OPPO CPH2699
Geekbench AI Score
804
Single Precision Score
757
Half Precision Score
1181
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | sebeg_the_tea_boii |
| Upload Date | March 28 2025 11:06 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2699 |
| Model ID | OPPO CPH2699 |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 11.14 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
411
76.4 IPS |
|
|
Image Classification (HP)
|
100% |
408
75.8 IPS |
|
|
Image Classification (Q)
|
100% |
1273
236.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
496
8.04 IPS |
|
|
Image Segmentation (HP)
|
100% |
505
8.19 IPS |
|
|
Image Segmentation (Q)
|
98% |
1492
24.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1882
2.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
1872
2.18 IPS |
|
|
Pose Estimation (Q)
|
84% |
3410
4.04 IPS |
|
|
Object Detection (SP)
|
100% |
421
33.4 IPS |
|
|
Object Detection (HP)
|
100% |
235
18.6 IPS |
|
|
Object Detection (Q)
|
83% |
991
80.1 IPS |
|
|
Face Detection (SP)
|
100% |
1049
12.5 IPS |
|
|
Face Detection (HP)
|
100% |
1053
12.5 IPS |
|
|
Face Detection (Q)
|
95% |
1265
15.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
769
5.93 IPS |
|
|
Depth Estimation (HP)
|
99% |
783
6.03 IPS |
|
|
Depth Estimation (Q)
|
64% |
3058
28.0 IPS |
|
|
Style Transfer (SP)
|
89% |
3385
4.39 IPS |
|
|
Style Transfer (HP)
|
89% |
3319
4.31 IPS |
|
|
Style Transfer (Q)
|
98% |
7808
10.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
817
30.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
819
30.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1771
65.6 IPS |
|
|
Text Classification (SP)
|
100% |
457
609.9 IPS |
|
|
Text Classification (HP)
|
100% |
451
601.9 IPS |
|
|
Text Classification (Q)
|
88% |
669
902.7 IPS |
|
|
Machine Translation (SP)
|
100% |
687
11.8 IPS |
|
|
Machine Translation (HP)
|
100% |
675
11.6 IPS |
|
|
Machine Translation (Q)
|
50% |
23
0.82 IPS |
