OnePlus PJF110
Geekbench ML Score
275
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 06:57 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus PJF110 |
| Model ID | OnePlus PJF110 |
| 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 | 1.90 GHz |
| Cluster 1 | 3 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.61 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 14.96 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
269
50.3 IPS |
|
|
Image Classification (F16)
|
100% |
268
50.1 IPS |
|
|
Image Classification (I8)
|
97% |
292
54.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
142
2.38 IPS |
|
|
Image Segmentation (F16)
|
100% |
143
2.38 IPS |
|
|
Image Segmentation (I8)
|
98% |
296
4.94 IPS |
|
|
Pose Estimation (F32)
|
100% |
194
0.23 IPS |
|
|
Pose Estimation (F16)
|
100% |
194
0.23 IPS |
|
|
Pose Estimation (I8)
|
100% |
735
0.89 IPS |
|
|
Object Detection (F32)
|
100% |
115
8.55 IPS |
|
|
Object Detection (F16)
|
100% |
114
8.53 IPS |
|
|
Object Detection (I8)
|
61% |
319
23.8 IPS |
|
|
Face Detection (F32)
|
100% |
315
3.75 IPS |
|
|
Face Detection (F16)
|
100% |
315
3.74 IPS |
|
|
Face Detection (I8)
|
86% |
648
7.70 IPS |
|
|
Depth Estimation (F32)
|
100% |
264
2.05 IPS |
|
|
Depth Estimation (F16)
|
100% |
264
2.05 IPS |
|
|
Depth Estimation (I8)
|
95% |
711
5.51 IPS |
|
|
Style Transfer (F32)
|
100% |
560
0.74 IPS |
|
|
Style Transfer (F16)
|
100% |
481
0.63 IPS |
|
|
Style Transfer (I8)
|
98% |
1330
1.75 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
131
4.68 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
131
4.68 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
447
16.0 IPS |
|
|
Text Classification (F32)
|
100% |
142
203.5 IPS |
|
|
Text Classification (F16)
|
100% |
142
203.5 IPS |
|
|
Text Classification (I8)
|
92% |
241
346.7 IPS |
|
|
Machine Translation (F32)
|
100% |
282
5.19 IPS |
|
|
Machine Translation (F16)
|
100% |
282
5.20 IPS |
|
|
Machine Translation (I8)
|
64% |
316
5.81 IPS |
