OnePlus PJX110
Geekbench ML Score
1183
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 05 2025 12:52 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus PJX110 |
| Model ID | OnePlus PJX110 |
| 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 | 22.69 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
560
104.8 IPS |
|
|
Image Classification (F16)
|
100% |
484
90.6 IPS |
|
|
Image Classification (I8)
|
97% |
950
177.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
741
12.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
724
12.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
713
11.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1511
1.83 IPS |
|
|
Pose Estimation (F16)
|
100% |
1416
1.72 IPS |
|
|
Pose Estimation (I8)
|
100% |
5663
6.86 IPS |
|
|
Object Detection (F32)
|
100% |
610
45.5 IPS |
|
|
Object Detection (F16)
|
100% |
620
46.3 IPS |
|
|
Object Detection (I8)
|
61% |
1183
88.3 IPS |
|
|
Face Detection (F32)
|
100% |
1362
16.2 IPS |
|
|
Face Detection (F16)
|
100% |
1332
15.8 IPS |
|
|
Face Detection (I8)
|
86% |
2293
27.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1429
11.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
1425
11.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
2276
17.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2579
3.39 IPS |
|
|
Style Transfer (F16)
|
100% |
2505
3.29 IPS |
|
|
Style Transfer (I8)
|
98% |
5434
7.15 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
933
33.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
920
32.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2066
73.8 IPS |
|
|
Text Classification (F32)
|
100% |
742
1.07 KIPS |
|
|
Text Classification (F16)
|
100% |
721
1.04 KIPS |
|
|
Text Classification (I8)
|
92% |
496
712.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1418
26.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1411
26.0 IPS |
|
|
Machine Translation (I8)
|
64% |
462
8.50 IPS |
