OnePlus PJA110
Geekbench ML Score
563
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 02:34 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | OnePlus PJA110 |
| Model ID | OnePlus PJA110 |
| 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 | 22.63 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
250
46.8 IPS |
|
|
Image Classification (F16)
|
100% |
248
46.4 IPS |
|
|
Image Classification (I8)
|
97% |
590
110.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
318
5.30 IPS |
|
|
Image Segmentation (F16)
|
100% |
319
5.32 IPS |
|
|
Image Segmentation (I8)
|
98% |
635
10.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
454
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
455
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1729
2.09 IPS |
|
|
Object Detection (F32)
|
100% |
267
20.0 IPS |
|
|
Object Detection (F16)
|
100% |
266
19.8 IPS |
|
|
Object Detection (I8)
|
61% |
756
56.4 IPS |
|
|
Face Detection (F32)
|
100% |
622
7.39 IPS |
|
|
Face Detection (F16)
|
100% |
624
7.42 IPS |
|
|
Face Detection (I8)
|
86% |
1323
15.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
538
4.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
567
4.39 IPS |
|
|
Depth Estimation (I8)
|
95% |
1466
11.4 IPS |
|
|
Style Transfer (F32)
|
100% |
883
1.16 IPS |
|
|
Style Transfer (F16)
|
100% |
884
1.16 IPS |
|
|
Style Transfer (I8)
|
98% |
2352
3.09 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
299
10.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
309
11.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1075
38.4 IPS |
|
|
Text Classification (F32)
|
100% |
393
564.6 IPS |
|
|
Text Classification (F16)
|
100% |
391
561.9 IPS |
|
|
Text Classification (I8)
|
92% |
576
827.6 IPS |
|
|
Machine Translation (F32)
|
100% |
598
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
593
10.9 IPS |
|
|
Machine Translation (I8)
|
64% |
574
10.6 IPS |
