HONOR PGT-N19
Geekbench ML Score
1029
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 12 2024 07:42 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
602
112.7 IPS |
|
|
Image Classification (F16)
|
100% |
935
175.0 IPS |
|
|
Image Classification (I8)
|
99% |
877
164.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1222
20.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1891
31.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1735
29.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
912
1.10 IPS |
|
|
Pose Estimation (F16)
|
100% |
1324
1.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
1329
1.61 IPS |
|
|
Object Detection (F32)
|
100% |
251
18.7 IPS |
|
|
Object Detection (F16)
|
100% |
375
28.0 IPS |
|
|
Object Detection (I8)
|
62% |
382
28.5 IPS |
|
|
Face Detection (F32)
|
100% |
2098
24.9 IPS |
|
|
Face Detection (F16)
|
97% |
3551
42.2 IPS |
|
|
Face Detection (I8)
|
86% |
3162
37.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1432
11.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
2720
21.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
2733
21.2 IPS |
|
|
Style Transfer (F32)
|
100% |
3539
4.66 IPS |
|
|
Style Transfer (F16)
|
100% |
7999
10.5 IPS |
|
|
Style Transfer (I8)
|
98% |
8084
10.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
466
16.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
412
14.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
409
14.6 IPS |
|
|
Text Classification (F32)
|
100% |
299
430.4 IPS |
|
|
Text Classification (F16)
|
100% |
301
432.2 IPS |
|
|
Text Classification (I8)
|
92% |
426
611.8 IPS |
|
|
Machine Translation (F32)
|
100% |
503
9.25 IPS |
|
|
Machine Translation (F16)
|
100% |
502
9.24 IPS |
|
|
Machine Translation (I8)
|
64% |
481
8.86 IPS |
