OPPO CPH2737
Geekbench AI Score
1716
Single Precision Score
1712
Half Precision Score
3073
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 23 2025 01:38 PM |
| 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% |
1295
240.8 IPS |
|
|
Image Classification (HP)
|
100% |
1294
240.6 IPS |
|
|
Image Classification (Q)
|
100% |
2311
429.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1403
22.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1394
22.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
2567
41.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2596
3.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
2545
2.97 IPS |
|
|
Pose Estimation (Q)
|
84% |
6261
7.43 IPS |
|
|
Object Detection (SP)
|
98% |
1174
93.4 IPS |
|
|
Object Detection (HP)
|
98% |
1199
95.4 IPS |
|
|
Object Detection (Q)
|
83% |
2007
162.1 IPS |
|
|
Face Detection (SP)
|
100% |
2204
26.2 IPS |
|
|
Face Detection (HP)
|
100% |
2303
27.4 IPS |
|
|
Face Detection (Q)
|
95% |
5229
62.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
2551
19.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2388
18.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
5094
46.7 IPS |
|
|
Style Transfer (SP)
|
89% |
6267
8.13 IPS |
|
|
Style Transfer (HP)
|
89% |
6346
8.24 IPS |
|
|
Style Transfer (Q)
|
98% |
13064
16.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1213
44.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1224
45.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3396
125.8 IPS |
|
|
Text Classification (SP)
|
100% |
732
976.4 IPS |
|
|
Text Classification (HP)
|
99% |
712
950.8 IPS |
|
|
Text Classification (Q)
|
88% |
1341
1.81 KIPS |
|
|
Machine Translation (SP)
|
100% |
1283
22.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1298
22.4 IPS |
|
|
Machine Translation (Q)
|
50% |
636
22.6 IPS |
