OPPO CPH2519
Geekbench ML Score
496
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 01:48 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO CPH2519 |
| Model ID | OPPO CPH2519 |
| Motherboard | k6985v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.05 GHz |
| Memory Information | |
|---|---|
| Size | 11.11 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
309
57.8 IPS |
|
|
Image Classification (F16)
|
100% |
296
55.4 IPS |
|
|
Image Classification (I8)
|
97% |
289
54.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
360
6.01 IPS |
|
|
Image Segmentation (F16)
|
100% |
361
6.03 IPS |
|
|
Image Segmentation (I8)
|
98% |
424
7.09 IPS |
|
|
Pose Estimation (F32)
|
100% |
554
0.67 IPS |
|
|
Pose Estimation (F16)
|
100% |
586
0.71 IPS |
|
|
Pose Estimation (I8)
|
100% |
2488
3.01 IPS |
|
|
Object Detection (F32)
|
100% |
300
22.4 IPS |
|
|
Object Detection (F16)
|
100% |
292
21.8 IPS |
|
|
Object Detection (I8)
|
61% |
388
28.9 IPS |
|
|
Face Detection (F32)
|
100% |
567
6.75 IPS |
|
|
Face Detection (F16)
|
100% |
586
6.97 IPS |
|
|
Face Detection (I8)
|
86% |
880
10.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
604
4.68 IPS |
|
|
Depth Estimation (F16)
|
100% |
569
4.41 IPS |
|
|
Depth Estimation (I8)
|
95% |
868
6.73 IPS |
|
|
Style Transfer (F32)
|
100% |
1090
1.43 IPS |
|
|
Style Transfer (F16)
|
100% |
1085
1.43 IPS |
|
|
Style Transfer (I8)
|
98% |
2343
3.08 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
297
10.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
350
12.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1204
43.0 IPS |
|
|
Text Classification (F32)
|
100% |
353
506.6 IPS |
|
|
Text Classification (F16)
|
100% |
353
507.2 IPS |
|
|
Text Classification (I8)
|
92% |
280
402.0 IPS |
|
|
Machine Translation (F32)
|
100% |
312
5.74 IPS |
|
|
Machine Translation (F16)
|
100% |
305
5.61 IPS |
|
|
Machine Translation (I8)
|
64% |
192
3.54 IPS |
