OPPO CPH2761
Geekbench AI Score
1104
Single Precision Score
1399
Half Precision Score
1105
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 29 2025 04:52 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2761 |
| Model ID | OPPO CPH2761 |
| Motherboard | k6899v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3463 revision 1 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 4 Cores @ 2.10 GHz |
| Cluster 2 | 3 Cores @ 3.00 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 7.29 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
610
113.5 IPS |
|
|
Image Classification (HP)
|
100% |
611
113.7 IPS |
|
|
Image Classification (Q)
|
97% |
572
106.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1375
22.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1884
30.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
1604
26.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
8615
10.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
12402
14.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
13980
16.4 IPS |
|
|
Object Detection (SP)
|
100% |
528
41.9 IPS |
|
|
Object Detection (HP)
|
99% |
628
49.8 IPS |
|
|
Object Detection (Q)
|
83% |
593
47.9 IPS |
|
|
Face Detection (SP)
|
100% |
2706
32.2 IPS |
|
|
Face Detection (HP)
|
100% |
2747
32.6 IPS |
|
|
Face Detection (Q)
|
96% |
2714
32.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
3061
23.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
6884
53.2 IPS |
|
|
Depth Estimation (Q)
|
62% |
5470
52.0 IPS |
|
|
Style Transfer (SP)
|
100% |
11238
14.4 IPS |
|
|
Style Transfer (HP)
|
100% |
23934
30.8 IPS |
|
|
Style Transfer (Q)
|
98% |
23470
30.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1836
67.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2489
91.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1487
55.1 IPS |
|
|
Text Classification (SP)
|
35% |
14
129.6 IPS |
|
|
Text Classification (HP)
|
29% |
9
153.8 IPS |
|
|
Text Classification (Q)
|
29% |
9
150.6 IPS |
|
|
Machine Translation (SP)
|
100% |
296
5.11 IPS |
|
|
Machine Translation (HP)
|
100% |
317
5.47 IPS |
|
|
Machine Translation (Q)
|
43% |
77
4.45 IPS |
