OPPO CPH2737
Geekbench AI Score
915
Single Precision Score
1139
Half Precision Score
889
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 06 2025 05:47 PM |
| Views | 4 |
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% |
421
78.2 IPS |
|
|
Image Classification (HP)
|
100% |
490
91.1 IPS |
|
|
Image Classification (Q)
|
97% |
392
73.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1385
22.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2230
36.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1566
25.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6762
7.89 IPS |
|
|
Pose Estimation (HP)
|
100% |
11715
13.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
9895
11.6 IPS |
|
|
Object Detection (SP)
|
100% |
377
29.9 IPS |
|
|
Object Detection (HP)
|
99% |
519
41.2 IPS |
|
|
Object Detection (Q)
|
83% |
492
39.8 IPS |
|
|
Face Detection (SP)
|
100% |
1861
22.1 IPS |
|
|
Face Detection (HP)
|
100% |
2357
28.0 IPS |
|
|
Face Detection (Q)
|
96% |
2196
26.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
2950
22.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
3806
29.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
2834
26.9 IPS |
|
|
Style Transfer (SP)
|
100% |
10934
14.1 IPS |
|
|
Style Transfer (HP)
|
100% |
15459
19.9 IPS |
|
|
Style Transfer (Q)
|
98% |
14891
19.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1133
41.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1415
52.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1343
49.8 IPS |
|
|
Text Classification (SP)
|
35% |
15
137.0 IPS |
|
|
Text Classification (HP)
|
29% |
9
147.8 IPS |
|
|
Text Classification (Q)
|
32% |
11
142.2 IPS |
|
|
Machine Translation (SP)
|
100% |
274
4.72 IPS |
|
|
Machine Translation (HP)
|
100% |
315
5.43 IPS |
|
|
Machine Translation (Q)
|
43% |
76
4.44 IPS |
