OPPO CPH2791
Geekbench AI Score
1436
Single Precision Score
1890
Half Precision Score
1575
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 13 2025 06:04 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% |
489
90.9 IPS |
|
|
Image Classification (HP)
|
100% |
789
146.7 IPS |
|
|
Image Classification (Q)
|
97% |
642
119.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2727
44.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2820
45.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
2483
40.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
11808
13.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
18801
21.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
18184
21.3 IPS |
|
|
Object Detection (SP)
|
100% |
517
41.0 IPS |
|
|
Object Detection (HP)
|
99% |
800
63.5 IPS |
|
|
Object Detection (Q)
|
83% |
768
62.0 IPS |
|
|
Face Detection (SP)
|
100% |
4127
49.0 IPS |
|
|
Face Detection (HP)
|
100% |
4515
53.7 IPS |
|
|
Face Detection (Q)
|
96% |
5387
64.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
4032
31.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
5906
45.6 IPS |
|
|
Depth Estimation (Q)
|
62% |
4606
43.7 IPS |
|
|
Style Transfer (SP)
|
100% |
15951
20.5 IPS |
|
|
Style Transfer (HP)
|
100% |
27639
35.5 IPS |
|
|
Style Transfer (Q)
|
98% |
28140
36.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1825
67.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2251
83.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2353
87.2 IPS |
|
|
Text Classification (SP)
|
35% |
25
225.6 IPS |
|
|
Text Classification (HP)
|
29% |
22
376.5 IPS |
|
|
Text Classification (Q)
|
32% |
23
297.1 IPS |
|
|
Machine Translation (SP)
|
100% |
380
6.54 IPS |
|
|
Machine Translation (HP)
|
100% |
477
8.22 IPS |
|
|
Machine Translation (Q)
|
43% |
112
6.49 IPS |
