OPPO CPH2797
Geekbench AI Score
1503
Single Precision Score
1914
Half Precision Score
1649
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 17 2025 08:54 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | OPPO CPH2797 |
| Model ID | OPPO CPH2797 |
| 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 | 11.03 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
523
97.3 IPS |
|
|
Image Classification (HP)
|
100% |
794
147.6 IPS |
|
|
Image Classification (Q)
|
97% |
794
148.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2125
34.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2607
42.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
2306
37.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
12157
14.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
21750
25.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
20038
23.5 IPS |
|
|
Object Detection (SP)
|
100% |
535
42.4 IPS |
|
|
Object Detection (HP)
|
99% |
880
69.8 IPS |
|
|
Object Detection (Q)
|
83% |
817
66.0 IPS |
|
|
Face Detection (SP)
|
100% |
3159
37.5 IPS |
|
|
Face Detection (HP)
|
100% |
4410
52.4 IPS |
|
|
Face Detection (Q)
|
96% |
4181
49.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5243
40.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
5793
44.8 IPS |
|
|
Depth Estimation (Q)
|
62% |
4947
47.0 IPS |
|
|
Style Transfer (SP)
|
100% |
16334
21.0 IPS |
|
|
Style Transfer (HP)
|
100% |
27099
34.8 IPS |
|
|
Style Transfer (Q)
|
98% |
26533
34.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2435
89.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2746
101.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2880
106.7 IPS |
|
|
Text Classification (SP)
|
35% |
29
267.7 IPS |
|
|
Text Classification (HP)
|
29% |
18
305.2 IPS |
|
|
Text Classification (Q)
|
32% |
26
333.3 IPS |
|
|
Machine Translation (SP)
|
100% |
427
7.36 IPS |
|
|
Machine Translation (HP)
|
100% |
488
8.41 IPS |
|
|
Machine Translation (Q)
|
43% |
121
7.05 IPS |
