OPPO PGEM10
Geekbench AI Score
413
Single Precision Score
398
Half Precision Score
876
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | 5j3rul3 |
| Upload Date | August 31 2024 01:30 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO PGEM10 |
| Model ID | OPPO PGEM10 |
| Motherboard | kalama |
| Governor | uag |
| 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 | 14.83 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
295
54.9 IPS |
|
|
Image Classification (HP)
|
100% |
287
53.4 IPS |
|
|
Image Classification (Q)
|
97% |
688
128.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
358
5.80 IPS |
|
|
Image Segmentation (HP)
|
100% |
357
5.79 IPS |
|
|
Image Segmentation (Q)
|
98% |
745
12.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
475
0.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
462
0.54 IPS |
|
|
Pose Estimation (Q)
|
98% |
1807
2.12 IPS |
|
|
Object Detection (SP)
|
100% |
267
21.2 IPS |
|
|
Object Detection (HP)
|
100% |
263
20.9 IPS |
|
|
Object Detection (Q)
|
89% |
656
52.5 IPS |
|
|
Face Detection (SP)
|
100% |
651
7.74 IPS |
|
|
Face Detection (HP)
|
100% |
641
7.62 IPS |
|
|
Face Detection (Q)
|
97% |
1440
17.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
558
4.30 IPS |
|
|
Depth Estimation (HP)
|
100% |
552
4.25 IPS |
|
|
Depth Estimation (Q)
|
73% |
1524
12.5 IPS |
|
|
Style Transfer (SP)
|
100% |
919
1.18 IPS |
|
|
Style Transfer (HP)
|
100% |
725
0.93 IPS |
|
|
Style Transfer (Q)
|
98% |
1705
2.20 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
230
8.48 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
221
8.17 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
813
30.1 IPS |
|
|
Text Classification (SP)
|
100% |
293
391.1 IPS |
|
|
Text Classification (HP)
|
100% |
302
403.7 IPS |
|
|
Text Classification (Q)
|
91% |
429
576.8 IPS |
|
|
Machine Translation (SP)
|
100% |
485
8.35 IPS |
|
|
Machine Translation (HP)
|
100% |
474
8.17 IPS |
|
|
Machine Translation (Q)
|
57% |
336
8.20 IPS |
