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Index for timm models of different size levels

1089 models in total.

For each level, only the top-30 most popular pretrained weight of each architecture will be listed here.

0 - nano

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
test_efficientnet.r160_in1k test_efficientnet 358.7K 160 46.42% 70.96% 1000 256 1259 0
test_byobnet.r160_in1k test_byobnet 459.2K 160 45.40% 70.61% 1000 256 926 1
test_vit.r160_in1k test_vit 371.2K 160 40.83% 67.21% 1000 64 896 0

1 - tiny

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
mobilevitv2_075.cvnets_in1k mobilevitv2_075 2.9M 256 75.60% 92.75% 1000 384 6112 0
mobilevit_xs.cvnets_in1k mobilevit_xs 2.3M 256 74.63% 92.35% 1000 384 3136 0
edgenext_x_small.in1k edgenext_x_small 2.3M 256 74.88% 92.30% 1000 192 260 1
semnasnet_075.rmsp_in1k semnasnet_075 2.9M 224 73.01% 91.13% 1000 1280 382 0
lcnet_100.ra2_in1k lcnet_100 3.0M 224 72.13% 90.37% 1000 1280 653 0
edgenext_xx_small.in1k edgenext_xx_small 1.3M 256 71.12% 90.04% 1000 168 956 2
mobilevitv2_050.cvnets_in1k mobilevitv2_050 1.4M 256 70.16% 89.94% 1000 256 6802 1
tinynet_c.in1k tinynet_c 2.5M 184 71.22% 89.75% 1000 1280 234 0
mobilevit_xxs.cvnets_in1k mobilevit_xxs 1.3M 256 68.93% 88.94% 1000 320 14344 1
regnetx_002.pycls_in1k regnetx_002 2.7M 224 68.76% 88.56% 1000 368 3318 0
dla60x_c.in1k dla60x_c 1.3M 224 67.93% 88.43% 1000 256 206 0
lcnet_075.ra2_in1k lcnet_075 2.4M 224 68.78% 88.39% 1000 1280 256 0
repghostnet_058.in1k repghostnet_058 2.6M 224 68.93% 88.39% 1000 1280 99 0
mobilenetv3_small_100.lamb_in1k mobilenetv3_small_100 2.6M 224 67.64% 87.65% 1000 1024 138668605 22
tinynet_d.in1k tinynet_d 2.4M 152 66.97% 87.06% 1000 1280 388 0
dla46x_c.in1k dla46x_c 1.1M 224 66.01% 86.95% 1000 256 328 0
repghostnet_050.in1k repghostnet_050 2.3M 224 66.98% 86.94% 1000 1280 272 0
mnasnet_small.lamb_in1k mnasnet_small 2.0M 224 66.20% 86.47% 1000 1280 299 0
dla46_c.in1k dla46_c 1.3M 224 64.88% 86.33% 1000 256 221 0
mobilenetv2_050.lamb_in1k mobilenetv2_050 2.0M 224 65.93% 86.10% 1000 1280 4719 2
mobilenetv3_small_075.lamb_in1k mobilenetv3_small_075 2.1M 224 65.27% 85.47% 1000 1024 6796 1
efficientvit_m0.r224_in1k efficientvit_m0 2.4M 224 63.29% 85.15% 1000 192 515 0
lcnet_050.ra2_in1k lcnet_050 1.9M 224 63.13% 84.40% 1000 1280 20053 0
tinynet_e.in1k tinynet_e 2.1M 106 59.87% 81.77% 1000 1280 464245 0
mobilenetv3_small_050.lamb_in1k mobilenetv3_small_050 1.6M 224 57.92% 80.14% 1000 1024 7996 0

2 - small

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
mobilevitv2_100.cvnets_in1k mobilevitv2_100 4.9M 256 78.09% 94.17% 1000 512 2157 1
xcit_nano_12_p8_384.fb_dist_in1k xcit_nano_12_p8_384 3.1M 384 77.82% 94.03% 1000 128 177 0
rexnet_100.nav_in1k rexnet_100 4.8M 224 77.85% 93.88% 1000 1280 19859 0
fastvit_t8.apple_dist_in1k fastvit_t8 4.1M 256 77.17% 93.27% 1000 768 37412 0
xcit_nano_12_p8_224.fb_dist_in1k xcit_nano_12_p8_224 3.1M 224 76.33% 93.07% 1000 128 132 1
convnextv2_atto.fcmae_ft_in1k convnextv2_atto 3.7M 224 76.65% 93.04% 1000 320 7155 0
convnext_atto.d2_in1k convnext_atto 3.7M 224 75.67% 92.91% 1000 320 8260 0
efficientformerv2_s0.snap_dist_in1k efficientformerv2_s0 3.6M 224 76.12% 92.85% 1000 176 749 1
convnext_atto_ols.a2_in1k convnext_atto_ols 3.7M 224 75.90% 92.84% 1000 320 10217 0
mixnet_s.ft_in1k mixnet_s 4.2M 224 76.00% 92.80% 1000 1536 3343 0
mobileone_s1.apple_in1k mobileone_s1 4.9M 224 75.77% 92.79% 1000 1280 573 0
regnety_004.tv2_in1k regnety_004 4.4M 224 75.59% 92.70% 1000 440 413 0
xcit_nano_12_p16_384.fb_dist_in1k xcit_nano_12_p16_384 3.1M 384 75.47% 92.67% 1000 128 271 0
semnasnet_100.rmsp_in1k semnasnet_100 3.9M 224 75.46% 92.61% 1000 1280 303 0
efficientnet_lite0.ra_in1k efficientnet_lite0 4.7M 224 75.49% 92.51% 1000 1280 12932 0
mobilenetv1_100.ra4_e3600_r224_in1k mobilenetv1_100 4.3M 224 75.38% 92.31% 1000 1024 1602 2
tinynet_b.in1k tinynet_b 3.8M 188 74.97% 92.20% 1000 1280 333 0
mobilenetv2_110d.ra_in1k mobilenetv2_110d 4.6M 224 75.05% 92.19% 1000 1280 628 0
repghostnet_111.in1k repghostnet_111 4.6M 224 75.07% 92.18% 1000 1280 105 0
mnasnet_100.rmsp_in1k mnasnet_100 4.4M 224 74.66% 92.11% 1000 1280 23684 0
spnasnet_100.rmsp_in1k spnasnet_100 4.5M 224 74.08% 91.83% 1000 1280 19260 0
repghostnet_100.in1k repghostnet_100 4.1M 224 74.20% 91.55% 1000 1280 178 0
mobilenetv4_conv_small.e2400_r224_in1k mobilenetv4_conv_small 3.8M 224 73.73% 91.43% 1000 960 6077 9
pit_ti_224.in1k pit_ti_224 4.8M 224 72.92% 91.41% 1000 256 530 0
mobilenetv2_100.ra_in1k mobilenetv2_100 3.5M 224 72.94% 91.00% 1000 1280 49189 4
xcit_nano_12_p16_224.fb_dist_in1k xcit_nano_12_p16_224 3.1M 224 72.32% 90.83% 1000 128 129 0
repghostnet_080.in1k repghostnet_080 3.3M 224 72.24% 90.49% 1000 1280 313 0
pvt_v2_b0.in1k pvt_v2_b0 3.7M 224 70.66% 90.21% 1000 256 3454 1
efficientvit_m2.r224_in1k efficientvit_m2 4.2M 224 70.80% 90.16% 1000 224 270 0
regnety_002.pycls_in1k regnety_002 3.2M 224 70.29% 89.53% 1000 368 23390 1

3 - compact

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
xcit_tiny_12_p8_384.fb_dist_in1k xcit_tiny_12_p8_384 6.7M 384 82.39% 96.21% 1000 192 337 0
tiny_vit_5m_224.dist_in22k_ft_in1k tiny_vit_5m_224 5.4M 224 80.86% 95.67% 1000 320 2878 1
xcit_tiny_12_p8_224.fb_dist_in1k xcit_tiny_12_p8_224 6.7M 224 81.21% 95.62% 1000 192 104 0
repvit_m1_1.dist_450e_in1k repvit_m1_1 8.9M 224 81.30% 95.57% 1000 512 92 0
eva02_tiny_patch14_336.mim_in22k_ft_in1k eva02_tiny_patch14_336 5.8M 336 80.67% 95.53% 1000 192 1100 2
xcit_tiny_12_p16_384.fb_dist_in1k xcit_tiny_12_p16_384 6.7M 384 80.95% 95.43% 1000 192 190 0
edgenext_small.usi_in1k edgenext_small 5.6M 256 81.06% 95.33% 1000 304 511092 4
fastvit_s12.apple_dist_in1k fastvit_s12 9.5M 256 81.07% 95.28% 1000 1024 107 2
efficientnet_b3_pruned.in1k efficientnet_b3_pruned 9.9M 300 80.87% 95.27% 1000 1536 178 0
maxvit_rmlp_pico_rw_256.sw_in1k maxvit_rmlp_pico_rw_256 7.5M 256 80.55% 95.19% 1000 256 198 0
mobilenetv4_conv_medium.e500_r256_in1k mobilenetv4_conv_medium 9.8M 256 79.92% 95.19% 1000 960 3592 1
repvit_m2.dist_in1k repvit_m2 8.9M 224 80.47% 95.17% 1000 512 248 0
rexnet_150.nav_in1k rexnet_150 9.8M 224 80.31% 95.17% 1000 1920 3179 0
efficientnet_b1.ra4_e3600_r240_in1k efficientnet_b1 7.9M 240 80.40% 95.15% 1000 1280 10246 0
convnextv2_pico.fcmae_ft_in1k convnextv2_pico 9.1M 224 80.30% 95.08% 1000 512 5964 0
fastvit_t12.apple_dist_in1k fastvit_t12 7.6M 256 80.36% 95.04% 1000 1024 66 0
mobilenet_edgetpu_v2_m.ra4_e3600_r224_in1k mobilenet_edgetpu_v2_m 8.5M 224 80.13% 95.00% 1000 1344 474 0
regnetz_b16.ra3_in1k regnetz_b16 9.8M 224 79.87% 94.98% 1000 1536 296 1
efficientvit_b1.r288_in1k efficientvit_b1 9.1M 288 80.31% 94.98% 1000 256 809 0
repvit_m1_0.dist_450e_in1k repvit_m1_0 7.4M 224 80.45% 94.92% 1000 448 513 0
mobilenetv4_conv_blur_medium.e500_r224_in1k mobilenetv4_conv_blur_medium 9.8M 224 79.45% 94.92% 1000 960 744 1
mobilevitv2_125.cvnets_in1k mobilevitv2_125 7.5M 256 79.68% 94.84% 1000 640 732 0
efficientnet_b2_pruned.in1k efficientnet_b2_pruned 8.4M 260 79.91% 94.84% 1000 1408 1091 0
efficientnet_em.ra2_in1k efficientnet_em 7.0M 240 79.26% 94.80% 1000 1280 261 0
regnetx_016.tv2_in1k regnetx_016 9.2M 224 79.45% 94.77% 1000 912 787 0
convnext_pico_ols.d1_in1k convnext_pico_ols 9.1M 224 79.54% 94.71% 1000 512 2168 0
efficientformerv2_s1.snap_dist_in1k efficientformerv2_s1 6.3M 224 79.68% 94.69% 1000 224 315 1
rexnet_130.nav_in1k rexnet_130 7.6M 224 79.49% 94.68% 1000 1664 193 0
efficientnet_b2.ra_in1k efficientnet_b2 9.2M 256 79.34% 94.58% 1000 1408 13208 0
convnext_pico.d1_in1k convnext_pico 9.0M 224 79.52% 94.55% 1000 512 7473 0

4 - medium

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
tiny_vit_21m_512.dist_in22k_ft_in1k tiny_vit_21m_512 21.3M 512 86.45% 97.88% 1000 576 3490 2
tiny_vit_21m_384.dist_in22k_ft_in1k tiny_vit_21m_384 21.2M 384 86.09% 97.71% 1000 576 10762 3
eva02_small_patch14_336.mim_in22k_ft_in1k eva02_small_patch14_336 22.1M 336 85.76% 97.61% 1000 384 4963 3
deit3_small_patch16_384.fb_in22k_ft_in1k deit3_small_patch16_384 22.2M 384 84.84% 97.48% 1000 384 3067 0
tiny_vit_21m_224.dist_in22k_ft_in1k tiny_vit_21m_224 21.2M 224 85.09% 97.36% 1000 576 2294 0
vit_small_patch16_384.augreg_in21k_ft_in1k vit_small_patch16_384 22.2M 384 83.80% 97.11% 1000 384 3639 2
vit_little_patch16_reg1_gap_256.sbb_in12k_ft_in1k vit_little_patch16_reg1_gap_256 22.5M 256 83.80% 96.96% 1000 320 134 0
hgnet_small.ssld_in1k hgnet_small 24.4M 224 83.81% 96.87% 1000 1024 234 0
edgenext_base.in21k_ft_in1k edgenext_base 18.5M 256 83.42% 96.80% 1000 584 154 0
hgnetv2_b4.ssld_stage2_ft_in1k hgnetv2_b4 19.8M 224 83.69% 96.79% 1000 2048 5919 0
deit3_small_patch16_224.fb_in22k_ft_in1k deit3_small_patch16_224 22.1M 224 83.08% 96.78% 1000 384 2315 0
regnetz_d8.ra3_in1k regnetz_d8 23.5M 256 83.55% 96.75% 1000 1792 352 1
convnextv2_nano.fcmae_ft_in22k_in1k_384 convnextv2_nano 15.6M 384 83.36% 96.74% 1000 640 2102 0
xcit_tiny_24_p8_384.fb_dist_in1k xcit_tiny_24_p8_384 12.1M 384 83.78% 96.72% 1000 192 221 0
regnetz_d8_evos.ch_in1k regnetz_d8_evos 23.5M 256 83.39% 96.66% 1000 1792 199 1
repvit_m2_3.dist_450e_in1k repvit_m2_3 23.8M 224 83.74% 96.64% 1000 640 126 0
tiny_vit_11m_224.dist_in22k_ft_in1k tiny_vit_11m_224 11.0M 224 83.23% 96.63% 1000 448 490 0
fastvit_sa24.apple_dist_in1k fastvit_sa24 21.6M 256 83.36% 96.58% 1000 1024 1143 0
mobilevitv2_200.cvnets_in22k_ft_in1k_384 mobilevitv2_200 18.5M 384 83.41% 96.57% 1000 1024 2765 0
mobilenetv4_hybrid_medium.ix_e550_r384_in1k mobilenetv4_hybrid_medium 11.2M 384 82.96% 96.47% 1000 960 1060 4
mobilevitv2_175.cvnets_in22k_ft_in1k_384 mobilevitv2_175 14.3M 384 82.93% 96.45% 1000 896 274 0
rexnetr_200.sw_in12k_ft_in1k rexnetr_200 16.6M 224 82.61% 96.39% 1000 2560 220 0
hgnetv2_b3.ssld_stage2_ft_in1k hgnetv2_b3 16.3M 224 82.91% 96.36% 1000 2048 349 0
maxxvit_rmlp_nano_rw_256.sw_in1k maxxvit_rmlp_nano_rw_256 16.8M 256 83.03% 96.34% 1000 512 230 0
convnext_nano.in12k_ft_in1k convnext_nano 15.6M 224 82.31% 96.34% 1000 640 13058 0
maxxvitv2_nano_rw_256.sw_in1k maxxvitv2_nano_rw_256 23.7M 256 83.10% 96.33% 1000 768 148 0
efficientnetv2_rw_s.ra2_in1k efficientnetv2_rw_s 24.1M 288 82.89% 96.33% 1000 1792 25905 1
mobilevitv2_150.cvnets_in22k_ft_in1k_384 mobilevitv2_150 10.6M 384 82.61% 96.31% 1000 768 474 0
efficientvit_b2.r288_in1k efficientvit_b2 24.4M 288 83.08% 96.30% 1000 384 1096 0
maxvit_rmlp_nano_rw_256.sw_in1k maxvit_rmlp_nano_rw_256 15.5M 256 82.98% 96.27% 1000 512 120 0

5 - large

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
caformer_s36.sail_in22k_ft_in1k_384 caformer_s36 39.3M 384 86.86% 98.22% 1000 512 986 1
nextvit_base.bd_ssld_6m_in1k_384 nextvit_base 44.9M 384 86.36% 98.04% 1000 1024 24 3
convformer_s36.sail_in22k_ft_in1k_384 convformer_s36 40.0M 384 86.38% 97.98% 1000 512 71 0
nextvit_small.bd_ssld_6m_in1k_384 nextvit_small 31.8M 384 85.96% 97.90% 1000 1024 136 2
efficientnet_b5.sw_in12k_ft_in1k efficientnet_b5 30.6M 448 85.89% 97.74% 1000 2048 38814 2
caformer_s18.sail_in22k_ft_in1k_384 caformer_s18 26.3M 384 85.42% 97.71% 1000 512 721 0
vit_medium_patch16_gap_384.sw_in12k_ft_in1k vit_medium_patch16_gap_384 39.0M 384 85.55% 97.64% 1000 512 482 0
convnext_tiny.in12k_ft_in1k_384 convnext_tiny 28.6M 384 85.15% 97.63% 1000 768 2440 0
convnextv2_tiny.fcmae_ft_in22k_in1k_384 convnextv2_tiny 28.6M 384 85.11% 97.63% 1000 768 9443 2
maxvit_tiny_tf_512.in1k maxvit_tiny_tf_512 31.1M 512 85.66% 97.59% 1000 512 6942 0
convformer_s18.sail_in22k_ft_in1k_384 convformer_s18 26.8M 384 85.03% 97.58% 1000 512 123 0
xcit_small_24_p8_384.fb_dist_in1k xcit_small_24_p8_384 47.7M 384 85.58% 97.57% 1000 384 147 0
vit_medium_patch16_reg4_gap_256.sbb_in12k_ft_in1k vit_medium_patch16_reg4_gap_256 38.9M 256 84.94% 97.39% 1000 512 1416 2
maxvit_tiny_tf_384.in1k maxvit_tiny_tf_384 31.0M 384 85.10% 97.38% 1000 512 664 0
coat_lite_medium_384.in1k coat_lite_medium_384 44.6M 384 84.89% 97.38% 1000 512 217 0
cait_s24_384.fb_dist_in1k cait_s24_384 47.1M 384 85.04% 97.35% 1000 384 179 0
xcit_small_24_p16_384.fb_dist_in1k xcit_small_24_p16_384 47.7M 384 85.10% 97.32% 1000 384 99 0
vit_small_r26_s32_384.augreg_in21k_ft_in1k vit_small_r26_s32_384 36.5M 384 84.07% 97.31% 1000 384 4192 1
hgnetv2_b5.ssld_stage2_ft_in1k hgnetv2_b5 39.7M 224 84.81% 97.30% 1000 2048 393 1
xcit_small_12_p8_384.fb_dist_in1k xcit_small_12_p8_384 26.2M 384 85.07% 97.26% 1000 384 172 0
hiera_small_abswin_256.sbb2_e200_in12k_ft_in1k hiera_small_abswin_256 34.4M 256 84.90% 97.25% 1000 768 141 0
volo_d1_384.sail_in1k volo_d1_384 26.8M 384 85.27% 97.22% 1000 384 308 0
vit_medium_patch16_gap_256.sw_in12k_ft_in1k vit_medium_patch16_gap_256 38.9M 256 84.45% 97.22% 1000 512 232 0
xcit_small_24_p8_224.fb_dist_in1k xcit_small_24_p8_224 47.7M 224 84.88% 97.20% 1000 384 89 0
deit3_medium_patch16_224.fb_in22k_ft_in1k deit3_medium_patch16_224 38.8M 224 84.57% 97.18% 1000 512 333 0
xcit_small_12_p16_384.fb_dist_in1k xcit_small_12_p16_384 26.3M 384 84.74% 97.14% 1000 384 150 0
mobilenetv4_conv_aa_large.e230_r448_in12k_ft_in1k mobilenetv4_conv_aa_large 32.7M 448 84.67% 97.11% 1000 960 6684 2
fastvit_ma36.apple_dist_in1k fastvit_ma36 44.2M 256 84.61% 97.01% 1000 1216 263 1
rexnetr_300.sw_in12k_ft_in1k rexnetr_300 34.9M 224 84.04% 97.00% 1000 3840 128 0
swin_small_patch4_window7_224.ms_in22k_ft_in1k swin_small_patch4_window7_224 49.9M 224 83.33% 97.00% 1000 768 12773 0

6 - xlarge

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
eva02_base_patch14_448.mim_in22k_ft_in22k_in1k eva02_base_patch14_448 87.1M 448 88.68% 98.73% 1000 768 7869 5
caformer_b36.sail_in22k_ft_in1k_384 caformer_b36 98.8M 384 88.07% 98.59% 1000 768 1265 0
convformer_b36.sail_in22k_ft_in1k_384 convformer_b36 99.9M 384 87.60% 98.43% 1000 768 36 0
convnextv2_base.fcmae_ft_in22k_in1k_384 convnextv2_base 88.7M 384 87.64% 98.42% 1000 1024 7986 0
caformer_m36.sail_in22k_ft_in1k_384 caformer_m36 56.2M 384 87.47% 98.31% 1000 576 1119 2
coatnet_rmlp_2_rw_384.sw_in12k_ft_in1k coatnet_rmlp_2_rw_384 73.9M 384 87.40% 98.31% 1000 1024 939 1
vit_mediumd_patch16_reg4_gap_384.sbb2_e200_in12k_ft_in1k vit_mediumd_patch16_reg4_gap_384 64.3M 384 87.44% 98.26% 1000 512 51575 5
convnext_base.fb_in22k_ft_in1k_384 convnext_base 88.6M 384 86.83% 98.24% 1000 1024 8739 0
swinv2_base_window12to24_192to384.ms_in22k_ft_in1k swinv2_base_window12to24_192to384 94.6M 384 87.14% 98.23% 1000 1024 14205 0
vit_base_patch16_clip_384.openai_ft_in12k_in1k vit_base_patch16_clip_384 86.9M 384 87.03% 98.19% 1000 768 103 1
beit_base_patch16_384.in22k_ft_in22k_in1k beit_base_patch16_384 90.7M 384 86.82% 98.14% 1000 768 800 0
nextvit_large.bd_ssld_6m_in1k_384 nextvit_large 58.0M 384 86.54% 98.13% 1000 1024 42 1
convformer_m36.sail_in22k_ft_in1k_384 convformer_m36 57.1M 384 86.87% 98.13% 1000 576 65 0
deit3_base_patch16_384.fb_in22k_ft_in1k deit3_base_patch16_384 86.9M 384 86.74% 98.11% 1000 768 1178 0
seresnextaa101d_32x8d.sw_in12k_ft_in1k_288 seresnextaa101d_32x8d 93.8M 288 86.54% 98.09% 1000 2048 772 2
swin_base_patch4_window12_384.ms_in22k_ft_in1k swin_base_patch4_window12_384 90.8M 384 86.44% 98.07% 1000 1024 12783 0
beitv2_base_patch16_224.in1k_ft_in22k_in1k beitv2_base_patch16_224 87.0M 224 86.49% 98.06% 1000 768 1731 0
regnety_160.swag_ft_in1k regnety_160 83.7M 384 86.02% 98.05% 1000 3024 59 0
vit_betwixt_patch16_reg4_gap_384.sbb2_e200_in12k_ft_in1k vit_betwixt_patch16_reg4_gap_384 60.6M 384 86.60% 98.02% 1000 640 527 1
vit_base_patch16_384.augreg_in21k_ft_in1k vit_base_patch16_384 86.9M 384 86.01% 98.00% 1000 768 36455 0
vit_mediumd_patch16_reg4_gap_256.sbb2_e200_in12k_ft_in1k vit_mediumd_patch16_reg4_gap_256 64.1M 256 86.60% 97.94% 1000 512 251 1
convnext_small.in12k_ft_in1k_384 convnext_small 50.2M 384 86.19% 97.92% 1000 768 3724 0
swinv2_base_window12to16_192to256.ms_in22k_ft_in1k swinv2_base_window12to16_192to256 89.2M 256 86.28% 97.91% 1000 1024 5457 0
coatnet_2_rw_224.sw_in12k_ft_in1k coatnet_2_rw_224 73.9M 224 86.58% 97.90% 1000 1024 1019 0
coatnet_rmlp_2_rw_224.sw_in12k_ft_in1k coatnet_rmlp_2_rw_224 73.9M 224 86.54% 97.90% 1000 1024 457 0
vit_base_patch8_224.augreg2_in21k_ft_in1k vit_base_patch8_224 86.6M 224 86.23% 97.84% 1000 768 327530 3
hgnetv2_b6.ssld_stage2_ft_in1k hgnetv2_b6 75.4M 224 86.21% 97.81% 1000 2048 170 0
maxvit_small_tf_512.in1k maxvit_small_tf_512 69.2M 512 86.10% 97.76% 1000 768 1182 2
vit_base_patch16_clip_224.laion2b_ft_in12k_in1k vit_base_patch16_clip_224 86.6M 224 86.21% 97.76% 1000 768 4884 2
deit3_base_patch16_224.fb_in22k_ft_in1k deit3_base_patch16_224 86.6M 224 85.73% 97.75% 1000 768 1439 0

7 - xxlarge

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
maxvit_large_tf_512.in21k_ft_in1k maxvit_large_tf_512 212.5M 512 88.24% 98.61% 1000 1024 276 0
convnext_large_mlp.clip_laion2b_soup_ft_in12k_in1k_384 convnext_large_mlp 200.1M 384 88.33% 98.57% 1000 1536 3565 2
maxvit_large_tf_384.in21k_ft_in1k maxvit_large_tf_384 212.2M 384 88.00% 98.57% 1000 1024 330 0
maxvit_base_tf_512.in21k_ft_in1k maxvit_base_tf_512 120.0M 512 88.21% 98.54% 1000 768 3907 1
maxvit_base_tf_384.in21k_ft_in1k maxvit_base_tf_384 119.8M 384 87.93% 98.54% 1000 768 2254 0
convnextv2_large.fcmae_ft_in22k_in1k_384 convnextv2_large 198.0M 384 88.18% 98.52% 1000 1536 3505 0
convnext_large.fb_in22k_ft_in1k_384 convnext_large 197.8M 384 87.46% 98.38% 1000 1536 16073 0
maxxvitv2_rmlp_base_rw_384.sw_in12k_ft_in1k maxxvitv2_rmlp_base_rw_384 116.1M 384 87.48% 98.37% 1000 1024 416 1
maxvit_rmlp_base_rw_384.sw_in12k_ft_in1k maxvit_rmlp_base_rw_384 116.3M 384 87.81% 98.37% 1000 768 257 0
regnety_320.swag_ft_in1k regnety_320 145.2M 384 86.86% 98.36% 1000 3712 707 0
seresnextaa201d_32x8d.sw_in12k_ft_in1k_384 seresnextaa201d_32x8d 149.8M 384 87.31% 98.33% 1000 2048 234 2
swinv2_large_window12to24_192to384.ms_in22k_ft_in1k swinv2_large_window12to24_192to384 203.4M 384 87.47% 98.26% 1000 1536 1607 0
swin_large_patch4_window12_384.ms_in22k_ft_in1k swin_large_patch4_window12_384 199.6M 384 87.14% 98.23% 1000 1536 8006 0
swinv2_large_window12to16_192to256.ms_in22k_ft_in1k swinv2_large_window12to16_192to256 198.1M 256 86.93% 98.10% 1000 1536 1794 0
maxxvitv2_rmlp_base_rw_224.sw_in12k_ft_in1k maxxvitv2_rmlp_base_rw_224 116.1M 224 86.64% 98.01% 1000 1024 254 2
maxvit_rmlp_base_rw_224.sw_in12k_ft_in1k maxvit_rmlp_base_rw_224 116.3M 224 86.91% 98.00% 1000 768 375 1
swin_large_patch4_window7_224.ms_in22k_ft_in1k swin_large_patch4_window7_224 196.9M 224 86.33% 97.88% 1000 1536 8461 0
volo_d4_448.sail_in1k volo_d4_448 193.4M 448 86.79% 97.88% 1000 768 166 0
xcit_large_24_p8_384.fb_dist_in1k xcit_large_24_p8_384 189.0M 384 86.03% 97.69% 1000 768 169 0
hiera_large_224.mae_in1k_ft_in1k hiera_large_224 213.7M 224 86.04% 97.65% 1000 1152 237 1
efficientvit_l3.r384_in1k efficientvit_l3 246.1M 384 86.40% 97.63% 1000 1024 67 1
xcit_large_24_p16_384.fb_dist_in1k xcit_large_24_p16_384 189.1M 384 85.78% 97.53% 1000 768 149 0
volo_d4_224.sail_in1k volo_d4_224 193.0M 224 85.87% 97.46% 1000 768 187 0
xcit_large_24_p8_224.fb_dist_in1k xcit_large_24_p8_224 189.0M 224 85.40% 97.42% 1000 768 89 0
resnetv2_152x2_bit.goog_in21k_ft_in1k resnetv2_152x2_bit 236.3M 448 84.48% 97.42% 1000 4096 2309 0
mvitv2_large.fb_in1k mvitv2_large 218.0M 224 85.26% 97.19% 1000 1152 225 1
resnext101_32x16d.fb_wsl_ig1b_ft_in1k resnext101_32x16d 194.4M 224 84.16% 97.19% 1000 2048 240 0
ecaresnet269d.ra2_in1k ecaresnet269d 102.3M 320 84.72% 97.18% 1000 2048 299 0
resnetv2_50x3_bit.goog_in21k_ft_in1k resnetv2_50x3_bit 217.3M 448 83.99% 97.13% 1000 6144 1452 1
xcit_large_24_p16_224.fb_dist_in1k xcit_large_24_p16_224 189.1M 224 84.94% 97.13% 1000 768 147 0

8 - huge

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
eva02_large_patch14_448.mim_m38m_ft_in22k_in1k eva02_large_patch14_448 305.1M 448 90.05% 99.06% 1000 1024 9994 20
eva_large_patch14_336.in22k_ft_in22k_in1k eva_large_patch14_336 304.5M 336 89.25% 98.85% 1000 1024 2067 1
eva_large_patch14_196.in22k_ft_in22k_in1k eva_large_patch14_196 304.1M 196 88.60% 98.66% 1000 1024 23709 2
beit_large_patch16_512.in22k_ft_in22k_in1k beit_large_patch16_512 330.9M 512 88.58% 98.66% 1000 1024 849 0
maxvit_xlarge_tf_512.in21k_ft_in1k maxvit_xlarge_tf_512 476.1M 512 88.54% 98.65% 1000 1536 584 3
beit_large_patch16_384.in22k_ft_in22k_in1k beit_large_patch16_384 313.0M 384 88.38% 98.61% 1000 1024 762 0
beitv2_large_patch16_224.in1k_ft_in22k_in1k beitv2_large_patch16_224 305.4M 224 88.41% 98.60% 1000 1024 1127 2
vit_large_patch14_clip_336.laion2b_ft_in12k_in1k vit_large_patch14_clip_336 304.5M 336 88.19% 98.57% 1000 1024 314 0
convnext_xlarge.fb_in22k_ft_in1k_384 convnext_xlarge 350.2M 384 87.77% 98.55% 1000 2048 4881 0
maxvit_xlarge_tf_384.in21k_ft_in1k maxvit_xlarge_tf_384 475.6M 384 88.30% 98.54% 1000 1536 369 0
vit_large_patch14_clip_224.openai_ft_in12k_in1k vit_large_patch14_clip_224 304.2M 224 88.16% 98.54% 1000 1024 244 38
deit3_large_patch16_384.fb_in22k_ft_in1k deit3_large_patch16_384 304.8M 384 87.73% 98.51% 1000 1024 716 0
beit_large_patch16_224.in22k_ft_in22k_in1k beit_large_patch16_224 305.4M 224 87.49% 98.32% 1000 1024 413 0
vit_large_patch16_384.augreg_in21k_ft_in1k vit_large_patch16_384 304.7M 384 87.09% 98.31% 1000 1024 18224 0
deit3_large_patch16_224.fb_in22k_ft_in1k deit3_large_patch16_224 304.4M 224 86.99% 98.24% 1000 1024 203 1
volo_d5_512.sail_in1k volo_d5_512 296.1M 512 87.07% 97.97% 1000 768 277 0
volo_d5_448.sail_in1k volo_d5_448 295.9M 448 86.98% 97.93% 1000 768 501 0
vit_large_r50_s32_384.augreg_in21k_ft_in1k vit_large_r50_s32_384 329.1M 384 86.18% 97.93% 1000 1024 269 0
vit_large_patch16_224.augreg_in21k_ft_in1k vit_large_patch16_224 304.3M 224 85.85% 97.83% 1000 1024 13120 1
dm_nfnet_f6.dm_in1k dm_nfnet_f6 438.4M 448 86.15% 97.77% 1000 3072 900 0
cait_m48_448.fb_dist_in1k cait_m48_448 356.5M 448 86.48% 97.75% 1000 768 4732 0
cait_m36_384.fb_dist_in1k cait_m36_384 271.2M 384 86.06% 97.73% 1000 768 18886 1
volo_d5_224.sail_in1k volo_d5_224 295.5M 224 86.08% 97.58% 1000 768 450 0
dm_nfnet_f5.dm_in1k dm_nfnet_f5 377.2M 416 85.72% 97.55% 1000 3072 258 0
flexivit_large.1200ep_in1k flexivit_large 304.4M 240 85.64% 97.55% 1000 1024 203 0
dm_nfnet_f4.dm_in1k dm_nfnet_f4 316.1M 384 85.50% 97.49% 1000 3072 409 0
resnext101_32x32d.fb_wsl_ig1b_ft_in1k resnext101_32x32d 469.1M 224 85.10% 97.44% 1000 2048 495 2
dm_nfnet_f3.dm_in1k dm_nfnet_f3 254.9M 320 85.10% 97.39% 1000 3072 10946 0
resnetv2_101x3_bit.goog_in21k_ft_in1k resnetv2_101x3_bit 387.9M 448 84.43% 97.38% 1000 6144 1245 0
vit_large_r50_s32_224.augreg_in21k_ft_in1k vit_large_r50_s32_224 329.0M 224 84.43% 97.15% 1000 1024 210 0

9 - giant

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
convnextv2_huge.fcmae_ft_in22k_in1k_512 convnextv2_huge 660.3M 512 88.86% 98.74% 1000 2816 2169 2
convnext_xxlarge.clip_laion2b_soup_ft_in1k convnext_xxlarge 846.5M 256 88.62% 98.72% 1000 3072 40384 2
regnety_1280.swag_ft_in1k regnety_1280 645.2M 384 88.22% 98.70% 1000 7392 151 0
vit_huge_patch14_clip_336.laion2b_ft_in12k_in1k vit_huge_patch14_clip_336 632.5M 336 88.63% 98.67% 1000 1280 2225 2
vit_huge_patch14_clip_224.laion2b_ft_in12k_in1k vit_huge_patch14_clip_224 632.0M 224 88.28% 98.55% 1000 1280 1415 2
deit3_huge_patch14_224.fb_in22k_ft_in1k deit3_huge_patch14_224 632.1M 224 87.18% 98.26% 1000 1280 176 0
hiera_huge_224.mae_in1k_ft_in1k hiera_huge_224 672.8M 224 86.83% 98.01% 1000 2048 281 1
resnetv2_152x4_bit.goog_in21k_ft_in1k resnetv2_152x4_bit 936.5M 480 84.92% 97.46% 1000 8192 1261 2

10 - colossal

Name Architecture Params Input Size Top-1 Top-5 Num Classes Num Features Downloads Likes
eva_giant_patch14_560.m30m_ft_in22k_in1k eva_giant_patch14_560 1.0G 560 89.80% 98.99% 1000 1408 7774 3
eva_giant_patch14_336.m30m_ft_in22k_in1k eva_giant_patch14_336 1.0G 336 89.57% 98.95% 1000 1408 49 0
eva_giant_patch14_224.clip_ft_in1k eva_giant_patch14_224 1.0G 224 88.89% 98.68% 1000 1408 399 2
regnety_2560.seer_ft_in1k regnety_2560 1.3G 384 85.15% 97.44% 1000 10444 52 0