OnePlus PJE110
Geekbench ML Score
747
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 08 2025 01:50 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OnePlus PJE110 |
| Model ID | OnePlus PJE110 |
| 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 | 10.88 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
339
63.4 IPS |
|
|
Image Classification (F16)
|
100% |
353
66.0 IPS |
|
|
Image Classification (I8)
|
97% |
481
90.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
506
8.46 IPS |
|
|
Image Segmentation (F16)
|
100% |
516
8.63 IPS |
|
|
Image Segmentation (I8)
|
98% |
501
8.37 IPS |
|
|
Pose Estimation (F32)
|
100% |
1047
1.27 IPS |
|
|
Pose Estimation (F16)
|
100% |
973
1.18 IPS |
|
|
Pose Estimation (I8)
|
100% |
3853
4.67 IPS |
|
|
Object Detection (F32)
|
100% |
389
29.0 IPS |
|
|
Object Detection (F16)
|
100% |
392
29.2 IPS |
|
|
Object Detection (I8)
|
61% |
652
48.7 IPS |
|
|
Face Detection (F32)
|
100% |
918
10.9 IPS |
|
|
Face Detection (F16)
|
100% |
922
11.0 IPS |
|
|
Face Detection (I8)
|
86% |
1291
15.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
935
7.25 IPS |
|
|
Depth Estimation (F16)
|
100% |
945
7.33 IPS |
|
|
Depth Estimation (I8)
|
95% |
1511
11.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1885
2.48 IPS |
|
|
Style Transfer (F16)
|
100% |
1791
2.36 IPS |
|
|
Style Transfer (I8)
|
98% |
3178
4.18 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
555
19.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
575
20.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1384
49.4 IPS |
|
|
Text Classification (F32)
|
100% |
372
534.0 IPS |
|
|
Text Classification (F16)
|
100% |
378
543.0 IPS |
|
|
Text Classification (I8)
|
92% |
290
417.4 IPS |
|
|
Machine Translation (F32)
|
100% |
791
14.6 IPS |
|
|
Machine Translation (F16)
|
100% |
848
15.6 IPS |
|
|
Machine Translation (I8)
|
64% |
295
5.43 IPS |
