asus ASUS_AI2401_H
Geekbench ML Score
466
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 04 2024 06:32 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | asus ASUS_AI2401_H |
| Model ID | asus ASUS_AI2401_H |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.94 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
164
30.7 IPS |
|
|
Image Classification (F16)
|
100% |
164
30.7 IPS |
|
|
Image Classification (I8)
|
97% |
415
77.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
215
3.59 IPS |
|
|
Image Segmentation (F16)
|
100% |
215
3.59 IPS |
|
|
Image Segmentation (I8)
|
98% |
433
7.23 IPS |
|
|
Pose Estimation (F32)
|
100% |
442
0.54 IPS |
|
|
Pose Estimation (F16)
|
100% |
442
0.54 IPS |
|
|
Pose Estimation (I8)
|
100% |
1650
2.00 IPS |
|
|
Object Detection (F32)
|
100% |
264
19.7 IPS |
|
|
Object Detection (F16)
|
100% |
167
12.5 IPS |
|
|
Object Detection (I8)
|
61% |
463
34.5 IPS |
|
|
Face Detection (F32)
|
100% |
637
7.58 IPS |
|
|
Face Detection (F16)
|
100% |
637
7.58 IPS |
|
|
Face Detection (I8)
|
86% |
1447
17.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
566
4.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
568
4.40 IPS |
|
|
Depth Estimation (I8)
|
95% |
1023
7.93 IPS |
|
|
Style Transfer (F32)
|
100% |
908
1.19 IPS |
|
|
Style Transfer (F16)
|
100% |
910
1.20 IPS |
|
|
Style Transfer (I8)
|
98% |
2137
2.81 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
296
10.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
317
11.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
651
23.3 IPS |
|
|
Text Classification (F32)
|
100% |
208
299.4 IPS |
|
|
Text Classification (F16)
|
100% |
209
300.0 IPS |
|
|
Text Classification (I8)
|
92% |
344
494.0 IPS |
|
|
Machine Translation (F32)
|
100% |
610
11.2 IPS |
|
|
Machine Translation (F16)
|
100% |
611
11.2 IPS |
|
|
Machine Translation (I8)
|
64% |
677
12.5 IPS |
