HONOR ANN-AN00
Geekbench ML Score
528
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | 46fy45 |
| Upload Date | September 10 2024 11:38 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | HONOR ANN-AN00 |
| Model ID | HONOR ANN-AN00 |
| Motherboard | lahaina |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM SM7325 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.71 GHz |
| Memory Information | |
|---|---|
| Size | 7.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
248
46.4 IPS |
|
|
Image Classification (F16)
|
100% |
252
47.1 IPS |
|
|
Image Classification (I8)
|
97% |
441
82.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
337
5.64 IPS |
|
|
Image Segmentation (F16)
|
100% |
348
5.81 IPS |
|
|
Image Segmentation (I8)
|
98% |
489
8.17 IPS |
|
|
Pose Estimation (F32)
|
100% |
515
0.62 IPS |
|
|
Pose Estimation (F16)
|
100% |
518
0.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
2732
3.31 IPS |
|
|
Object Detection (F32)
|
100% |
271
20.2 IPS |
|
|
Object Detection (F16)
|
100% |
270
20.2 IPS |
|
|
Object Detection (I8)
|
61% |
585
43.6 IPS |
|
|
Face Detection (F32)
|
100% |
535
6.36 IPS |
|
|
Face Detection (F16)
|
100% |
529
6.29 IPS |
|
|
Face Detection (I8)
|
86% |
1480
17.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
534
4.14 IPS |
|
|
Depth Estimation (F16)
|
100% |
535
4.15 IPS |
|
|
Depth Estimation (I8)
|
95% |
1350
10.5 IPS |
|
|
Style Transfer (F32)
|
100% |
897
1.18 IPS |
|
|
Style Transfer (F16)
|
100% |
897
1.18 IPS |
|
|
Style Transfer (I8)
|
98% |
2210
2.91 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
344
12.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
337
12.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1285
45.9 IPS |
|
|
Text Classification (F32)
|
100% |
303
435.2 IPS |
|
|
Text Classification (F16)
|
100% |
340
489.2 IPS |
|
|
Text Classification (I8)
|
92% |
282
405.2 IPS |
|
|
Machine Translation (F32)
|
100% |
591
10.9 IPS |
|
|
Machine Translation (F16)
|
100% |
591
10.9 IPS |
|
|
Machine Translation (I8)
|
64% |
233
4.28 IPS |
