OPPO CPH2737
Geekbench AI Score
1272
Single Precision Score
1073
Half Precision Score
1946
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 10 2025 06:10 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | OPPO CPH2737 |
| Model ID | OPPO CPH2737 |
| Motherboard | k6897v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 0 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores @ 2.20 GHz |
| Cluster 2 | 3 Cores @ 3.20 GHz |
| Cluster 3 | 1 Core @ 3.35 GHz |
| Memory Information | |
|---|---|
| Size | 7.30 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1311
243.8 IPS |
|
|
Image Classification (HP)
|
100% |
1371
255.0 IPS |
|
|
Image Classification (Q)
|
100% |
1664
309.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1035
16.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
452
7.33 IPS |
|
|
Image Segmentation (Q)
|
98% |
1848
30.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1933
2.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
1903
2.22 IPS |
|
|
Pose Estimation (Q)
|
84% |
4485
5.32 IPS |
|
|
Object Detection (SP)
|
98% |
768
61.1 IPS |
|
|
Object Detection (HP)
|
98% |
619
49.2 IPS |
|
|
Object Detection (Q)
|
83% |
1312
106.0 IPS |
|
|
Face Detection (SP)
|
100% |
2042
24.3 IPS |
|
|
Face Detection (HP)
|
100% |
987
11.7 IPS |
|
|
Face Detection (Q)
|
95% |
1779
21.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
1855
14.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
1900
14.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
3273
30.0 IPS |
|
|
Style Transfer (SP)
|
89% |
4589
5.96 IPS |
|
|
Style Transfer (HP)
|
89% |
5088
6.60 IPS |
|
|
Style Transfer (Q)
|
98% |
8812
11.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
853
31.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
874
32.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2123
78.7 IPS |
|
|
Text Classification (SP)
|
100% |
413
551.3 IPS |
|
|
Text Classification (HP)
|
99% |
358
477.8 IPS |
|
|
Text Classification (Q)
|
88% |
814
1.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
903
15.6 IPS |
|
|
Machine Translation (HP)
|
100% |
935
16.1 IPS |
|
|
Machine Translation (Q)
|
50% |
487
17.3 IPS |
