,397.78,480.469,192,299,42.68
tf_efficientnet_b3,393.44,323.695,128,300,12.23
swin_small_patch4_window7_224,393.38,486.272,192,224,49.61
legacy_seresnet152,392.87,485.406,192,224,66.82
tf_efficientnet_b3_ap,392.08,324.783,128,300,12.23
vit_base_patch16_224_miil,391.87,489.169,192,224,86.54
tf_efficientnet_b3_ns,391.61,325.176,128,300,12.23
crossvit_18_dagger_240,387.95,327.891,128,240,44.27
vit_base_patch16_224,385.23,497.575,192,224,86.57
vit_base_patch16_224_sam,384.98,497.891,192,224,86.57
deit_base_patch16_224,384.15,498.956,192,224,86.57
cait_xxs36_224,380.29,501.012,192,224,17.3
repvgg_b2,380.03,1346.183,512,224,89.02
regnetx_016,379.21,1349.264,512,224,9.19
deit_base_distilled_patch16_224,378.28,506.739,192,224,87.34
densenet161,376.13,337.907,128,224,28.68
haloregnetz_b,375.52,680.247,256,224,11.68
xcit_tiny_12_p8_224,374.86,339.659,128,224,6.71
xcit_tiny_12_p8_224_dist,374.8,339.672,128,224,6.71
seresnet152,372.93,339.954,128,224,66.82
dla102x2,362.92,351.15,128,224,41.28
wide_resnet101_2,360.46,531.121,192,224,126.89
gluon_resnext101_64x4d,357.83,356.147,128,224,83.46
efficientnet_b3a,354.6,359.335,128,320,12.23
resnet200,354.57,357.998,128,224,64.67
xception41p,353.88,360.846,128,299,26.91
regnety_016,353.36,1447.082,512,224,11.2
efficientnet_b3,353.18,360.796,128,320,12.23
beit_base_patch16_224,352.29,543.93,192,224,86.53
resnest14d,349.84,1463.045,512,224,10.61
hrnet_w30,346.82,733.381,256,224,37.71
ens_adv_inception_resnet_v2,341.5,558.819,192,299,55.84
inception_resnet_v2,341.03,559.722,192,299,55.84
xcit_small_24_p16_224_dist,341.01,371.894,128,224,47.67
tnt_s_patch16_224,340.3,562.32,192,224,23.76
xcit_small_24_p16_224,339.02,373.952,128,224,47.67
efficientnet_lite4,334.87,189.779,64,380,13.01
dpn92,332.25,769.002,256,224,37.67
nf_regnet_b1,330.04,1549.911,512,288,10.22
twins_pcpvt_large,327.73,386.698,128,224,60.99
resnet101d,327.41,389.353,128,320,44.57
convnext_small_in22ft1k,327.31,389.301,128,224,88.59
convnext_base,327.3,389.374,128,224,88.59
convnext_base_in22ft1k,326.61,390.177,128,224,88.59
convnext_tiny_in22ft1k,324.94,392.181,128,224,88.59
tf_efficientnet_lite4,322.62,197.041,64,380,13.01
resnetrs101,321.74,395.61,128,288,63.62
pit_b_224,318.92,400.391,128,224,73.76
pit_b_distilled_224,318.09,401.455,128,224,74.79
gcresnext50ts,316.73,604.706,192,256,15.67
repvgg_b3,315.56,1215.795,384,224,123.09
gluon_seresnext101_64x4d,313.23,406.424,128,224,88.23
regnetz_d8,311.3,204.013,64,320,23.37
poolformer_m36,307.82,413.95,128,224,56.17
xception41,305.16,418.228,128,299,26.97
resnetv2_50d_gn,304.62,419.347,128,288,25.57
coat_tiny,304.05,418.955,128,224,5.5
vit_small_patch16_36x1_224,302.22,420.928,128,224,64.67
swin_v2_cr_small_224,302.05,421.43,128,224,49.7
cait_s24_224,301.09,422.497,128,224,46.92
mixnet_xl,300.81,849.169,256,224,11.9
vit_small_patch16_18x2_224,299.9,424.102,128,224,64.67
resnetv2_50d_frn,299.64,426.047,128,224,25.59
efficientnetv2_s,299.05,318.819,96,384,21.46
twins_svt_large,298.59,426.599,128,224,99.27
tf_efficientnetv2_s,297.45,320.544,96,384,21.46
tf_efficientnetv2_s_in21ft1k,295.84,322.238,96,384,21.46
efficientnetv2_rw_s,295.58,214.343,64,384,23.94
nest_small,295.19,323.571,96,224,38.35
jx_nest_small,293.04,325.974,96,224,38.35
hrnet_w40,291.68,653.529,192,224,57.56
regnetz_005,286.8,1783.819,512,224,7.12
nf_regnet_b2,284.19,1799.964,512,272,14.31
dpn98,283.21,450.397,128,224,61.57
gluon_xception65,280.82,339.911,96,299,39.92
xception65,279.18,341.922,96,299,39.92
resnet51q,277.93,689.969,192,288,35.7
nf_regnet_b4,277.28,459.47,128,384,30.21
swin_s3_small_224,277.05,344.678,96,224,49.74
swin_base_patch4_window7_224,275.83,462.244,128,224,87.77
xception65p,274.95,464.241,128,299,39.82
gmlp_b16_224,270.89,352.851,96,224,73.08
hrnet_w48,266.5,475.648,128,224,77.47
resnest26d,258.35,1485.604,384,224,17.07
resnest50d_1s4x24d,258.11,990.508,256,224,25.68
xcit_tiny_24_p16_384_dist,251.56,378.207,96,384,12.12
regnetz_c16,250.16,510.248,128,320,13.46
crossvit_base_240,249.99,382.366,96,240,105.03
coat_mini,247.34,515.482,128,224,10.34
xcit_medium_24_p16_224,244.65,519.851,128,224,84.4
xcit_medium_24_p16_224_dist,244.08,521.069,128,224,84.4
hrnet_w44,241.77,789.352,192,224,67.06
efficientnet_b4,241.47,262.953,64,384,19.34
volo_d2_224,238.72,400.292,96,224,58.68
tf_efficientnet_b4,236.52,268.528,64,380,19.34
tf_efficientnet_b4_ap,236.39,268.69,64,380,19.34
tf_efficientnet_b4_ns,236.1,269.028,64,380,19.34
vit_small_patch16_384,235.52,270.897,64,384,22.2
resnetv2_50d_evob,235.19,406.951,96,224,25.59
tresnet_m,234.84,2177.505,512,224,31.39
nfnet_l0,233.22,1096.449,256,288,35.07
visformer_small,232.72,1649.37,384,224,40.22
xcit_small_12_p16_384_dist,230.87,414.048,96,384,26.25
vit_large_r50_s32_224,228.88,417.083,96,224,328.99
convit_base,228.65,558.76,128,224,86.54
eca_nfnet_l0,226.92,1127.142,256,288,24.14
resnetv2_50d_evos,223.6,285.051,64,288,25.59
tnt_b_patch16_224,222.54,573.324,128,224,65.41
vit_small_r26_s32_384,221.41,287.746,64,384,36.47
densenet264,220.0,432.388,96,224,72.69
swin_s3_base_224,219.07,435.557,96,224,71.13
hrnet_w64,218.91,579.973,128,224,128.06
resnext101_64x4d,217.22,440.378,96,288,83.46
resnet152d,216.09,441.927,96,320,60.21
xception71,215.62,294.681,64,299,42.34
swin_v2_cr_base_224,215.23,443.662,96,224,87.88
dpn131,211.54,603.038,128,224,79.25
nest_base,210.35,302.564,64,224,67.72
vit_base_r50_s16_224,208.87,457.959,96,224,98.66
jx_nest_base,208.37,305.48,64,224,67.72
resnet61q,207.91,614.63,128,288,36.85
mixnet_xxl,202.79,629.315,128,224,23.96
xcit_nano_12_p8_384_dist,196.18,324.445,64,384,3.05
poolformer_m48,193.91,492.638,96,224,73.47
xcit_tiny_24_p8_224,190.8,499.85,96,224,12.11
xcit_tiny_24_p8_224_dist,190.62,500.3,96,224,12.11
seresnet200d,190.31,500.165,96,256,71.86
ecaresnet200d,182.23,523.49,96,256,64.69
regnetz_b16,181.6,1055.83,192,288,9.72
convnext_large_in22ft1k,180.86,529.028,96,224,197.77
convnext_large,180.64,529.707,96,224,197.77
convmixer_768_32,179.25,534.249,96,224,21.11
repvgg_b1g4,178.41,2868.637,512,224,39.97
regnety_032,178.01,1436.656,256,288,19.44
regnetx_032,177.68,2160.015,384,224,15.3
resnest50d,177.64,1439.786,256,224,27.48
gluon_senet154,177.29,538.24,96,224,115.09
senet154,176.81,539.67,96,224,115.09
halonet_h1,175.85,362.526,64,256,8.1
legacy_senet154,175.45,543.752,96,224,115.09
xcit_small_12_p8_224,174.99,363.954,64,224,26.21
xcit_small_12_p8_224_dist,174.85,364.256,64,224,26.21
seresnet152d,173.74,364.967,64,320,66.84
dpn107,173.23,552.482,96,224,86.92
mixer_l16_224,172.58,554.751,96,224,208.2
resnetrs152,171.14,370.433,64,320,86.62
resnest50d_4s2x40d,167.22,1529.64,256,224,30.42
resnet200d,166.19,382.131,64,320,64.69
volo_d3_224,162.25,391.709,64,224,86.33
regnetx_040,161.87,2371.182,384,224,22.12
vit_large_patch32_384,161.83,591.666,96,384,306.63
efficientnet_b3_gn,160.22,397.781,64,320,11.73
swin_large_patch4_window7_224,151.35,420.987,64,224,196.53
regnetx_080,150.02,2558.515,384,224,39.57
regnety_040s_gn,149.61,853.983,128,224,20.65
efficientnetv2_m,149.31,318.263,48,416,54.14
ssl_resnext101_32x8d,147.46,866.477,128,224,88.79
resnext101_32x8d,147.32,867.312,128,224,88.79
swsl_resnext101_32x8d,147.16,868.264,128,224,88.79
ig_resnext101_32x8d,146.91,869.691,128,224,88.79
regnetz_e8,146.27,326.163,48,320,57.7
resnetv2_50x1_bitm,140.77,340.162,48,448,25.55
seresnet269d,137.16,460.633,64,256,113.67
xcit_large_24_p16_224,136.77,464.553,64,224,189.1
xcit_large_24_p16_224_dist,136.73,464.738,64,224,189.1
xcit_tiny_12_p8_384_dist,128.06,373.098,48,384,6.71
efficientnetv2_rw_m,126.21,250.013,32,416,53.24
regnetx_064,124.13,2061.422,256,224,26.21
resnetrs200,123.75,383.587,48,320,93.21
dm_nfnet_f0,121.58,2104.417,256,256,71.49
swin_v2_cr_large_224,120.98,394.327,48,224,196.68
regnety_040,120.25,1595.17,192,288,20.65
nfnet_f0,119.63,2138.729,256,256,71.49
regnetv_040,118.92,1074.873,128,288,20.64
ese_vovnet99b_iabn,118.27,3243.951,384,224,63.2
xcit_small_24_p16_384_dist,117.41,405.393,48,384,47.67
regnetz_b16_evos,117.22,544.08,64,288,9.74
crossvit_15_dagger_408,116.43,273.026,32,408,28.5
efficientnet_b0_g8_gn,115.43,2216.717,256,224,6.56
vit_large_patch16_224,115.39,553.095,64,224,304.33
regnetz_c16_evos,115.15,414.978,48,320,13.49
vit_base_patch16_18x2_224,114.12,558.126,64,224,256.73
convnext_xlarge_in22ft1k,114.03,559.475,64,224,350.2
convnext_tiny_384_in22ft1k,112.53,424.859,48,384,88.59
convnext_small_384_in22ft1k,112.49,424.983,48,384,88.59
convnext_base_384_in22ft1k,112.43,425.187,48,384,88.59
swin_v2_cr_tiny_384,111.07,286.85,32,384,28.33
tf_efficientnetv2_m,109.5,289.071,32,480,54.14
tf_efficientnetv2_m_in21ft1k,109.37,289.435,32,480,54.14
beit_large_patch16_224,106.59,598.365,64,224,304.43
volo_d1_384,104.96,303.527,32,384,26.78
tresnet_l,104.79,4882.686,512,224,55.99
repvgg_b2g4,102.33,5002.104,512,224,61.76
eca_nfnet_l1,101.26,1262.246,128,320,41.41
volo_d4_224,101.17,471.916,48,224,192.96
cspdarknet53_iabn,98.65,3890.155,384,256,27.64
cait_xxs24_384,98.52,484.701,48,384,12.03
efficientnet_b5,97.28,326.485,32,456,30.39
tf_efficientnet_b5,95.75,331.792,32,456,30.39
tf_efficientnet_b5_ns,95.73,331.833,32,456,30.39
vit_base_patch16_384,95.69,333.568,32,384,86.86
deit_base_patch16_384,95.67,333.658,32,384,86.86
regnetz_d8_evos,95.66,332.456,32,320,23.46
tf_efficientnet_b5_ap,95.45,332.725,32,456,30.39
regnetz_040,94.56,674.98,64,320,27.12
regnetz_040h,94.14,678.01,64,320,28.94
deit_base_distilled_patch16_384,93.65,340.87,32,384,87.63
tresnet_xl,90.76,4227.401,384,224,78.44
cspresnext50_iabn,89.98,4265.102,384,256,20.57
resnest101e,89.71,1424.366,128,256,48.28
crossvit_18_dagger_408,87.99,361.633,32,408,44.61
xcit_small_24_p8_224,87.73,361.414,32,224,47.63
xcit_small_24_p8_224_dist,87.7,361.441,32,224,47.63
resnetv2_101x1_bitm,86.89,366.637,32,448,44.54
nf_regnet_b5,86.53,736.892,64,456,49.74
resnetv2_152x2_bit_teacher,86.4,368.012,32,224,236.34
repvgg_b3g4,84.75,4530.071,384,224,83.83
vit_large_patch14_224,84.3,567.814,48,224,304.2
beit_base_patch16_384,82.73,385.724,32,384,86.74
seresnext101_32x8d,81.65,781.61,64,288,93.57
xcit_medium_24_p16_384_dist,81.08,391.168,32,384,84.4
ecaresnet269d,77.88,406.425,32,352,102.09
regnetx_120,77.54,3300.773,256,224,46.11
pnasnet5large,76.44,414.721,32,331,86.06
vit_large_r50_s32_384,75.76,419.984,32,384,329.09
regnety_120,75.34,2547.007,192,224,51.82
resnetrs270,75.27,419.128,32,352,129.86
swin_base_patch4_window12_384,73.61,432.836,32,384,87.9
regnety_064,72.69,1759.173,128,288,30.58
regnetz_d32,72.18,885.049,64,320,27.58
regnetv_064,71.81,1780.738,128,288,30.58
resmlp_big_24_224,68.34,466.717,32,224,129.14
resmlp_big_24_224_in22ft1k,68.31,466.955,32,224,129.14
resmlp_big_24_distilled_224,68.26,467.278,32,224,129.14
regnety_320,67.49,1895.092,128,224,145.05
nasnetalarge,66.93,473.19,32,331,88.75
swin_v2_cr_small_384,66.26,359.874,24,384,49.7
cait_xs24_384,65.98,482.447,32,384,26.67
regnety_080,65.45,1954.421,128,288,39.18
regnetx_160,65.01,2952.336,192,224,54.28
xcit_tiny_24_p8_384_dist,64.61,492.002,32,384,12.11
volo_d5_224,64.26,494.733,32,224,295.46
cait_xxs36_384,63.75,498.023,32,384,17.37
vit_base_patch8_224,62.96,380.293,24,224,86.58
xcit_medium_24_p8_224,62.71,506.97,32,224,84.32
xcit_medium_24_p8_224_dist,62.63,507.407,32,224,84.32
efficientnet_b3_g8_gn,62.43,1023.448,64,320,14.25
convnext_large_384_in22ft1k,61.7,516.836,32,384,197.77
convmixer_1024_20_ks9_p14,61.37,4170.722,256,224,24.38
efficientnet_b0_g16_evos,60.46,6350.16,384,224,8.11
tf_efficientnetv2_l_in21ft1k,60.25,261.19,16,480,118.52
xcit_small_12_p8_384_dist,60.04,398.02,24,384,26.21
efficientnetv2_l,59.19,265.957,16,480,118.52
vit_base_resnet50_384,59.0,405.136,24,384,98.95
tf_efficientnetv2_l,58.87,267.382,16,480,118.52
vit_base_r50_s16_384,58.85,406.196,24,384,98.95
volo_d2_384,58.21,273.125,16,384,58.87
tresnet_m_448,53.55,3582.526,192,448,31.39
cait_s24_384,49.8,479.385,24,384,47.06
regnety_160,48.14,1993.0,96,288,83.59
ig_resnext101_32x16d,47.52,2018.737,96,224,194.03
swsl_resnext101_32x16d,47.43,2022.391,96,224,194.03
xcit_large_24_p16_384_dist,47.39,502.961,24,384,189.1
ssl_resnext101_32x16d,47.29,2028.601,96,224,194.03
resnetrs350,47.22,500.442,24,384,163.96
swin_v2_cr_base_384,47.19,336.677,16,384,87.88
swin_v2_cr_huge_224,46.26,343.404,16,224,657.83
regnetx_320,46.16,2771.769,128,224,107.81
eca_nfnet_l2,44.82,1425.204,64,384,56.72
efficientnet_b6,42.73,371.597,16,528,43.04
tf_efficientnet_b6,41.54,382.29,16,528,43.04
tf_efficientnet_b6_ns,41.5,382.621,16,528,43.04
tf_efficientnet_b6_ap,41.36,384.088,16,528,43.04
swin_large_patch4_window12_384,41.02,388.265,16,384,196.74
nfnet_f1,40.44,2371.478,96,320,132.63
vit_huge_patch14_224,39.64,401.543,16,224,632.05
dm_nfnet_f1,38.26,1670.645,64,320,132.63
convnext_xlarge_384_in22ft1k,37.04,430.195,16,384,350.2
efficientnet_b7,36.68,214.625,8,600,66.35
efficientnetv2_xl,36.54,322.755,12,512,208.12
tf_efficientnetv2_xl_in21ft1k,36.36,324.371,12,512,208.12
tf_efficientnet_b7_ap,36.21,217.402,8,600,66.35
tf_efficientnet_b7,36.05,218.422,8,600,66.35
tf_efficientnet_b7_ns,35.41,221.975,8,600,66.35
xcit_large_24_p8_224,34.96,454.269,16,224,188.93
xcit_large_24_p8_224_dist,34.92,454.696,16,224,188.93
resnetrs420,32.2,487.619,16,416,191.89
cait_s36_384,32.09,494.814,16,384,68.37
resnest200e,32.0,1494.763,48,320,70.2
densenet264d_iabn,31.93,4003.992,128,224,72.74
resnetv2_50x3_bitm,31.81,502.194,16,448,217.32
xcit_small_24_p8_384_dist,29.97,396.971,12,384,47.63
resnetv2_152x2_bit_teacher_384,29.92,398.698,12,384,236.34
vit_large_patch16_384,28.85,414.372,12,384,304.72
swin_v2_cr_large_384,28.47,419.18,12,384,196.68
tresnet_l_448,25.64,4988.984,128,448,55.99
beit_large_patch16_384,25.11,475.839,12,384,305.0
volo_d3_448,24.79,320.233,8,448,86.63
eca_nfnet_l3,24.19,1319.468,32,448,72.04
tresnet_xl_448,23.17,4140.191,96,448,78.44
nfnet_f2,22.36,2143.929,48,352,193.78
vit_giant_patch14_224,22.25,356.944,8,224,1012.61
dm_nfnet_f2,22.12,2166.49,48,352,193.78
efficientnet_cc_b0_8e,21.78,44.083,1,224,24.01
resnetv2_152x2_bitm,21.74,365.619,8,448,236.34
tf_efficientnet_cc_b0_4e,21.44,44.859,1,224,13.31
tf_efficientnet_cc_b0_8e,20.98,45.875,1,224,24.01
xcit_medium_24_p8_384_dist,20.42,388.21,8,384,84.32
efficientnet_cc_b0_4e,20.36,47.276,1,224,13.31
ig_resnext101_32x32d,18.17,1760.063,32,224,468.53
volo_d4_448,17.6,338.311,6,448,193.41
resnetv2_101x3_bitm,17.53,454.801,8,448,387.93
tf_efficientnet_cc_b1_8e,17.15,56.006,1,240,39.72
efficientnet_cc_b1_8e,16.21,59.398,1,240,39.72
resnest269e,13.09,1826.778,24,416,110.93
tf_efficientnet_b8_ap,12.18,488.771,6,672,87.41
efficientnet_b8,12.12,491.31,6,672,87.41
nfnet_f3,12.08,1982.52,24,416,254.92
xcit_large_24_p8_384_dist,11.91,500.622,6,384,188.93
tf_efficientnet_b8,11.9,500.516,6,672,87.41
cait_m36_384,11.87,501.638,6,384,271.22
dm_nfnet_f3,11.74,2040.434,24,416,254.92
volo_d5_448,11.52,343.952,4,448,295.91
swin_v2_cr_huge_384,10.9,364.423,4,384,657.94
convmixer_1536_20,9.63,4981.706,48,224,51.63
beit_large_patch16_512,9.42,422.773,4,512,305.67
tf_efficientnet_l2_ns_475,9.0,327.787,3,475,480.31
ig_resnext101_32x48d,8.5,1880.808,16,224,828.41
volo_d5_512,8.05,369.448,3,512,296.09
nfnet_f4,6.47,1849.874,12,512,316.07
dm_nfnet_f4,6.2,1929.065,12,512,316.07
cait_m48_448,4.75,415.897,2,448,356.46
nfnet_f5,4.63,1719.792,8,544,377.21
resnetv2_152x4_bitm,4.49,443.185,2,480,936.53
dm_nfnet_f5,4.47,1782.137,8,544,377.21
nfnet_f6,3.5,1707.387,6,576,438.36
dm_nfnet_f6,3.39,1759.608,6,576,438.36
nfnet_f7,2.67,1489.771,4,608,499.5
efficientnet_l2,2.09,473.733,1,800,480.31
tf_efficientnet_l2_ns,2.09,474.031,1,800,480.31