OPPO CPH2701
Geekbench AI Score
506
Single Precision Score
500
Half Precision Score
911
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | February 07 2026 04:20 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2701 |
| Model ID | OPPO CPH2701 |
| Motherboard | k6789v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 7.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
221
41.1 IPS |
|
|
Image Classification (HP)
|
100% |
221
41.2 IPS |
|
|
Image Classification (Q)
|
100% |
570
106.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
279
4.52 IPS |
|
|
Image Segmentation (HP)
|
100% |
279
4.52 IPS |
|
|
Image Segmentation (Q)
|
98% |
703
11.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1084
1.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
1064
1.24 IPS |
|
|
Pose Estimation (Q)
|
84% |
1574
1.87 IPS |
|
|
Object Detection (SP)
|
100% |
223
17.7 IPS |
|
|
Object Detection (HP)
|
100% |
223
17.7 IPS |
|
|
Object Detection (Q)
|
83% |
623
50.3 IPS |
|
|
Face Detection (SP)
|
100% |
708
8.41 IPS |
|
|
Face Detection (HP)
|
100% |
708
8.41 IPS |
|
|
Face Detection (Q)
|
95% |
1446
17.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
928
7.15 IPS |
|
|
Depth Estimation (HP)
|
99% |
886
6.82 IPS |
|
|
Depth Estimation (Q)
|
64% |
1445
13.2 IPS |
|
|
Style Transfer (SP)
|
89% |
1832
2.38 IPS |
|
|
Style Transfer (HP)
|
89% |
1819
2.36 IPS |
|
|
Style Transfer (Q)
|
98% |
3617
4.66 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
486
18.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
484
17.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
870
32.3 IPS |
|
|
Text Classification (SP)
|
100% |
271
361.8 IPS |
|
|
Text Classification (HP)
|
100% |
268
357.8 IPS |
|
|
Text Classification (Q)
|
88% |
476
641.5 IPS |
|
|
Machine Translation (SP)
|
100% |
466
8.03 IPS |
|
|
Machine Translation (HP)
|
100% |
457
7.87 IPS |
|
|
Machine Translation (Q)
|
50% |
322
11.4 IPS |
