- System host: Intel® Core™ i5-9400 CPU @ 2.90GHz
- Hailo Dataflow Compiler Version v5.3.0
- Measurement conditions: Measuring from the SoC, room temperature
| Key / Icon | Description |
|---|---|
| ⭐ | Networks used by Hailo-apps. |
| S | Source – Link to the model's open-source repository. |
| PT | Pretrained – Download the pretrained model file (ZIP format). |
| HEF, NV12, RGBX | Compiled Models – Links to models in various formats: - HEF: RGB format - NV12: NV12 format - RGBX: RGBX format |
| PR | Profiler Report – Download the model's performance profiling report. |
| Network Name | float Accuracy (top1) | Hardware Accuracy (top1) | FPS (Batch Size=1) | FPS (Batch Size=8) | Links | Input Resolution (HxWxC) | Params (M) | OPS (G) |
|---|---|---|---|---|---|---|---|---|
| cas_vit_m | 81.2 | 81.0 | 50.7 | 87.9 | 384x384x3 | 12.42 | 10.89 | |
| cas_vit_s | 79.8 | 79.6 | 68.2 | 122 | 384x384x3 | 5.5 | 5.4 | |
| cas_vit_t | 81.9 | 81.5 | 37.1 | 61.0 | 384x384x3 | 21.76 | 20.85 | |
| deit_base | 80.7 | 78.9 | 34.5 | 80.0 | 224x224x3 | 80.26 | 35.22 | |
| deit_small | 78.1 | 77.5 | 82.5 | 175 | 224x224x3 | 20.52 | 9.4 | |
| efficientnet_l | 80.5 | 79.3 | 66.3 | 95.9 | 300x300x3 | 10.55 | 19.4 | |
| efficientnet_lite0 | 75.0 | 74.0 | 351 | 711 | 224x224x3 | 4.63 | 0.78 | |
| efficientnet_lite1 | 76.5 | 76.0 | 256 | 524 | 240x240x3 | 5.39 | 1.22 | |
| efficientnet_lite2 | 77.5 | 76.5 | 150 | 271 | 260x260x3 | 6.06 | 1.74 | |
| efficientnet_lite3 | 79.3 | 78.6 | 113 | 197 | 280x280x3 | 8.16 | 2.8 | |
| efficientnet_lite4 | 80.8 | 80.1 | 73.2 | 124 | 300x300x3 | 12.95 | 5.10 | |
| efficientnet_m | 78.8 | 78.3 | 154 | 252 | 240x240x3 | 6.87 | 7.32 | |
| fastvit_sa12⭐ | 79.7 | 76.6 | 163 | 352 | 224x224x3 | 11.99 | 3.59 | |
| hardnet39ds⭐ | 73.3 | 72.9 | 364 | 774 | 224x224x3 | 3.48 | 0.86 | |
| hardnet68⭐ | 75.3 | 75.1 | 123 | 252 | 224x224x3 | 17.56 | 8.5 | |
| inception_v1 | 69.7 | 69.4 | 330 | 584 | 224x224x3 | 6.62 | 3 | |
| mobilenet_v1 | 70.8 | 70.1 | 574 | 1207 | 224x224x3 | 4.22 | 1.14 | |
| mobilenet_v2_1.0 | 71.6 | 70.9 | 453 | 883 | 224x224x3 | 3.49 | 0.62 | |
| mobilenet_v2_1.4 | 73.8 | 73.0 | 335 | 638 | 224x224x3 | 6.09 | 1.18 | |
| mobilenet_v3 | 72.0 | 71.7 | 399 | 825 | 224x224x3 | 4.07 | 2 | |
| regnetx_1.6gf | 76.8 | 76.4 | 311 | 674 | 224x224x3 | 9.17 | 3.22 | |
| regnetx_800mf | 75.0 | 74.7 | 498 | 1316 | 224x224x3 | 7.24 | 1.6 | |
| repghost_1_0x | 73.0 | 72.1 | 272 | 607 | 224x224x3 | 4.1 | 0.28 | |
| repghost_2_0x | 77.2 | 76.9 | 155 | 322 | 224x224x3 | 9.8 | 1.04 | |
| repvgg_a1 | 74.4 | 72.1 | 285 | 648 | 224x224x3 | 12.79 | 4.7 | |
| repvgg_a2 | 76.4 | 74.5 | 148 | 296 | 224x224x3 | 25.5 | 10.2 | |
| resmlp12_relu | 74.9 | 74.6 | 114 | 374 | 224x224x3 | 15.77 | 6.04 | |
| resnet_v1_18⭐ | 71.1 | 70.6 | 377 | 786 | 224x224x3 | 11.68 | 3.64 | |
| resnet_v1_34⭐ | 72.6 | 72.1 | 176 | 415 | 224x224x3 | 21.79 | 7.34 | |
| resnet_v1_50⭐ | 75.2 | 74.6 | 159 | 379 | 224x224x3 | 25.53 | 6.98 | |
| resnext26_32x4d | 76.0 | 75.7 | 200 | 446 | 224x224x3 | 15.37 | 4.96 | |
| resnext50_32x4d | 79.3 | 78.4 | 133 | 287 | 224x224x3 | 24.99 | 8.48 | |
| squeezenet_v1.1 | 59.6 | 59.1 | 784 | 1266 | 224x224x3 | 1.24 | 0.78 | |
| vit_base | 84.2 | 83.0 | 34.5 | 80.0 | 224x224x3 | 86.5 | 35.188 | |
| vit_large | 83.2 | 82.0 | 9.63 | 21.1 | 224x224x3 | 304.2 | 123.4 | |
| vit_small_bn | 77.9 | 77.2 | 142 | 351 | 224x224x3 | 21.12 | 8.62 | |
| vit_tiny_bn | 68.5 | 67.0 | 240 | 629 | 224x224x3 | 5.73 | 2.2 |