OnePlus CPH2609
Geekbench AI Score
641
Single Precision Score
605
Half Precision Score
1032
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 28 2024 12:33 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OnePlus CPH2609 |
| Model ID | OnePlus CPH2609 |
| Motherboard | kalama |
| Governor | uag |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 14.78 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
511
95.0 IPS |
|
|
Image Classification (HP)
|
100% |
343
63.7 IPS |
|
|
Image Classification (Q)
|
100% |
850
158.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
372
6.03 IPS |
|
|
Image Segmentation (HP)
|
100% |
420
6.81 IPS |
|
|
Image Segmentation (Q)
|
98% |
896
14.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1241
1.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
1230
1.43 IPS |
|
|
Pose Estimation (Q)
|
84% |
2628
3.12 IPS |
|
|
Object Detection (SP)
|
98% |
316
25.1 IPS |
|
|
Object Detection (HP)
|
98% |
316
25.1 IPS |
|
|
Object Detection (Q)
|
83% |
732
59.1 IPS |
|
|
Face Detection (SP)
|
100% |
811
9.63 IPS |
|
|
Face Detection (HP)
|
100% |
821
9.76 IPS |
|
|
Face Detection (Q)
|
95% |
1717
20.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
989
7.64 IPS |
|
|
Depth Estimation (HP)
|
99% |
915
7.07 IPS |
|
|
Depth Estimation (Q)
|
64% |
1988
18.2 IPS |
|
|
Style Transfer (SP)
|
89% |
2192
2.85 IPS |
|
|
Style Transfer (HP)
|
89% |
2528
3.28 IPS |
|
|
Style Transfer (Q)
|
98% |
5324
6.87 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
531
19.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
559
20.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1195
44.3 IPS |
|
|
Text Classification (SP)
|
100% |
298
397.1 IPS |
|
|
Text Classification (HP)
|
99% |
241
321.6 IPS |
|
|
Text Classification (Q)
|
88% |
295
398.3 IPS |
|
|
Machine Translation (SP)
|
100% |
573
9.87 IPS |
|
|
Machine Translation (HP)
|
100% |
463
7.97 IPS |
|
|
Machine Translation (Q)
|
50% |
147
5.22 IPS |
