OPPO CPH2651
Geekbench AI Score
1259
Single Precision Score
1788
Half Precision Score
1413
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 13 2025 03:31 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | OPPO CPH2651 |
| Model ID | OPPO CPH2651 |
| Motherboard | k6991v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 1 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 4 Cores @ 2.40 GHz |
| Cluster 2 | 3 Cores @ 3.30 GHz |
| Cluster 3 | 1 Core @ 3.63 GHz |
| Memory Information | |
|---|---|
| Size | 11.11 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
463
86.1 IPS |
|
|
Image Classification (HP)
|
100% |
802
149.2 IPS |
|
|
Image Classification (Q)
|
97% |
659
123.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1747
28.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2666
43.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2214
36.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
8723
10.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
15626
18.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
14577
17.1 IPS |
|
|
Object Detection (SP)
|
100% |
532
42.2 IPS |
|
|
Object Detection (HP)
|
99% |
765
60.7 IPS |
|
|
Object Detection (Q)
|
83% |
746
60.3 IPS |
|
|
Face Detection (SP)
|
100% |
3006
35.7 IPS |
|
|
Face Detection (HP)
|
100% |
4244
50.4 IPS |
|
|
Face Detection (Q)
|
96% |
3788
45.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
3666
28.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
5515
42.6 IPS |
|
|
Depth Estimation (Q)
|
62% |
4419
42.0 IPS |
|
|
Style Transfer (SP)
|
100% |
13859
17.8 IPS |
|
|
Style Transfer (HP)
|
100% |
24745
31.8 IPS |
|
|
Style Transfer (Q)
|
98% |
25236
32.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1790
66.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2494
92.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2230
82.6 IPS |
|
|
Text Classification (SP)
|
35% |
24
216.4 IPS |
|
|
Text Classification (HP)
|
29% |
18
312.7 IPS |
|
|
Text Classification (Q)
|
32% |
18
238.5 IPS |
|
|
Machine Translation (SP)
|
100% |
409
7.04 IPS |
|
|
Machine Translation (HP)
|
100% |
504
8.67 IPS |
|
|
Machine Translation (Q)
|
43% |
118
6.86 IPS |
