OPPO CPH2737
Geekbench AI Score
1803
Single Precision Score
1799
Half Precision Score
3236
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 06 2025 04:54 PM |
| Views | 6 |
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% |
1422
264.5 IPS |
|
|
Image Classification (HP)
|
100% |
1423
264.6 IPS |
|
|
Image Classification (Q)
|
100% |
2438
453.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1437
23.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1429
23.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2583
42.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2598
3.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
2582
3.01 IPS |
|
|
Pose Estimation (Q)
|
84% |
6431
7.63 IPS |
|
|
Object Detection (SP)
|
98% |
1269
101.0 IPS |
|
|
Object Detection (HP)
|
98% |
1346
107.1 IPS |
|
|
Object Detection (Q)
|
83% |
2181
176.2 IPS |
|
|
Face Detection (SP)
|
100% |
2458
29.2 IPS |
|
|
Face Detection (HP)
|
100% |
2460
29.2 IPS |
|
|
Face Detection (Q)
|
95% |
5299
63.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
2497
19.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2366
18.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
5343
48.9 IPS |
|
|
Style Transfer (SP)
|
89% |
6422
8.34 IPS |
|
|
Style Transfer (HP)
|
89% |
6415
8.33 IPS |
|
|
Style Transfer (Q)
|
98% |
13635
17.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1239
45.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1252
46.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3605
133.6 IPS |
|
|
Text Classification (SP)
|
100% |
741
988.6 IPS |
|
|
Text Classification (HP)
|
99% |
752
1.00 KIPS |
|
|
Text Classification (Q)
|
88% |
1421
1.92 KIPS |
|
|
Machine Translation (SP)
|
100% |
1494
25.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1430
24.6 IPS |
|
|
Machine Translation (Q)
|
50% |
722
25.6 IPS |
