OPPO CPH2519
Geekbench AI Score
448
Single Precision Score
2004
Half Precision Score
2488
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 28 2024 10:20 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2519 |
| Model ID | OPPO CPH2519 |
| Motherboard | k6985v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.05 GHz |
| Memory Information | |
|---|---|
| Size | 11.10 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
557
103.7 IPS |
|
|
Image Classification (HP)
|
100% |
2050
381.2 IPS |
|
|
Image Classification (Q)
|
99% |
3584
668.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
381
6.18 IPS |
|
|
Image Segmentation (HP)
|
100% |
2245
36.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
1237
20.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
3116
3.64 IPS |
|
|
Pose Estimation (HP)
|
100% |
8161
9.52 IPS |
|
|
Pose Estimation (Q)
|
95% |
32560
38.2 IPS |
|
|
Object Detection (SP)
|
100% |
417
33.1 IPS |
|
|
Object Detection (HP)
|
100% |
2022
160.4 IPS |
|
|
Object Detection (Q)
|
86% |
2864
230.4 IPS |
|
|
Face Detection (SP)
|
28% |
100
18.6 IPS |
|
|
Face Detection (HP)
|
100% |
6317
75.1 IPS |
|
|
Face Detection (Q)
|
97% |
9350
111.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
740
5.70 IPS |
|
|
Depth Estimation (HP)
|
99% |
9678
74.6 IPS |
|
|
Depth Estimation (Q)
|
62% |
20121
191.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1805
2.32 IPS |
|
|
Style Transfer (HP)
|
100% |
536
0.69 IPS |
|
|
Style Transfer (Q)
|
30% |
324
4.88 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1113
41.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4769
176.1 IPS |
|
|
Image Super-Resolution (Q)
|
41% |
3274
476.9 IPS |
|
|
Text Classification (SP)
|
100% |
40
53.6 IPS |
|
|
Text Classification (HP)
|
100% |
251
334.6 IPS |
|
|
Text Classification (Q)
|
93% |
447
600.1 IPS |
|
|
Machine Translation (SP)
|
100% |
200
3.45 IPS |
|
|
Machine Translation (HP)
|
100% |
352
6.06 IPS |
|
|
Machine Translation (Q)
|
60% |
247
5.56 IPS |
