HONOR VER-N49
Geekbench ML Score
1075
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 17 2024 09:10 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | HONOR VER-N49 |
| Model ID | HONOR VER-N49 |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 14.95 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
620
116.1 IPS |
|
|
Image Classification (F16)
|
100% |
1008
188.6 IPS |
|
|
Image Classification (I8)
|
99% |
987
184.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1240
20.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1893
31.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1974
33.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
930
1.13 IPS |
|
|
Pose Estimation (F16)
|
100% |
1375
1.67 IPS |
|
|
Pose Estimation (I8)
|
100% |
1382
1.67 IPS |
|
|
Object Detection (F32)
|
100% |
415
31.0 IPS |
|
|
Object Detection (F16)
|
100% |
589
44.0 IPS |
|
|
Object Detection (I8)
|
62% |
426
31.8 IPS |
|
|
Face Detection (F32)
|
100% |
2124
25.3 IPS |
|
|
Face Detection (F16)
|
97% |
3363
40.0 IPS |
|
|
Face Detection (I8)
|
86% |
3017
35.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1436
11.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
2773
21.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
2714
21.0 IPS |
|
|
Style Transfer (F32)
|
100% |
3574
4.70 IPS |
|
|
Style Transfer (F16)
|
100% |
8031
10.6 IPS |
|
|
Style Transfer (I8)
|
98% |
8068
10.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
456
16.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
412
14.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
415
14.8 IPS |
|
|
Text Classification (F32)
|
100% |
337
483.7 IPS |
|
|
Text Classification (F16)
|
100% |
144
206.3 IPS |
|
|
Text Classification (I8)
|
92% |
476
684.0 IPS |
|
|
Machine Translation (F32)
|
100% |
564
10.4 IPS |
|
|
Machine Translation (F16)
|
100% |
570
10.5 IPS |
|
|
Machine Translation (I8)
|
64% |
544
10.0 IPS |
