asus ASUSAI2501E
Geekbench ML Score
1805
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 08 2024 04:12 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1113
208.3 IPS |
|
|
Image Classification (F16)
|
100% |
1054
197.3 IPS |
|
|
Image Classification (I8)
|
97% |
1321
247.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1352
22.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1354
22.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1043
17.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
2058
2.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
2066
2.50 IPS |
|
|
Pose Estimation (I8)
|
100% |
7627
9.24 IPS |
|
|
Object Detection (F32)
|
100% |
1034
77.2 IPS |
|
|
Object Detection (F16)
|
100% |
1032
77.1 IPS |
|
|
Object Detection (I8)
|
61% |
1760
131.4 IPS |
|
|
Face Detection (F32)
|
100% |
2439
29.0 IPS |
|
|
Face Detection (F16)
|
100% |
2460
29.2 IPS |
|
|
Face Detection (I8)
|
86% |
3544
42.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
2230
17.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
2232
17.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
3935
30.5 IPS |
|
|
Style Transfer (F32)
|
100% |
3506
4.61 IPS |
|
|
Style Transfer (F16)
|
100% |
3509
4.62 IPS |
|
|
Style Transfer (I8)
|
98% |
8963
11.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1164
41.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1132
40.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
3058
109.2 IPS |
|
|
Text Classification (F32)
|
100% |
887
1.28 KIPS |
|
|
Text Classification (F16)
|
100% |
888
1.28 KIPS |
|
|
Text Classification (I8)
|
92% |
627
901.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1991
36.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1986
36.5 IPS |
|
|
Machine Translation (I8)
|
64% |
769
14.2 IPS |
