OPPO CPH2687
Geekbench AI Score
341
Single Precision Score
339
Half Precision Score
392
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | February 01 2026 02:59 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2687 |
| Model ID | OPPO CPH2687 |
| Motherboard | bengal |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.41 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
187
34.8 IPS |
|
|
Image Classification (HP)
|
100% |
187
34.9 IPS |
|
|
Image Classification (Q)
|
100% |
364
67.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
220
3.57 IPS |
|
|
Image Segmentation (HP)
|
100% |
220
3.57 IPS |
|
|
Image Segmentation (Q)
|
98% |
451
7.33 IPS |
|
|
Pose Estimation (SP)
|
100% |
881
1.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
819
0.96 IPS |
|
|
Pose Estimation (Q)
|
84% |
732
0.87 IPS |
|
|
Object Detection (SP)
|
100% |
177
14.0 IPS |
|
|
Object Detection (HP)
|
100% |
172
13.6 IPS |
|
|
Object Detection (Q)
|
83% |
335
27.1 IPS |
|
|
Face Detection (SP)
|
100% |
461
5.48 IPS |
|
|
Face Detection (HP)
|
100% |
481
5.72 IPS |
|
|
Face Detection (Q)
|
95% |
783
9.35 IPS |
|
|
Depth Estimation (SP)
|
100% |
718
5.53 IPS |
|
|
Depth Estimation (HP)
|
99% |
710
5.47 IPS |
|
|
Depth Estimation (Q)
|
64% |
755
6.92 IPS |
|
|
Style Transfer (SP)
|
89% |
1480
1.92 IPS |
|
|
Style Transfer (HP)
|
89% |
1494
1.94 IPS |
|
|
Style Transfer (Q)
|
98% |
1761
2.27 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
321
11.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
312
11.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
178
6.61 IPS |
|
|
Text Classification (SP)
|
100% |
115
154.0 IPS |
|
|
Text Classification (HP)
|
100% |
115
153.8 IPS |
|
|
Text Classification (Q)
|
88% |
126
169.3 IPS |
|
|
Machine Translation (SP)
|
100% |
187
3.22 IPS |
|
|
Machine Translation (HP)
|
100% |
192
3.30 IPS |
|
|
Machine Translation (Q)
|
50% |
93
3.31 IPS |
