OnePlus CPH2709
Geekbench AI Score
204
Single Precision Score
207
Half Precision Score
462
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | nano-onan |
| Upload Date | December 01 2025 08:19 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OnePlus CPH2709 |
| Model ID | OnePlus CPH2709 |
| Motherboard | pineapple |
| Governor | uag |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.01 GHz |
| Memory Information | |
|---|---|
| Size | 7.14 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
117
21.7 IPS |
|
|
Image Classification (HP)
|
100% |
117
21.7 IPS |
|
|
Image Classification (Q)
|
99% |
295
55.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
154
2.50 IPS |
|
|
Image Segmentation (HP)
|
100% |
154
2.50 IPS |
|
|
Image Segmentation (Q)
|
98% |
320
5.20 IPS |
|
|
Pose Estimation (SP)
|
100% |
208
0.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
209
0.24 IPS |
|
|
Pose Estimation (Q)
|
98% |
794
0.93 IPS |
|
|
Object Detection (SP)
|
100% |
115
9.12 IPS |
|
|
Object Detection (HP)
|
100% |
115
9.10 IPS |
|
|
Object Detection (Q)
|
87% |
324
26.0 IPS |
|
|
Face Detection (SP)
|
100% |
331
3.94 IPS |
|
|
Face Detection (HP)
|
100% |
331
3.93 IPS |
|
|
Face Detection (Q)
|
97% |
677
8.08 IPS |
|
|
Depth Estimation (SP)
|
100% |
278
2.14 IPS |
|
|
Depth Estimation (HP)
|
99% |
278
2.14 IPS |
|
|
Depth Estimation (Q)
|
64% |
634
5.76 IPS |
|
|
Style Transfer (SP)
|
100% |
511
0.66 IPS |
|
|
Style Transfer (HP)
|
100% |
569
0.73 IPS |
|
|
Style Transfer (Q)
|
98% |
1433
1.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
132
4.89 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
132
4.89 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
450
16.7 IPS |
|
|
Text Classification (SP)
|
100% |
164
219.0 IPS |
|
|
Text Classification (HP)
|
100% |
164
219.0 IPS |
|
|
Text Classification (Q)
|
91% |
276
370.7 IPS |
|
|
Machine Translation (SP)
|
100% |
298
5.13 IPS |
|
|
Machine Translation (HP)
|
100% |
299
5.14 IPS |
|
|
Machine Translation (Q)
|
57% |
241
5.88 IPS |
