OnePlus CPH2581
Geekbench ML Score
424
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 06 2024 03:16 AM |
| 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 | 14.90 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
228
42.8 IPS |
|
|
Image Classification (F16)
|
100% |
231
43.1 IPS |
|
|
Image Classification (I8)
|
97% |
629
117.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
288
4.81 IPS |
|
|
Image Segmentation (F16)
|
100% |
285
4.75 IPS |
|
|
Image Segmentation (I8)
|
98% |
649
10.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
379
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
381
0.46 IPS |
|
|
Pose Estimation (I8)
|
100% |
1681
2.04 IPS |
|
|
Object Detection (F32)
|
100% |
255
19.1 IPS |
|
|
Object Detection (F16)
|
100% |
271
20.2 IPS |
|
|
Object Detection (I8)
|
61% |
836
62.4 IPS |
|
|
Face Detection (F32)
|
100% |
565
6.72 IPS |
|
|
Face Detection (F16)
|
100% |
564
6.71 IPS |
|
|
Face Detection (I8)
|
86% |
1350
16.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
528
4.09 IPS |
|
|
Depth Estimation (F16)
|
100% |
500
3.88 IPS |
|
|
Depth Estimation (I8)
|
95% |
1403
10.9 IPS |
|
|
Style Transfer (F32)
|
100% |
754
0.99 IPS |
|
|
Style Transfer (F16)
|
100% |
481
0.63 IPS |
|
|
Style Transfer (I8)
|
98% |
1374
1.81 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
134
4.78 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
142
5.06 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
483
17.2 IPS |
|
|
Text Classification (F32)
|
100% |
146
210.4 IPS |
|
|
Text Classification (F16)
|
100% |
146
209.9 IPS |
|
|
Text Classification (I8)
|
92% |
239
344.1 IPS |
|
|
Machine Translation (F32)
|
100% |
323
5.94 IPS |
|
|
Machine Translation (F16)
|
100% |
460
8.47 IPS |
|
|
Machine Translation (I8)
|
64% |
489
8.99 IPS |
