OPPO CPH2689
Geekbench AI Score
1600
Single Precision Score
1600
Half Precision Score
2039
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 26 2024 04:05 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2689 |
| Model ID | OPPO CPH2689 |
| Motherboard | k6897v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 0 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores @ 2.20 GHz |
| Cluster 2 | 3 Cores @ 3.20 GHz |
| Cluster 3 | 1 Core @ 3.35 GHz |
| Memory Information | |
|---|---|
| Size | 11.21 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1425
265.0 IPS |
|
|
Image Classification (HP)
|
100% |
1385
257.6 IPS |
|
|
Image Classification (Q)
|
100% |
1796
334.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1515
24.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1490
24.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2149
34.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2438
2.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
2378
2.77 IPS |
|
|
Pose Estimation (Q)
|
84% |
5731
6.80 IPS |
|
|
Object Detection (SP)
|
98% |
867
69.0 IPS |
|
|
Object Detection (HP)
|
98% |
954
75.9 IPS |
|
|
Object Detection (Q)
|
83% |
1548
125.0 IPS |
|
|
Face Detection (SP)
|
100% |
2323
27.6 IPS |
|
|
Face Detection (HP)
|
100% |
2359
28.0 IPS |
|
|
Face Detection (Q)
|
95% |
3680
43.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
2236
17.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2256
17.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
3032
27.8 IPS |
|
|
Style Transfer (SP)
|
89% |
6215
8.07 IPS |
|
|
Style Transfer (HP)
|
89% |
6296
8.17 IPS |
|
|
Style Transfer (Q)
|
98% |
11383
14.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
927
34.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
897
33.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1733
64.2 IPS |
|
|
Text Classification (SP)
|
100% |
622
830.5 IPS |
|
|
Text Classification (HP)
|
99% |
614
819.7 IPS |
|
|
Text Classification (Q)
|
88% |
506
682.3 IPS |
|
|
Machine Translation (SP)
|
100% |
1298
22.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1278
22.0 IPS |
|
|
Machine Translation (Q)
|
50% |
326
11.6 IPS |
