OnePlus Nord
Geekbench ML Score
296
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 24 2024 04:09 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | OnePlus Nord |
| Model ID | OnePlus AC2001 |
| Motherboard | lito |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 15 part 2052 revision 14 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 1 Core @ 2.21 GHz |
| Cluster 3 | 1 Core @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 11.11 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
148
27.7 IPS |
|
|
Image Classification (F16)
|
100% |
164
30.6 IPS |
|
|
Image Classification (I8)
|
97% |
257
48.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
240
4.01 IPS |
|
|
Image Segmentation (F16)
|
100% |
203
3.40 IPS |
|
|
Image Segmentation (I8)
|
98% |
260
4.35 IPS |
|
|
Pose Estimation (F32)
|
100% |
331
0.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
364
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1126
1.36 IPS |
|
|
Object Detection (F32)
|
100% |
171
12.8 IPS |
|
|
Object Detection (F16)
|
100% |
173
12.9 IPS |
|
|
Object Detection (I8)
|
61% |
364
27.2 IPS |
|
|
Face Detection (F32)
|
100% |
327
3.89 IPS |
|
|
Face Detection (F16)
|
100% |
324
3.85 IPS |
|
|
Face Detection (I8)
|
86% |
528
6.27 IPS |
|
|
Depth Estimation (F32)
|
100% |
299
2.32 IPS |
|
|
Depth Estimation (F16)
|
100% |
313
2.42 IPS |
|
|
Depth Estimation (I8)
|
95% |
739
5.73 IPS |
|
|
Style Transfer (F32)
|
100% |
620
0.82 IPS |
|
|
Style Transfer (F16)
|
100% |
619
0.81 IPS |
|
|
Style Transfer (I8)
|
98% |
1322
1.74 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
40
1.45 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
200
7.15 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
554
19.8 IPS |
|
|
Text Classification (F32)
|
100% |
192
276.4 IPS |
|
|
Text Classification (F16)
|
100% |
189
271.7 IPS |
|
|
Text Classification (I8)
|
92% |
163
234.2 IPS |
|
|
Machine Translation (F32)
|
100% |
407
7.48 IPS |
|
|
Machine Translation (F16)
|
100% |
415
7.65 IPS |
|
|
Machine Translation (I8)
|
64% |
144
2.65 IPS |
