OPPO CPH2737
Geekbench AI Score
1785
Single Precision Score
1775
Half Precision Score
3202
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 14 2025 09:42 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 11.21 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1432
266.3 IPS |
|
|
Image Classification (HP)
|
100% |
1415
263.2 IPS |
|
|
Image Classification (Q)
|
100% |
2476
460.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1488
24.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1483
24.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2654
43.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2591
3.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
2441
2.85 IPS |
|
|
Pose Estimation (Q)
|
84% |
6262
7.43 IPS |
|
|
Object Detection (SP)
|
98% |
1261
100.3 IPS |
|
|
Object Detection (HP)
|
98% |
1313
104.5 IPS |
|
|
Object Detection (Q)
|
83% |
2179
176.0 IPS |
|
|
Face Detection (SP)
|
100% |
2489
29.6 IPS |
|
|
Face Detection (HP)
|
100% |
2508
29.8 IPS |
|
|
Face Detection (Q)
|
95% |
5187
61.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
2289
17.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2279
17.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
5184
47.5 IPS |
|
|
Style Transfer (SP)
|
89% |
6265
8.13 IPS |
|
|
Style Transfer (HP)
|
89% |
6304
8.18 IPS |
|
|
Style Transfer (Q)
|
98% |
13464
17.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1221
45.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1186
43.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3524
130.6 IPS |
|
|
Text Classification (SP)
|
100% |
755
1.01 KIPS |
|
|
Text Classification (HP)
|
99% |
757
1.01 KIPS |
|
|
Text Classification (Q)
|
88% |
1413
1.91 KIPS |
|
|
Machine Translation (SP)
|
100% |
1439
24.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1433
24.7 IPS |
|
|
Machine Translation (Q)
|
50% |
702
24.9 IPS |
