OnePlus CPH2581
Geekbench ML Score
409
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 27 2024 07:15 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus CPH2581 |
| Model ID | OnePlus CPH2581 |
| 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 | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 22.69 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
178
33.4 IPS |
|
|
Image Classification (F16)
|
100% |
180
33.6 IPS |
|
|
Image Classification (I8)
|
97% |
465
87.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
234
3.91 IPS |
|
|
Image Segmentation (F16)
|
100% |
234
3.90 IPS |
|
|
Image Segmentation (I8)
|
98% |
485
8.09 IPS |
|
|
Pose Estimation (F32)
|
100% |
298
0.36 IPS |
|
|
Pose Estimation (F16)
|
100% |
298
0.36 IPS |
|
|
Pose Estimation (I8)
|
100% |
1113
1.35 IPS |
|
|
Object Detection (F32)
|
100% |
182
13.6 IPS |
|
|
Object Detection (F16)
|
100% |
181
13.5 IPS |
|
|
Object Detection (I8)
|
61% |
490
36.6 IPS |
|
|
Face Detection (F32)
|
100% |
508
6.04 IPS |
|
|
Face Detection (F16)
|
100% |
508
6.04 IPS |
|
|
Face Detection (I8)
|
86% |
978
11.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
399
3.10 IPS |
|
|
Depth Estimation (F16)
|
100% |
417
3.24 IPS |
|
|
Depth Estimation (I8)
|
95% |
1158
8.98 IPS |
|
|
Style Transfer (F32)
|
100% |
733
0.96 IPS |
|
|
Style Transfer (F16)
|
100% |
731
0.96 IPS |
|
|
Style Transfer (I8)
|
98% |
2018
2.65 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
212
7.56 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
212
7.56 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
741
26.5 IPS |
|
|
Text Classification (F32)
|
100% |
239
342.8 IPS |
|
|
Text Classification (F16)
|
100% |
238
342.6 IPS |
|
|
Text Classification (I8)
|
92% |
390
560.9 IPS |
|
|
Machine Translation (F32)
|
100% |
435
8.00 IPS |
|
|
Machine Translation (F16)
|
100% |
436
8.02 IPS |
|
|
Machine Translation (I8)
|
64% |
493
9.07 IPS |
