asus ASUSAI2501E
Geekbench ML Score
1812
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 08 2024 04:14 PM |
| Views | 2 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1071
200.4 IPS |
|
|
Image Classification (F16)
|
100% |
1057
197.7 IPS |
|
|
Image Classification (I8)
|
97% |
1329
248.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1345
22.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1358
22.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1084
18.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
2055
2.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
2046
2.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
7682
9.30 IPS |
|
|
Object Detection (F32)
|
100% |
1032
77.0 IPS |
|
|
Object Detection (F16)
|
100% |
1030
76.9 IPS |
|
|
Object Detection (I8)
|
61% |
1771
132.2 IPS |
|
|
Face Detection (F32)
|
100% |
2466
29.3 IPS |
|
|
Face Detection (F16)
|
100% |
2457
29.2 IPS |
|
|
Face Detection (I8)
|
86% |
3548
42.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2224
17.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
2223
17.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
3959
30.7 IPS |
|
|
Style Transfer (F32)
|
100% |
3490
4.59 IPS |
|
|
Style Transfer (F16)
|
100% |
3501
4.61 IPS |
|
|
Style Transfer (I8)
|
98% |
9064
11.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1161
41.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1150
41.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
3223
115.1 IPS |
|
|
Text Classification (F32)
|
100% |
887
1.27 KIPS |
|
|
Text Classification (F16)
|
100% |
887
1.27 KIPS |
|
|
Text Classification (I8)
|
92% |
631
906.6 IPS |
|
|
Machine Translation (F32)
|
100% |
2021
37.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1993
36.7 IPS |
|
|
Machine Translation (I8)
|
64% |
775
14.3 IPS |
