OPPO PKD130
Geekbench ML Score
405
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 06 2024 11:17 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO PKD130 |
| Model ID | OPPO PKD130 |
| Motherboard | k6835v2_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.41 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
189
35.4 IPS |
|
|
Image Classification (F16)
|
100% |
189
35.4 IPS |
|
|
Image Classification (I8)
|
97% |
333
62.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
293
4.89 IPS |
|
|
Image Segmentation (F16)
|
100% |
293
4.89 IPS |
|
|
Image Segmentation (I8)
|
98% |
398
6.65 IPS |
|
|
Pose Estimation (F32)
|
100% |
395
0.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
394
0.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
1766
2.14 IPS |
|
|
Object Detection (F32)
|
100% |
229
17.1 IPS |
|
|
Object Detection (F16)
|
100% |
227
16.9 IPS |
|
|
Object Detection (I8)
|
61% |
455
34.0 IPS |
|
|
Face Detection (F32)
|
100% |
426
5.06 IPS |
|
|
Face Detection (F16)
|
100% |
437
5.19 IPS |
|
|
Face Detection (I8)
|
86% |
875
10.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
427
3.31 IPS |
|
|
Depth Estimation (F16)
|
100% |
426
3.30 IPS |
|
|
Depth Estimation (I8)
|
95% |
905
7.01 IPS |
|
|
Style Transfer (F32)
|
100% |
660
0.87 IPS |
|
|
Style Transfer (F16)
|
100% |
661
0.87 IPS |
|
|
Style Transfer (I8)
|
98% |
1994
2.62 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
247
8.80 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
248
8.84 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
686
24.5 IPS |
|
|
Text Classification (F32)
|
100% |
247
355.0 IPS |
|
|
Text Classification (F16)
|
100% |
251
360.1 IPS |
|
|
Text Classification (I8)
|
92% |
204
292.9 IPS |
|
|
Machine Translation (F32)
|
100% |
379
6.98 IPS |
|
|
Machine Translation (F16)
|
100% |
378
6.96 IPS |
|
|
Machine Translation (I8)
|
64% |
358
6.58 IPS |
