HONOR ADT-AN00
Geekbench ML Score
653
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 03 2025 06:16 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR ADT-AN00 |
| Model ID | HONOR ADT-AN00 |
| Motherboard | ADT |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM SM8350 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 11.09 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
392
73.4 IPS |
|
|
Image Classification (F16)
|
100% |
399
74.6 IPS |
|
|
Image Classification (I8)
|
97% |
396
74.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
597
9.97 IPS |
|
|
Image Segmentation (F16)
|
100% |
686
11.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
862
14.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
712
0.86 IPS |
|
|
Pose Estimation (F16)
|
100% |
419
0.51 IPS |
|
|
Pose Estimation (I8)
|
100% |
418
0.51 IPS |
|
|
Object Detection (F32)
|
100% |
241
18.0 IPS |
|
|
Object Detection (F16)
|
100% |
210
15.7 IPS |
|
|
Object Detection (I8)
|
62% |
223
16.6 IPS |
|
|
Face Detection (F32)
|
100% |
1441
17.1 IPS |
|
|
Face Detection (F16)
|
97% |
2014
23.9 IPS |
|
|
Face Detection (I8)
|
87% |
1882
22.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1011
7.84 IPS |
|
|
Depth Estimation (F16)
|
100% |
1290
10.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
1263
9.79 IPS |
|
|
Style Transfer (F32)
|
100% |
2080
2.74 IPS |
|
|
Style Transfer (F16)
|
100% |
3330
4.38 IPS |
|
|
Style Transfer (I8)
|
98% |
3326
4.38 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
408
14.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
426
15.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
526
18.8 IPS |
|
|
Text Classification (F32)
|
100% |
286
410.3 IPS |
|
|
Text Classification (F16)
|
100% |
287
411.8 IPS |
|
|
Text Classification (I8)
|
92% |
509
732.1 IPS |
|
|
Machine Translation (F32)
|
100% |
466
8.57 IPS |
|
|
Machine Translation (F16)
|
100% |
455
8.37 IPS |
|
|
Machine Translation (I8)
|
64% |
546
10.0 IPS |
