OPPO CPH2737
Geekbench AI Score
927
Single Precision Score
1243
Half Precision Score
990
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 14 2025 09:47 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
491
91.3 IPS |
|
|
Image Classification (HP)
|
100% |
500
93.0 IPS |
|
|
Image Classification (Q)
|
97% |
406
75.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1217
19.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2181
35.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
3027
49.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6719
7.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
11164
13.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
10175
11.9 IPS |
|
|
Object Detection (SP)
|
100% |
379
30.1 IPS |
|
|
Object Detection (HP)
|
99% |
541
42.9 IPS |
|
|
Object Detection (Q)
|
83% |
525
42.4 IPS |
|
|
Face Detection (SP)
|
100% |
1883
22.4 IPS |
|
|
Face Detection (HP)
|
100% |
2394
28.4 IPS |
|
|
Face Detection (Q)
|
96% |
2784
33.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
2657
20.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
4692
36.3 IPS |
|
|
Depth Estimation (Q)
|
62% |
2949
28.0 IPS |
|
|
Style Transfer (SP)
|
100% |
10484
13.5 IPS |
|
|
Style Transfer (HP)
|
100% |
17188
22.1 IPS |
|
|
Style Transfer (Q)
|
98% |
15509
20.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1257
46.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1485
54.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1304
48.3 IPS |
|
|
Text Classification (SP)
|
35% |
14
125.3 IPS |
|
|
Text Classification (HP)
|
29% |
15
253.6 IPS |
|
|
Text Classification (Q)
|
32% |
11
138.1 IPS |
|
|
Machine Translation (SP)
|
100% |
337
5.81 IPS |
|
|
Machine Translation (HP)
|
100% |
311
5.36 IPS |
|
|
Machine Translation (Q)
|
43% |
76
4.43 IPS |
