OnePlus PJA110
Geekbench ML Score
511
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 01:41 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% |
254
47.5 IPS |
|
|
Image Classification (F16)
|
100% |
250
46.7 IPS |
|
|
Image Classification (I8)
|
97% |
603
112.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
318
5.32 IPS |
|
|
Image Segmentation (F16)
|
100% |
316
5.28 IPS |
|
|
Image Segmentation (I8)
|
98% |
622
10.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
452
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
452
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1686
2.04 IPS |
|
|
Object Detection (F32)
|
100% |
267
19.9 IPS |
|
|
Object Detection (F16)
|
100% |
269
20.1 IPS |
|
|
Object Detection (I8)
|
61% |
709
52.9 IPS |
|
|
Face Detection (F32)
|
100% |
627
7.45 IPS |
|
|
Face Detection (F16)
|
100% |
625
7.43 IPS |
|
|
Face Detection (I8)
|
86% |
1305
15.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
510
3.96 IPS |
|
|
Depth Estimation (F16)
|
100% |
491
3.81 IPS |
|
|
Depth Estimation (I8)
|
95% |
1287
9.98 IPS |
|
|
Style Transfer (F32)
|
100% |
785
1.03 IPS |
|
|
Style Transfer (F16)
|
100% |
784
1.03 IPS |
|
|
Style Transfer (I8)
|
98% |
2084
2.74 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
273
9.73 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
270
9.65 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
894
31.9 IPS |
|
|
Text Classification (F32)
|
100% |
292
419.1 IPS |
|
|
Text Classification (F16)
|
100% |
183
262.4 IPS |
|
|
Text Classification (I8)
|
92% |
423
608.1 IPS |
|
|
Machine Translation (F32)
|
100% |
522
9.60 IPS |
|
|
Machine Translation (F16)
|
100% |
526
9.68 IPS |
|
|
Machine Translation (I8)
|
64% |
503
9.25 IPS |
