OPPO CPH2629
Geekbench AI Score
564
Single Precision Score
562
Half Precision Score
1018
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 09 2024 09:00 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO CPH2629 |
| Model ID | OPPO CPH2629 |
| Motherboard | k6878v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.50 GHz |
| Memory Information | |
|---|---|
| Size | 11.18 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
231
43.0 IPS |
|
|
Image Classification (HP)
|
100% |
229
42.5 IPS |
|
|
Image Classification (Q)
|
100% |
689
128.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
316
5.13 IPS |
|
|
Image Segmentation (HP)
|
100% |
315
5.10 IPS |
|
|
Image Segmentation (Q)
|
98% |
808
13.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1360
1.59 IPS |
|
|
Pose Estimation (HP)
|
100% |
1455
1.70 IPS |
|
|
Pose Estimation (Q)
|
84% |
1882
2.23 IPS |
|
|
Object Detection (SP)
|
100% |
236
18.7 IPS |
|
|
Object Detection (HP)
|
100% |
234
18.5 IPS |
|
|
Object Detection (Q)
|
83% |
671
54.2 IPS |
|
|
Face Detection (SP)
|
100% |
770
9.15 IPS |
|
|
Face Detection (HP)
|
100% |
653
7.76 IPS |
|
|
Face Detection (Q)
|
95% |
1766
21.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1076
8.29 IPS |
|
|
Depth Estimation (HP)
|
99% |
1069
8.23 IPS |
|
|
Depth Estimation (Q)
|
64% |
1647
15.1 IPS |
|
|
Style Transfer (SP)
|
89% |
2100
2.73 IPS |
|
|
Style Transfer (HP)
|
89% |
2012
2.61 IPS |
|
|
Style Transfer (Q)
|
98% |
4225
5.45 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
597
22.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
592
21.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1003
37.2 IPS |
|
|
Text Classification (SP)
|
100% |
263
350.6 IPS |
|
|
Text Classification (HP)
|
100% |
262
349.2 IPS |
|
|
Text Classification (Q)
|
88% |
476
641.4 IPS |
|
|
Machine Translation (SP)
|
100% |
516
8.89 IPS |
|
|
Machine Translation (HP)
|
100% |
593
10.2 IPS |
|
|
Machine Translation (Q)
|
50% |
290
10.3 IPS |
