OPPO PFUM10
Geekbench AI Score
548
Single Precision Score
551
Half Precision Score
1087
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| Upload Date | December 22 2024 05:54 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | OPPO PFUM10 |
| Model ID | OPPO PFUM10 |
| Motherboard | holi |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 7.24 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
234
43.5 IPS |
|
|
Image Classification (HP)
|
100% |
241
44.8 IPS |
|
|
Image Classification (Q)
|
100% |
737
137.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
314
5.09 IPS |
|
|
Image Segmentation (HP)
|
100% |
314
5.09 IPS |
|
|
Image Segmentation (Q)
|
98% |
836
13.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1188
1.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
1189
1.39 IPS |
|
|
Pose Estimation (Q)
|
84% |
1739
2.06 IPS |
|
|
Object Detection (SP)
|
100% |
241
19.1 IPS |
|
|
Object Detection (HP)
|
100% |
241
19.1 IPS |
|
|
Object Detection (Q)
|
87% |
731
58.7 IPS |
|
|
Face Detection (SP)
|
100% |
775
9.21 IPS |
|
|
Face Detection (HP)
|
100% |
770
9.15 IPS |
|
|
Face Detection (Q)
|
95% |
1743
20.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1022
7.87 IPS |
|
|
Depth Estimation (HP)
|
100% |
1007
7.76 IPS |
|
|
Depth Estimation (Q)
|
75% |
1845
15.0 IPS |
|
|
Style Transfer (SP)
|
89% |
2028
2.63 IPS |
|
|
Style Transfer (HP)
|
89% |
2040
2.65 IPS |
|
|
Style Transfer (Q)
|
98% |
4047
5.22 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
510
18.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
535
19.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1011
37.5 IPS |
|
|
Text Classification (SP)
|
100% |
291
387.9 IPS |
|
|
Text Classification (HP)
|
100% |
289
386.2 IPS |
|
|
Text Classification (Q)
|
88% |
588
793.2 IPS |
|
|
Machine Translation (SP)
|
100% |
494
8.51 IPS |
|
|
Machine Translation (HP)
|
100% |
487
8.39 IPS |
|
|
Machine Translation (Q)
|
50% |
383
13.6 IPS |
