OPPO CPH2705
Geekbench AI Score
935
Single Precision Score
934
Half Precision Score
2094
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | March 31 2025 07:01 AM |
| Views | 22 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2705 |
| Model ID | OPPO CPH2705 |
| 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 | 7.30 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
467
86.9 IPS |
|
|
Image Classification (HP)
|
100% |
464
86.3 IPS |
|
|
Image Classification (Q)
|
100% |
1483
275.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
539
8.74 IPS |
|
|
Image Segmentation (HP)
|
100% |
547
8.86 IPS |
|
|
Image Segmentation (Q)
|
98% |
1725
28.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2043
2.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
2043
2.38 IPS |
|
|
Pose Estimation (Q)
|
84% |
3856
4.57 IPS |
|
|
Object Detection (SP)
|
100% |
465
36.9 IPS |
|
|
Object Detection (HP)
|
100% |
462
36.6 IPS |
|
|
Object Detection (Q)
|
83% |
1422
114.9 IPS |
|
|
Face Detection (SP)
|
100% |
1089
12.9 IPS |
|
|
Face Detection (HP)
|
100% |
1090
13.0 IPS |
|
|
Face Detection (Q)
|
95% |
3529
42.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1552
12.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
1549
11.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
3523
32.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3698
4.80 IPS |
|
|
Style Transfer (HP)
|
89% |
3694
4.80 IPS |
|
|
Style Transfer (Q)
|
98% |
8765
11.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
846
31.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
859
31.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2089
77.4 IPS |
|
|
Text Classification (SP)
|
100% |
527
703.9 IPS |
|
|
Text Classification (HP)
|
100% |
514
685.8 IPS |
|
|
Text Classification (Q)
|
88% |
996
1.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
774
13.3 IPS |
|
|
Machine Translation (HP)
|
100% |
768
13.2 IPS |
|
|
Machine Translation (Q)
|
50% |
511
18.1 IPS |
