HONOR AGT-AN00
Geekbench ML Score
940
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 23 2024 01:11 PM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR AGT-AN00 |
| Model ID | HONOR AGT-AN00 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM SM8475 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 11.03 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
562
105.1 IPS |
|
|
Image Classification (F16)
|
100% |
876
163.9 IPS |
|
|
Image Classification (I8)
|
97% |
896
167.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
878
14.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1207
20.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
1106
18.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
720
0.87 IPS |
|
|
Pose Estimation (F16)
|
100% |
1304
1.58 IPS |
|
|
Pose Estimation (I8)
|
100% |
1314
1.59 IPS |
|
|
Object Detection (F32)
|
100% |
304
22.7 IPS |
|
|
Object Detection (F16)
|
100% |
722
53.9 IPS |
|
|
Object Detection (I8)
|
62% |
608
45.4 IPS |
|
|
Face Detection (F32)
|
100% |
1625
19.3 IPS |
|
|
Face Detection (F16)
|
97% |
2901
34.5 IPS |
|
|
Face Detection (I8)
|
87% |
2302
27.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1144
8.87 IPS |
|
|
Depth Estimation (F16)
|
100% |
2582
20.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
2561
19.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2916
3.84 IPS |
|
|
Style Transfer (F16)
|
100% |
6548
8.61 IPS |
|
|
Style Transfer (I8)
|
98% |
6622
8.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
403
14.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
544
19.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
538
19.2 IPS |
|
|
Text Classification (F32)
|
100% |
211
302.6 IPS |
|
|
Text Classification (F16)
|
100% |
201
289.5 IPS |
|
|
Text Classification (I8)
|
92% |
364
523.3 IPS |
|
|
Machine Translation (F32)
|
100% |
432
7.96 IPS |
|
|
Machine Translation (F16)
|
100% |
467
8.59 IPS |
|
|
Machine Translation (I8)
|
64% |
497
9.15 IPS |
