OPPO PHY110
Geekbench ML Score
1205
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 25 2024 08:10 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO PHY110 |
| Model ID | OPPO PHY110 |
| 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 | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.90 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
559
104.7 IPS |
|
|
Image Classification (F16)
|
100% |
561
105.0 IPS |
|
|
Image Classification (I8)
|
97% |
950
177.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
720
12.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
749
12.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
742
12.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1524
1.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
1464
1.77 IPS |
|
|
Pose Estimation (I8)
|
100% |
5573
6.75 IPS |
|
|
Object Detection (F32)
|
100% |
605
45.2 IPS |
|
|
Object Detection (F16)
|
100% |
625
46.6 IPS |
|
|
Object Detection (I8)
|
61% |
1245
92.9 IPS |
|
|
Face Detection (F32)
|
100% |
1390
16.5 IPS |
|
|
Face Detection (F16)
|
100% |
1357
16.1 IPS |
|
|
Face Detection (I8)
|
86% |
2221
26.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1430
11.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
1412
11.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
2303
17.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2614
3.44 IPS |
|
|
Style Transfer (F16)
|
100% |
2644
3.48 IPS |
|
|
Style Transfer (I8)
|
98% |
5531
7.28 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
962
34.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
984
35.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2352
84.0 IPS |
|
|
Text Classification (F32)
|
100% |
727
1.04 KIPS |
|
|
Text Classification (F16)
|
100% |
713
1.02 KIPS |
|
|
Text Classification (I8)
|
92% |
455
653.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1497
27.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1464
26.9 IPS |
|
|
Machine Translation (I8)
|
64% |
456
8.40 IPS |
