OPPO CPH2699
Geekbench AI Score
128
Single Precision Score
128
Half Precision Score
358
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | sebeg_the_tea_boii |
| Upload Date | March 28 2025 01:47 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2699 |
| Model ID | OPPO CPH2699 |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 11.14 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
74
13.7 IPS |
|
|
Image Classification (HP)
|
100% |
74
13.8 IPS |
|
|
Image Classification (Q)
|
99% |
231
43.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
101
1.64 IPS |
|
|
Image Segmentation (HP)
|
100% |
102
1.65 IPS |
|
|
Image Segmentation (Q)
|
98% |
274
4.46 IPS |
|
|
Pose Estimation (SP)
|
100% |
128
0.15 IPS |
|
|
Pose Estimation (HP)
|
100% |
128
0.15 IPS |
|
|
Pose Estimation (Q)
|
98% |
517
0.61 IPS |
|
|
Object Detection (SP)
|
100% |
72
5.75 IPS |
|
|
Object Detection (HP)
|
100% |
73
5.77 IPS |
|
|
Object Detection (Q)
|
87% |
241
19.4 IPS |
|
|
Face Detection (SP)
|
100% |
213
2.53 IPS |
|
|
Face Detection (HP)
|
100% |
215
2.56 IPS |
|
|
Face Detection (Q)
|
97% |
569
6.78 IPS |
|
|
Depth Estimation (SP)
|
100% |
169
1.30 IPS |
|
|
Depth Estimation (HP)
|
99% |
170
1.31 IPS |
|
|
Depth Estimation (Q)
|
64% |
472
4.28 IPS |
|
|
Style Transfer (SP)
|
100% |
310
0.40 IPS |
|
|
Style Transfer (HP)
|
100% |
309
0.40 IPS |
|
|
Style Transfer (Q)
|
98% |
974
1.26 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
80
2.94 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
80
2.95 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
304
11.2 IPS |
|
|
Text Classification (SP)
|
100% |
107
143.1 IPS |
|
|
Text Classification (HP)
|
100% |
107
142.9 IPS |
|
|
Text Classification (Q)
|
91% |
252
338.7 IPS |
|
|
Machine Translation (SP)
|
100% |
185
3.19 IPS |
|
|
Machine Translation (HP)
|
100% |
185
3.19 IPS |
|
|
Machine Translation (Q)
|
57% |
225
5.51 IPS |
