OPPO PKD130
Geekbench ML Score
328
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 07 2024 12:24 AM |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
133
24.9 IPS |
|
|
Image Classification (F16)
|
100% |
424
79.3 IPS |
|
|
Image Classification (I8)
|
97% |
51
9.54 IPS |
|
|
Image Segmentation (F32)
|
100% |
252
4.22 IPS |
|
|
Image Segmentation (F16)
|
100% |
480
8.02 IPS |
|
|
Image Segmentation (I8)
|
98% |
86
1.44 IPS |
|
|
Pose Estimation (F32)
|
100% |
898
1.09 IPS |
|
|
Pose Estimation (F16)
|
100% |
2073
2.51 IPS |
|
|
Pose Estimation (I8)
|
87% |
1203
1.46 IPS |
|
|
Object Detection (F32)
|
100% |
162
12.1 IPS |
|
|
Object Detection (F16)
|
100% |
342
25.5 IPS |
|
|
Object Detection (I8)
|
51% |
96
7.15 IPS |
|
|
Face Detection (F32)
|
25% |
703
8.36 IPS |
|
|
Face Detection (F16)
|
25% |
987
11.7 IPS |
|
|
Face Detection (I8)
|
87% |
136
1.62 IPS |
|
|
Depth Estimation (F32)
|
100% |
378
2.93 IPS |
|
|
Depth Estimation (F16)
|
74% |
479
3.72 IPS |
|
|
Depth Estimation (I8)
|
93% |
367
2.85 IPS |
|
|
Style Transfer (F32)
|
100% |
716
0.94 IPS |
|
|
Style Transfer (F16)
|
100% |
1289
1.70 IPS |
|
|
Style Transfer (I8)
|
98% |
1694
2.23 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
381
13.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
892
31.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
458
16.4 IPS |
|
|
Text Classification (F32)
|
100% |
84
121.1 IPS |
|
|
Text Classification (F16)
|
100% |
93
133.5 IPS |
|
|
Text Classification (I8)
|
94% |
81
117.0 IPS |
|
|
Machine Translation (F32)
|
100% |
217
3.99 IPS |
|
|
Machine Translation (F16)
|
100% |
290
5.34 IPS |
|
|
Machine Translation (I8)
|
57% |
149
2.74 IPS |
