OnePlus CPH2551
Geekbench ML Score
380
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 08 2023 05:26 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | OnePlus CPH2551 |
| Model ID | OnePlus CPH2551 |
| 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 | 14.83 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
176
32.9 IPS |
|
|
Image Classification (F16)
|
100% |
171
32.0 IPS |
|
|
Image Classification (I8)
|
97% |
424
79.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
230
3.84 IPS |
|
|
Image Segmentation (F16)
|
100% |
213
3.55 IPS |
|
|
Image Segmentation (I8)
|
98% |
417
6.97 IPS |
|
|
Pose Estimation (F32)
|
100% |
306
0.37 IPS |
|
|
Pose Estimation (F16)
|
100% |
304
0.37 IPS |
|
|
Pose Estimation (I8)
|
100% |
1160
1.40 IPS |
|
|
Object Detection (F32)
|
100% |
179
13.3 IPS |
|
|
Object Detection (F16)
|
100% |
181
13.5 IPS |
|
|
Object Detection (I8)
|
61% |
461
34.4 IPS |
|
|
Face Detection (F32)
|
100% |
443
5.27 IPS |
|
|
Face Detection (F16)
|
100% |
429
5.11 IPS |
|
|
Face Detection (I8)
|
86% |
862
10.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
384
2.98 IPS |
|
|
Depth Estimation (F16)
|
100% |
388
3.01 IPS |
|
|
Depth Estimation (I8)
|
95% |
998
7.74 IPS |
|
|
Style Transfer (F32)
|
100% |
623
0.82 IPS |
|
|
Style Transfer (F16)
|
100% |
630
0.83 IPS |
|
|
Style Transfer (I8)
|
98% |
1657
2.18 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
202
7.21 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
204
7.30 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
734
26.2 IPS |
|
|
Text Classification (F32)
|
100% |
240
345.3 IPS |
|
|
Text Classification (F16)
|
100% |
240
345.2 IPS |
|
|
Text Classification (I8)
|
92% |
345
496.2 IPS |
|
|
Machine Translation (F32)
|
100% |
407
7.49 IPS |
|
|
Machine Translation (F16)
|
100% |
408
7.50 IPS |
|
|
Machine Translation (I8)
|
64% |
393
7.23 IPS |
