HONOR ANN-AN00
Geekbench ML Score
402
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | 46fy45 |
| Upload Date | September 10 2024 11:44 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
243
45.4 IPS |
|
|
Image Classification (F16)
|
100% |
332
62.1 IPS |
|
|
Image Classification (I8)
|
97% |
319
59.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
281
4.70 IPS |
|
|
Image Segmentation (F16)
|
100% |
359
6.00 IPS |
|
|
Image Segmentation (I8)
|
98% |
357
5.97 IPS |
|
|
Pose Estimation (F32)
|
100% |
396
0.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
297
0.36 IPS |
|
|
Pose Estimation (I8)
|
100% |
297
0.36 IPS |
|
|
Object Detection (F32)
|
100% |
155
11.6 IPS |
|
|
Object Detection (F16)
|
100% |
168
12.5 IPS |
|
|
Object Detection (I8)
|
62% |
159
11.8 IPS |
|
|
Face Detection (F32)
|
100% |
716
8.51 IPS |
|
|
Face Detection (F16)
|
97% |
964
11.5 IPS |
|
|
Face Detection (I8)
|
87% |
867
10.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
615
4.77 IPS |
|
|
Depth Estimation (F16)
|
100% |
949
7.36 IPS |
|
|
Depth Estimation (I8)
|
95% |
922
7.15 IPS |
|
|
Style Transfer (F32)
|
100% |
1136
1.49 IPS |
|
|
Style Transfer (F16)
|
100% |
1999
2.63 IPS |
|
|
Style Transfer (I8)
|
98% |
2003
2.63 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
253
9.03 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
403
14.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
400
14.3 IPS |
|
|
Text Classification (F32)
|
100% |
153
220.1 IPS |
|
|
Text Classification (F16)
|
100% |
153
220.6 IPS |
|
|
Text Classification (I8)
|
92% |
299
429.7 IPS |
|
|
Machine Translation (F32)
|
100% |
277
5.09 IPS |
|
|
Machine Translation (F16)
|
100% |
283
5.20 IPS |
|
|
Machine Translation (I8)
|
64% |
316
5.82 IPS |
