asus ASUSAI2501E
Geekbench ML Score
1006
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 08 2024 05:03 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | asus ASUSAI2501E |
| Model ID | asus ASUSAI2501E |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 22.51 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
441
82.5 IPS |
|
|
Image Classification (F16)
|
100% |
432
80.8 IPS |
|
|
Image Classification (I8)
|
97% |
1192
223.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
551
9.20 IPS |
|
|
Image Segmentation (F16)
|
100% |
547
9.14 IPS |
|
|
Image Segmentation (I8)
|
98% |
1118
18.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
751
0.91 IPS |
|
|
Pose Estimation (F16)
|
100% |
742
0.90 IPS |
|
|
Pose Estimation (I8)
|
100% |
3024
3.66 IPS |
|
|
Object Detection (F32)
|
100% |
449
33.5 IPS |
|
|
Object Detection (F16)
|
100% |
450
33.6 IPS |
|
|
Object Detection (I8)
|
61% |
1318
98.4 IPS |
|
|
Face Detection (F32)
|
100% |
1117
13.3 IPS |
|
|
Face Detection (F16)
|
100% |
1102
13.1 IPS |
|
|
Face Detection (I8)
|
86% |
2617
31.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
949
7.36 IPS |
|
|
Depth Estimation (F16)
|
100% |
945
7.33 IPS |
|
|
Depth Estimation (I8)
|
95% |
2767
21.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1616
2.13 IPS |
|
|
Style Transfer (F16)
|
100% |
1608
2.11 IPS |
|
|
Style Transfer (I8)
|
98% |
4534
5.96 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
542
19.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
545
19.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2019
72.1 IPS |
|
|
Text Classification (F32)
|
100% |
658
946.4 IPS |
|
|
Text Classification (F16)
|
100% |
660
948.7 IPS |
|
|
Text Classification (I8)
|
92% |
1026
1.47 KIPS |
|
|
Machine Translation (F32)
|
100% |
1105
20.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1095
20.1 IPS |
|
|
Machine Translation (I8)
|
64% |
1155
21.3 IPS |
