OPPO CPH2791
Geekbench AI Score
1620
Single Precision Score
2140
Half Precision Score
1784
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 13 2025 09:38 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | OPPO CPH2791 |
| Model ID | OPPO CPH2791 |
| Motherboard | k6993v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3468 revision 0 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 4 Cores @ 2.70 GHz |
| Cluster 2 | 3 Cores @ 3.50 GHz |
| Cluster 3 | 1 Core @ 4.21 GHz |
| Memory Information | |
|---|---|
| Size | 14.93 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
688
127.9 IPS |
|
|
Image Classification (HP)
|
100% |
920
171.2 IPS |
|
|
Image Classification (Q)
|
97% |
870
162.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2325
37.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2780
45.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
2425
39.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
11715
13.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
19878
23.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
18839
22.1 IPS |
|
|
Object Detection (SP)
|
100% |
582
46.1 IPS |
|
|
Object Detection (HP)
|
99% |
992
78.7 IPS |
|
|
Object Detection (Q)
|
83% |
940
75.9 IPS |
|
|
Face Detection (SP)
|
100% |
3846
45.7 IPS |
|
|
Face Detection (HP)
|
100% |
5070
60.2 IPS |
|
|
Face Detection (Q)
|
96% |
4420
52.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
4392
33.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
6608
51.1 IPS |
|
|
Depth Estimation (Q)
|
62% |
5050
48.0 IPS |
|
|
Style Transfer (SP)
|
100% |
17006
21.9 IPS |
|
|
Style Transfer (HP)
|
100% |
29178
37.5 IPS |
|
|
Style Transfer (Q)
|
98% |
28045
36.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2324
85.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3308
122.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3484
129.1 IPS |
|
|
Text Classification (SP)
|
35% |
32
293.9 IPS |
|
|
Text Classification (HP)
|
29% |
20
344.3 IPS |
|
|
Text Classification (Q)
|
32% |
27
348.4 IPS |
|
|
Machine Translation (SP)
|
100% |
536
9.23 IPS |
|
|
Machine Translation (HP)
|
100% |
618
10.6 IPS |
|
|
Machine Translation (Q)
|
43% |
149
8.68 IPS |
