OPPO PGEM10
Geekbench AI Score
812
Single Precision Score
709
Half Precision Score
1465
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 18 2024 10:09 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
767
142.6 IPS |
|
|
Image Classification (HP)
|
100% |
403
74.9 IPS |
|
|
Image Classification (Q)
|
100% |
893
166.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
491
7.97 IPS |
|
|
Image Segmentation (HP)
|
100% |
452
7.32 IPS |
|
|
Image Segmentation (Q)
|
98% |
1022
16.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1794
2.09 IPS |
|
|
Pose Estimation (HP)
|
100% |
1526
1.78 IPS |
|
|
Pose Estimation (Q)
|
84% |
3751
4.45 IPS |
|
|
Object Detection (SP)
|
98% |
245
19.5 IPS |
|
|
Object Detection (HP)
|
98% |
434
34.5 IPS |
|
|
Object Detection (Q)
|
83% |
1210
97.8 IPS |
|
|
Face Detection (SP)
|
100% |
1592
18.9 IPS |
|
|
Face Detection (HP)
|
100% |
966
11.5 IPS |
|
|
Face Detection (Q)
|
95% |
2170
25.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
1178
9.10 IPS |
|
|
Depth Estimation (HP)
|
99% |
1178
9.10 IPS |
|
|
Depth Estimation (Q)
|
64% |
2497
22.9 IPS |
|
|
Style Transfer (SP)
|
89% |
2630
3.41 IPS |
|
|
Style Transfer (HP)
|
89% |
2575
3.34 IPS |
|
|
Style Transfer (Q)
|
98% |
6293
8.11 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
605
22.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
619
22.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1555
57.6 IPS |
|
|
Text Classification (SP)
|
100% |
325
433.5 IPS |
|
|
Text Classification (HP)
|
99% |
256
341.7 IPS |
|
|
Text Classification (Q)
|
88% |
466
629.1 IPS |
|
|
Machine Translation (SP)
|
100% |
783
13.5 IPS |
|
|
Machine Translation (HP)
|
100% |
574
9.89 IPS |
|
|
Machine Translation (Q)
|
50% |
447
15.9 IPS |
