asus ASUSAI2501E
Geekbench ML Score
654
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 08 2024 04:26 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% |
278
52.1 IPS |
|
|
Image Classification (F16)
|
100% |
279
52.2 IPS |
|
|
Image Classification (I8)
|
97% |
727
136.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
360
6.01 IPS |
|
|
Image Segmentation (F16)
|
100% |
360
6.02 IPS |
|
|
Image Segmentation (I8)
|
98% |
702
11.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
504
0.61 IPS |
|
|
Pose Estimation (F16)
|
100% |
499
0.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
1931
2.34 IPS |
|
|
Object Detection (F32)
|
100% |
290
21.6 IPS |
|
|
Object Detection (F16)
|
100% |
288
21.5 IPS |
|
|
Object Detection (I8)
|
61% |
830
62.0 IPS |
|
|
Face Detection (F32)
|
100% |
760
9.03 IPS |
|
|
Face Detection (F16)
|
100% |
767
9.12 IPS |
|
|
Face Detection (I8)
|
86% |
1656
19.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
646
5.01 IPS |
|
|
Depth Estimation (F16)
|
100% |
654
5.07 IPS |
|
|
Depth Estimation (I8)
|
95% |
1777
13.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1157
1.52 IPS |
|
|
Style Transfer (F16)
|
100% |
1152
1.52 IPS |
|
|
Style Transfer (I8)
|
98% |
3034
3.99 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
350
12.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
344
12.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1240
44.3 IPS |
|
|
Text Classification (F32)
|
100% |
399
573.6 IPS |
|
|
Text Classification (F16)
|
100% |
404
580.5 IPS |
|
|
Text Classification (I8)
|
92% |
627
900.5 IPS |
|
|
Machine Translation (F32)
|
100% |
724
13.3 IPS |
|
|
Machine Translation (F16)
|
100% |
728
13.4 IPS |
|
|
Machine Translation (I8)
|
64% |
748
13.8 IPS |
