HONOR PGT-N19
Geekbench ML Score
915
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 12 2024 07:39 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | HONOR PGT-N19 |
| Model ID | HONOR PGT-N19 |
| 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 | 10.85 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
447
83.6 IPS |
|
|
Image Classification (F16)
|
100% |
432
80.8 IPS |
|
|
Image Classification (I8)
|
97% |
698
130.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
600
10.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
607
10.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
660
11.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1105
1.34 IPS |
|
|
Pose Estimation (F16)
|
100% |
1077
1.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
4235
5.13 IPS |
|
|
Object Detection (F32)
|
100% |
488
36.4 IPS |
|
|
Object Detection (F16)
|
100% |
482
36.0 IPS |
|
|
Object Detection (I8)
|
61% |
880
65.7 IPS |
|
|
Face Detection (F32)
|
100% |
1058
12.6 IPS |
|
|
Face Detection (F16)
|
100% |
1067
12.7 IPS |
|
|
Face Detection (I8)
|
86% |
1675
19.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1110
8.61 IPS |
|
|
Depth Estimation (F16)
|
100% |
1137
8.82 IPS |
|
|
Depth Estimation (I8)
|
95% |
1905
14.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1958
2.58 IPS |
|
|
Style Transfer (F16)
|
100% |
1940
2.55 IPS |
|
|
Style Transfer (I8)
|
98% |
3775
4.97 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
706
25.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
708
25.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1916
68.4 IPS |
|
|
Text Classification (F32)
|
100% |
506
726.8 IPS |
|
|
Text Classification (F16)
|
100% |
496
712.3 IPS |
|
|
Text Classification (I8)
|
92% |
339
486.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1036
19.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1030
19.0 IPS |
|
|
Machine Translation (I8)
|
64% |
370
6.80 IPS |
