OPPO PJT110
Geekbench ML Score
402
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 02 2025 05:53 PM |
| Views | 9 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO PJT110 |
| Model ID | OPPO PJT110 |
| Motherboard | blair |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 11.07 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
120
22.4 IPS |
|
|
Image Classification (F16)
|
100% |
173
32.3 IPS |
|
|
Image Classification (I8)
|
97% |
434
81.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
271
4.52 IPS |
|
|
Image Segmentation (F16)
|
100% |
268
4.47 IPS |
|
|
Image Segmentation (I8)
|
98% |
433
7.24 IPS |
|
|
Pose Estimation (F32)
|
100% |
364
0.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
363
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1803
2.18 IPS |
|
|
Object Detection (F32)
|
100% |
194
14.5 IPS |
|
|
Object Detection (F16)
|
100% |
203
15.2 IPS |
|
|
Object Detection (I8)
|
61% |
538
40.1 IPS |
|
|
Face Detection (F32)
|
100% |
425
5.05 IPS |
|
|
Face Detection (F16)
|
100% |
424
5.04 IPS |
|
|
Face Detection (I8)
|
86% |
1049
12.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
414
3.21 IPS |
|
|
Depth Estimation (F16)
|
100% |
417
3.24 IPS |
|
|
Depth Estimation (I8)
|
95% |
1071
8.30 IPS |
|
|
Style Transfer (F32)
|
100% |
680
0.89 IPS |
|
|
Style Transfer (F16)
|
100% |
679
0.89 IPS |
|
|
Style Transfer (I8)
|
98% |
1975
2.60 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
232
8.27 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
236
8.42 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
788
28.2 IPS |
|
|
Text Classification (F32)
|
100% |
240
345.2 IPS |
|
|
Text Classification (F16)
|
100% |
235
337.4 IPS |
|
|
Text Classification (I8)
|
92% |
203
291.0 IPS |
|
|
Machine Translation (F32)
|
100% |
459
8.44 IPS |
|
|
Machine Translation (F16)
|
100% |
483
8.88 IPS |
|
|
Machine Translation (I8)
|
64% |
273
5.03 IPS |
