OnePlus CPH2747
Geekbench AI Score
525
Single Precision Score
514
Half Precision Score
1221
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | iClondike |
| Upload Date | January 24 2026 04:27 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | OnePlus CPH2747 |
| Model ID | OnePlus CPH2747 |
| Motherboard | canoe |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 2 revision 1 |
| Base Frequency | 3.63 GHz |
| Cluster 1 | 6 Cores @ 3.63 GHz |
| Cluster 2 | 2 Cores @ 4.61 GHz |
| Memory Information | |
|---|---|
| Size | 14.76 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
366
68.0 IPS |
|
|
Image Classification (HP)
|
100% |
370
68.9 IPS |
|
|
Image Classification (Q)
|
99% |
867
161.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
404
6.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
390
6.32 IPS |
|
|
Image Segmentation (Q)
|
98% |
809
13.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
489
0.57 IPS |
|
|
Pose Estimation (HP)
|
100% |
489
0.57 IPS |
|
|
Pose Estimation (Q)
|
98% |
1905
2.23 IPS |
|
|
Object Detection (SP)
|
100% |
295
23.4 IPS |
|
|
Object Detection (HP)
|
100% |
285
22.6 IPS |
|
|
Object Detection (Q)
|
87% |
973
78.0 IPS |
|
|
Face Detection (SP)
|
100% |
798
9.48 IPS |
|
|
Face Detection (HP)
|
100% |
764
9.07 IPS |
|
|
Face Detection (Q)
|
97% |
2069
24.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
639
4.93 IPS |
|
|
Depth Estimation (HP)
|
99% |
649
5.00 IPS |
|
|
Depth Estimation (Q)
|
64% |
1496
13.6 IPS |
|
|
Style Transfer (SP)
|
100% |
1141
1.47 IPS |
|
|
Style Transfer (HP)
|
100% |
1147
1.47 IPS |
|
|
Style Transfer (Q)
|
98% |
3004
3.87 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
348
12.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
324
12.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1385
51.3 IPS |
|
|
Text Classification (SP)
|
100% |
494
659.3 IPS |
|
|
Text Classification (HP)
|
100% |
489
652.1 IPS |
|
|
Text Classification (Q)
|
91% |
813
1.09 KIPS |
|
|
Machine Translation (SP)
|
100% |
759
13.1 IPS |
|
|
Machine Translation (HP)
|
100% |
713
12.3 IPS |
|
|
Machine Translation (Q)
|
57% |
545
13.3 IPS |
