OPPO CPH2797
Geekbench AI Score
1416
Single Precision Score
1824
Half Precision Score
1643
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 28 2025 12:51 PM |
| Views | 1 |
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 | 14.93 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
546
101.5 IPS |
|
|
Image Classification (HP)
|
100% |
828
154.0 IPS |
|
|
Image Classification (Q)
|
97% |
1089
203.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2048
33.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2172
35.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2311
37.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
11722
13.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
19153
22.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
18292
21.4 IPS |
|
|
Object Detection (SP)
|
100% |
611
48.4 IPS |
|
|
Object Detection (HP)
|
99% |
830
65.8 IPS |
|
|
Object Detection (Q)
|
83% |
1021
82.5 IPS |
|
|
Face Detection (SP)
|
100% |
3257
38.7 IPS |
|
|
Face Detection (HP)
|
100% |
4324
51.4 IPS |
|
|
Face Detection (Q)
|
96% |
4067
48.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
3938
30.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
5798
44.8 IPS |
|
|
Depth Estimation (Q)
|
62% |
4339
41.2 IPS |
|
|
Style Transfer (SP)
|
100% |
16551
21.3 IPS |
|
|
Style Transfer (HP)
|
100% |
26504
34.1 IPS |
|
|
Style Transfer (Q)
|
98% |
26265
33.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1726
63.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2201
81.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2204
81.7 IPS |
|
|
Text Classification (SP)
|
35% |
26
234.4 IPS |
|
|
Text Classification (HP)
|
29% |
21
371.3 IPS |
|
|
Text Classification (Q)
|
32% |
28
359.2 IPS |
|
|
Machine Translation (SP)
|
100% |
426
7.34 IPS |
|
|
Machine Translation (HP)
|
100% |
465
8.01 IPS |
|
|
Machine Translation (Q)
|
43% |
107
6.21 IPS |
