OPPO CPH2791
Geekbench AI Score
1349
Single Precision Score
1841
Half Precision Score
1543
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 18 2025 10:33 PM |
| Views | 5 |
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% |
601
111.8 IPS |
|
|
Image Classification (HP)
|
100% |
921
171.2 IPS |
|
|
Image Classification (Q)
|
97% |
1182
220.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1716
27.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2284
37.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2558
41.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
11130
13.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
19137
22.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
15570
18.2 IPS |
|
|
Object Detection (SP)
|
100% |
497
39.5 IPS |
|
|
Object Detection (HP)
|
99% |
839
66.6 IPS |
|
|
Object Detection (Q)
|
83% |
765
61.8 IPS |
|
|
Face Detection (SP)
|
100% |
2672
31.7 IPS |
|
|
Face Detection (HP)
|
100% |
4465
53.1 IPS |
|
|
Face Detection (Q)
|
96% |
2989
35.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
4011
30.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
5558
42.9 IPS |
|
|
Depth Estimation (Q)
|
62% |
4164
39.6 IPS |
|
|
Style Transfer (SP)
|
100% |
15951
20.5 IPS |
|
|
Style Transfer (HP)
|
100% |
27281
35.1 IPS |
|
|
Style Transfer (Q)
|
98% |
26659
34.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2180
80.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2131
78.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2551
94.5 IPS |
|
|
Text Classification (SP)
|
35% |
28
255.6 IPS |
|
|
Text Classification (HP)
|
29% |
23
390.2 IPS |
|
|
Text Classification (Q)
|
32% |
26
329.6 IPS |
|
|
Machine Translation (SP)
|
100% |
337
5.80 IPS |
|
|
Machine Translation (HP)
|
100% |
401
6.90 IPS |
|
|
Machine Translation (Q)
|
43% |
97
5.61 IPS |
