Here, we give the full list of publicly pre-trained models supported by the Hailo Model Zoo.
- Benchmark Networks are marked with
- Networks available in TAPPAS are marked with
- Benchmark and TAPPAS networks run in performance mode
- All models were compiled using Hailo Dataflow Compiler v3.30.0
Network Name | Accuracy (top1) | HW Accuracy | FPS (Batch Size=1) | FPS (Batch Size=8) | Input Resolution (HxWxC) | Params (M) | OPS (G) | Pretrained | Source | Compiled | Profile Html |
---|---|---|---|---|---|---|---|---|---|---|---|
cas_vit_m | 81.2 | 80.97 | 44 | 93 | 384x384x3 | 12.42 | 10.89 | download | link | rgbx | download |
cas_vit_s | 79.93 | 79.83 | 61 | 131 | 384x384x3 | 5.5 | 5.4 | download | link | rgbx | download |
cas_vit_t | 81.9 | 81.63 | 31 | 63 | 384x384x3 | 21.76 | 20.85 | download | link | rgbx | download |
davit_tiny | 82.7 | 82.18 | 9 | 15 | 224x224x3 | 28.36 | 9.1 | download | link | rgbx | download |
deit_base | 80.93 | 79.78 | 40 | 117 | 224x224x3 | 80.26 | 35.22 | download | link | rgbx | download |
deit_small | 78.25 | 77.52 | 52 | 124 | 224x224x3 | 20.52 | 9.4 | download | link | rgbx | download |
deit_tiny | 69.07 | 68.69 | 108 | 400 | 224x224x3 | 5.3 | 2.57 | download | link | rgbx | download |
efficientformer_l1 | 79.13 | 76.57 | 61 | 105 | 224x224x3 | 12.3 | 2.6 | download | link | rgbx | download |
efficientnet_l | 80.47 | 79.29 | 109 | 228 | 300x300x3 | 10.55 | 19.4 | download | link | rgbx | download |
efficientnet_lite0 | 74.99 | 73.82 | 1009 | 1008 | 224x224x3 | 4.63 | 0.78 | download | link | rgbx | download |
efficientnet_lite1 | 76.67 | 76.27 | 292 | 791 | 240x240x3 | 5.39 | 1.22 | download | link | rgbx | download |
efficientnet_lite2 | 77.46 | 76.76 | 193 | 485 | 260x260x3 | 6.06 | 1.74 | download | link | rgbx | download |
efficientnet_lite3 | 79.29 | 78.79 | 151 | 365 | 280x280x3 | 8.16 | 2.8 | download | link | rgbx | download |
efficientnet_lite4 | 80.79 | 80.06 | 107 | 255 | 300x300x3 | 12.95 | 5.10 | download | link | rgbx | download |
efficientnet_m | 78.91 | 78.53 | 181 | 415 | 240x240x3 | 6.87 | 7.32 | download | link | rgbx | download |
efficientnet_s | 77.63 | 77.27 | 341 | 341 | 224x224x3 | 5.41 | 4.72 | download | link | rgbx | download |
fastvit_sa12 | 79.8 | 76.85 | 199 | 630 | 224x224x3 | 11.99 | 3.59 | download | link | rgbx | download |
hardnet39ds | 73.43 | 73.01 | 416 | 1249 | 224x224x3 | 3.48 | 0.86 | download | link | rgbx | download |
hardnet68 | 75.47 | 75.25 | 167 | 391 | 224x224x3 | 17.56 | 8.5 | download | link | rgbx | download |
inception_v1 | 69.74 | 69.54 | 380 | 859 | 224x224x3 | 6.62 | 3 | download | link | rgbx | download |
mobilenet_v1 | 70.97 | 70.3 | 2873 | 2873 | 224x224x3 | 4.22 | 1.14 | download | link | rgbx | download |
mobilenet_v2_1.0 | 71.78 | 70.85 | 3454 | 3454 | 224x224x3 | 3.49 | 0.62 | download | link | rgbx | download |
mobilenet_v2_1.4 | 74.18 | 73.2 | 579 | 579 | 224x224x3 | 6.09 | 1.18 | download | link | rgbx | download |
mobilenet_v3 | 72.21 | 71.81 | 379 | 1204 | 224x224x3 | 4.07 | 2 | download | link | rgbx | download |
mobilenet_v3_large_minimalistic | 72.12 | 70.6 | 2596 | 2596 | 224x224x3 | 3.91 | 0.42 | download | link | rgbx | download |
regnetx_1.6gf | 77.05 | 76.77 | 396 | 1146 | 224x224x3 | 9.17 | 3.22 | download | link | rgbx | download |
regnetx_800mf | 75.16 | 74.87 | 2558 | 2558 | 224x224x3 | 7.24 | 1.6 | download | link | rgbx | download |
repghost_1_0x | 73.03 | 72.2 | 234 | 692 | 224x224x3 | 4.1 | 0.28 | download | link | rgbx | download |
repghost_2_0x | 77.18 | 76.93 | 146 | 422 | 224x224x3 | 9.8 | 1.04 | download | link | rgbx | download |
repvgg_a1 | 74.4 | 72.53 | 1 | 782 | 224x224x3 | 12.79 | 4.7 | download | link | rgbx | download |
repvgg_a2 | 76.52 | 74.47 | 281 | 580 | 224x224x3 | 25.5 | 10.2 | download | link | rgbx | download |
resmlp12_relu | 75.27 | 74.82 | 88 | 309 | 224x224x3 | 15.77 | 6.04 | download | link | rgbx | download |
resnet_v1_18 | 71.27 | 70.79 | 2030 | 2030 | 224x224x3 | 11.68 | 3.64 | download | link | rgbx | download |
resnet_v1_34 | 72.7 | 72.18 | 279 | 703 | 224x224x3 | 21.79 | 7.34 | download | link | rgbx | download |
resnet_v1_50 | 75.21 | 74.67 | 313 | 1013 | 224x224x3 | 25.53 | 6.98 | download | link | rgbx | download |
resnext26_32x4d | 76.17 | 75.94 | 362 | 830 | 224x224x3 | 15.37 | 4.96 | download | link | rgbx | download |
resnext50_32x4d | 79.3 | 78.4 | 202 | 509 | 224x224x3 | 24.99 | 8.48 | download | link | rgbx | download |
squeezenet_v1.1 | 59.85 | 59.35 | 2 | 775 | 224x224x3 | 1.24 | 0.78 | download | link | rgbx | download |
swin_small | 83.13 | 80.25 | 16 | 38 | 224x224x3 | 50 | 17.6 | download | link | rgbx | download |
swin_tiny | 81.3 | 79.54 | 32 | 75 | 224x224x3 | 29 | 9.1 | download | link | rgbx | download |
vit_base | 84.5 | 83.45 | 40 | 117 | 224x224x3 | 86.5 | 35.188 | download | link | rgbx | download |
vit_base_bn | 79.98 | 79.24 | 65 | 204 | 224x224x3 | 86.5 | 35.188 | download | link | rgbx | download |
vit_small | 81.5 | 80.38 | 58 | 155 | 224x224x3 | 21.12 | 8.62 | download | link | rgbx | download |
vit_small_bn | 78.12 | 77.26 | 135 | 475 | 224x224x3 | 21.12 | 8.62 | download | link | rgbx | download |
vit_tiny | 75.51 | 74.15 | 108 | 394 | 224x224x3 | 5.73 | 2.2 | download | link | rgbx | download |
vit_tiny_bn | 68.95 | 67.33 | 248 | 1117 | 224x224x3 | 5.73 | 2.2 | download | link | rgbx | download |