OPPO CPH2689
Geekbench AI Score
1097
Single Precision Score
4208
Half Precision Score
4465
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 26 2024 10:53 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
954
177.3 IPS |
|
|
Image Classification (HP)
|
100% |
3963
737.0 IPS |
|
|
Image Classification (Q)
|
99% |
7268
1.36 KIPS |
|
|
Image Segmentation (SP)
|
100% |
664
10.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
3976
64.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
1785
29.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
8995
10.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
17677
20.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
72954
85.5 IPS |
|
|
Object Detection (SP)
|
100% |
640
50.8 IPS |
|
|
Object Detection (HP)
|
100% |
4185
331.9 IPS |
|
|
Object Detection (Q)
|
86% |
4972
399.9 IPS |
|
|
Face Detection (SP)
|
100% |
3399
40.4 IPS |
|
|
Face Detection (HP)
|
100% |
10121
120.3 IPS |
|
|
Face Detection (Q)
|
97% |
11186
133.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
874
6.73 IPS |
|
|
Depth Estimation (HP)
|
99% |
18951
146.0 IPS |
|
|
Depth Estimation (Q)
|
62% |
30783
292.3 IPS |
|
|
Style Transfer (SP)
|
100% |
3335
4.29 IPS |
|
|
Style Transfer (HP)
|
100% |
397
0.51 IPS |
|
|
Style Transfer (Q)
|
30% |
497
7.49 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2435
89.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
10149
374.8 IPS |
|
|
Image Super-Resolution (Q)
|
41% |
6763
985.0 IPS |
|
|
Text Classification (SP)
|
100% |
89
118.3 IPS |
|
|
Text Classification (HP)
|
100% |
1488
1.99 KIPS |
|
|
Text Classification (Q)
|
93% |
1501
2.02 KIPS |
|
|
Machine Translation (SP)
|
100% |
323
5.56 IPS |
|
|
Machine Translation (HP)
|
100% |
1299
22.4 IPS |
|
|
Machine Translation (Q)
|
60% |
386
8.70 IPS |
