HONOR ANN-AN00
Geekbench ML Score
481
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | 46fy45 |
| Upload Date | September 10 2024 11:52 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
327
61.2 IPS |
|
|
Image Classification (F16)
|
100% |
530
99.1 IPS |
|
|
Image Classification (I8)
|
94% |
17
3.26 IPS |
|
|
Image Segmentation (F32)
|
100% |
552
9.22 IPS |
|
|
Image Segmentation (F16)
|
100% |
816
13.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
409
6.83 IPS |
|
|
Pose Estimation (F32)
|
100% |
1065
1.29 IPS |
|
|
Pose Estimation (F16)
|
100% |
3657
4.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
943
1.14 IPS |
|
|
Object Detection (F32)
|
100% |
356
26.5 IPS |
|
|
Object Detection (F16)
|
100% |
530
39.6 IPS |
|
|
Object Detection (I8)
|
0% |
2000
149.3 IPS |
|
|
Face Detection (F32)
|
100% |
855
10.2 IPS |
|
|
Face Detection (F16)
|
97% |
1302
15.5 IPS |
|
|
Face Detection (I8)
|
86% |
826
9.83 IPS |
|
|
Depth Estimation (F32)
|
100% |
496
3.84 IPS |
|
|
Depth Estimation (F16)
|
100% |
589
4.56 IPS |
|
|
Depth Estimation (I8)
|
73% |
8175
63.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1383
1.82 IPS |
|
|
Style Transfer (F16)
|
100% |
1851
2.43 IPS |
|
|
Style Transfer (I8)
|
98% |
1447
1.90 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
628
22.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1629
58.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
262
9.37 IPS |
|
|
Text Classification (F32)
|
100% |
3
4.80 IPS |
|
|
Text Classification (F16)
|
100% |
63
90.6 IPS |
|
|
Text Classification (I8)
|
94% |
29
42.1 IPS |
|
|
Machine Translation (F32)
|
100% |
264
4.86 IPS |
|
|
Machine Translation (F16)
|
100% |
328
6.04 IPS |
|
|
Machine Translation (I8)
|
64% |
380
7.00 IPS |
