OPPO Reno9 Pro+ 5G OPPO PGW110
Geekbench AI Score
332
Single Precision Score
333
Half Precision Score
809
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | rennsport |
| Upload Date | March 13 2025 03:40 AM |
| Views | 23 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO PGW110 |
| Model ID | OPPO PGW110 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 14.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
194
36.2 IPS |
|
|
Image Classification (HP)
|
100% |
196
36.4 IPS |
|
|
Image Classification (Q)
|
99% |
545
101.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
255
4.14 IPS |
|
|
Image Segmentation (HP)
|
100% |
252
4.09 IPS |
|
|
Image Segmentation (Q)
|
98% |
589
9.57 IPS |
|
|
Pose Estimation (SP)
|
100% |
351
0.41 IPS |
|
|
Pose Estimation (HP)
|
100% |
351
0.41 IPS |
|
|
Pose Estimation (Q)
|
98% |
1357
1.59 IPS |
|
|
Object Detection (SP)
|
100% |
196
15.5 IPS |
|
|
Object Detection (HP)
|
100% |
192
15.2 IPS |
|
|
Object Detection (Q)
|
87% |
580
46.5 IPS |
|
|
Face Detection (SP)
|
100% |
516
6.14 IPS |
|
|
Face Detection (HP)
|
100% |
530
6.30 IPS |
|
|
Face Detection (Q)
|
97% |
1274
15.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
434
3.34 IPS |
|
|
Depth Estimation (HP)
|
99% |
444
3.42 IPS |
|
|
Depth Estimation (Q)
|
64% |
1097
9.95 IPS |
|
|
Style Transfer (SP)
|
100% |
756
0.97 IPS |
|
|
Style Transfer (HP)
|
100% |
763
0.98 IPS |
|
|
Style Transfer (Q)
|
98% |
1931
2.49 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
215
7.95 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
216
7.99 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
797
29.5 IPS |
|
|
Text Classification (SP)
|
100% |
285
380.9 IPS |
|
|
Text Classification (HP)
|
100% |
285
380.7 IPS |
|
|
Text Classification (Q)
|
91% |
520
698.9 IPS |
|
|
Machine Translation (SP)
|
100% |
468
8.05 IPS |
|
|
Machine Translation (HP)
|
100% |
468
8.06 IPS |
|
|
Machine Translation (Q)
|
57% |
428
10.5 IPS |
