OnePlus Nord CE 2 Lite
Geekbench ML Score
403
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 12:11 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus Nord CE 2 Lite |
| Model ID | OnePlus CPH2381 |
| Motherboard | holi |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 5.28 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
191
35.7 IPS |
|
|
Image Classification (F16)
|
100% |
191
35.8 IPS |
|
|
Image Classification (I8)
|
97% |
484
90.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
257
4.29 IPS |
|
|
Image Segmentation (F16)
|
100% |
244
4.08 IPS |
|
|
Image Segmentation (I8)
|
98% |
389
6.50 IPS |
|
|
Pose Estimation (F32)
|
100% |
362
0.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
360
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1930
2.34 IPS |
|
|
Object Detection (F32)
|
100% |
213
15.9 IPS |
|
|
Object Detection (F16)
|
100% |
151
11.3 IPS |
|
|
Object Detection (I8)
|
61% |
560
41.8 IPS |
|
|
Face Detection (F32)
|
100% |
414
4.93 IPS |
|
|
Face Detection (F16)
|
100% |
426
5.06 IPS |
|
|
Face Detection (I8)
|
86% |
1098
13.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
421
3.26 IPS |
|
|
Depth Estimation (F16)
|
100% |
415
3.22 IPS |
|
|
Depth Estimation (I8)
|
95% |
1084
8.41 IPS |
|
|
Style Transfer (F32)
|
100% |
671
0.88 IPS |
|
|
Style Transfer (F16)
|
100% |
666
0.88 IPS |
|
|
Style Transfer (I8)
|
98% |
1884
2.48 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
240
8.57 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
235
8.39 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
774
27.7 IPS |
|
|
Text Classification (F32)
|
100% |
240
344.3 IPS |
|
|
Text Classification (F16)
|
100% |
240
345.3 IPS |
|
|
Text Classification (I8)
|
92% |
192
276.2 IPS |
|
|
Machine Translation (F32)
|
100% |
463
8.52 IPS |
|
|
Machine Translation (F16)
|
100% |
466
8.57 IPS |
|
|
Machine Translation (I8)
|
64% |
236
4.34 IPS |
