OPPO PFUM10
Geekbench AI Score
195
Single Precision Score
196
Half Precision Score
474
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| Upload Date | December 24 2024 01:30 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| 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% |
113
21.0 IPS |
|
|
Image Classification (HP)
|
100% |
114
21.1 IPS |
|
|
Image Classification (Q)
|
97% |
307
57.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
155
2.50 IPS |
|
|
Image Segmentation (HP)
|
100% |
156
2.52 IPS |
|
|
Image Segmentation (Q)
|
98% |
340
5.53 IPS |
|
|
Pose Estimation (SP)
|
100% |
210
0.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
210
0.25 IPS |
|
|
Pose Estimation (Q)
|
98% |
800
0.94 IPS |
|
|
Object Detection (SP)
|
100% |
113
8.98 IPS |
|
|
Object Detection (HP)
|
100% |
114
9.02 IPS |
|
|
Object Detection (Q)
|
89% |
331
26.5 IPS |
|
|
Face Detection (SP)
|
100% |
294
3.50 IPS |
|
|
Face Detection (HP)
|
100% |
297
3.53 IPS |
|
|
Face Detection (Q)
|
97% |
657
7.83 IPS |
|
|
Depth Estimation (SP)
|
100% |
254
1.96 IPS |
|
|
Depth Estimation (HP)
|
100% |
255
1.97 IPS |
|
|
Depth Estimation (Q)
|
73% |
708
5.79 IPS |
|
|
Style Transfer (SP)
|
100% |
440
0.57 IPS |
|
|
Style Transfer (HP)
|
100% |
440
0.57 IPS |
|
|
Style Transfer (Q)
|
98% |
1328
1.71 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
126
4.66 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
126
4.66 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
447
16.5 IPS |
|
|
Text Classification (SP)
|
100% |
168
223.7 IPS |
|
|
Text Classification (HP)
|
100% |
167
223.4 IPS |
|
|
Text Classification (Q)
|
91% |
312
420.0 IPS |
|
|
Machine Translation (SP)
|
100% |
285
4.92 IPS |
|
|
Machine Translation (HP)
|
100% |
287
4.94 IPS |
|
|
Machine Translation (Q)
|
57% |
245
5.98 IPS |
