OPPO CPH2659
Geekbench AI Score
1719
Single Precision Score
1723
Half Precision Score
2030
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 18 2024 02:09 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2659 |
| Model ID | OPPO CPH2659 |
| Motherboard | k6991v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 1 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 4 Cores @ 2.40 GHz |
| Cluster 2 | 3 Cores @ 3.30 GHz |
| Cluster 3 | 1 Core @ 3.63 GHz |
| Memory Information | |
|---|---|
| Size | 15.03 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1661
308.9 IPS |
|
|
Image Classification (HP)
|
100% |
1780
331.1 IPS |
|
|
Image Classification (Q)
|
100% |
2623
487.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2117
34.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2095
34.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2980
48.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
3631
4.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
3549
4.14 IPS |
|
|
Pose Estimation (Q)
|
84% |
4082
4.84 IPS |
|
|
Object Detection (SP)
|
98% |
848
67.5 IPS |
|
|
Object Detection (HP)
|
98% |
827
65.8 IPS |
|
|
Object Detection (Q)
|
83% |
1270
102.6 IPS |
|
|
Face Detection (SP)
|
100% |
2054
24.4 IPS |
|
|
Face Detection (HP)
|
100% |
2036
24.2 IPS |
|
|
Face Detection (Q)
|
95% |
2976
35.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
2586
20.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
2620
20.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
3195
29.3 IPS |
|
|
Style Transfer (SP)
|
89% |
5376
6.98 IPS |
|
|
Style Transfer (HP)
|
89% |
5382
6.99 IPS |
|
|
Style Transfer (Q)
|
98% |
8864
11.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1180
43.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1188
43.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1917
71.0 IPS |
|
|
Text Classification (SP)
|
100% |
477
636.9 IPS |
|
|
Text Classification (HP)
|
99% |
468
625.3 IPS |
|
|
Text Classification (Q)
|
88% |
516
695.5 IPS |
|
|
Machine Translation (SP)
|
100% |
1301
22.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1324
22.8 IPS |
|
|
Machine Translation (Q)
|
50% |
353
12.5 IPS |
