asus ASUSAI2501E
Geekbench ML Score
1008
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 08 2024 04:59 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% |
442
82.7 IPS |
|
|
Image Classification (F16)
|
100% |
434
81.2 IPS |
|
|
Image Classification (I8)
|
97% |
1195
223.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
552
9.22 IPS |
|
|
Image Segmentation (F16)
|
100% |
549
9.17 IPS |
|
|
Image Segmentation (I8)
|
98% |
1118
18.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
752
0.91 IPS |
|
|
Pose Estimation (F16)
|
100% |
746
0.90 IPS |
|
|
Pose Estimation (I8)
|
100% |
3034
3.67 IPS |
|
|
Object Detection (F32)
|
100% |
453
33.8 IPS |
|
|
Object Detection (F16)
|
100% |
453
33.8 IPS |
|
|
Object Detection (I8)
|
61% |
1338
99.9 IPS |
|
|
Face Detection (F32)
|
100% |
1116
13.3 IPS |
|
|
Face Detection (F16)
|
100% |
1104
13.1 IPS |
|
|
Face Detection (I8)
|
86% |
2632
31.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
949
7.36 IPS |
|
|
Depth Estimation (F16)
|
100% |
948
7.35 IPS |
|
|
Depth Estimation (I8)
|
95% |
2773
21.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1618
2.13 IPS |
|
|
Style Transfer (F16)
|
100% |
1606
2.11 IPS |
|
|
Style Transfer (I8)
|
98% |
4538
5.97 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
546
19.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
549
19.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2017
72.1 IPS |
|
|
Text Classification (F32)
|
100% |
659
947.4 IPS |
|
|
Text Classification (F16)
|
100% |
660
947.8 IPS |
|
|
Text Classification (I8)
|
92% |
1024
1.47 KIPS |
|
|
Machine Translation (F32)
|
100% |
1106
20.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1095
20.2 IPS |
|
|
Machine Translation (I8)
|
64% |
1154
21.2 IPS |
