OPPO PHY110
Geekbench ML Score
1213
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 02:31 AM |
| Views | 2 |
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% |
528
98.8 IPS |
|
|
Image Classification (F16)
|
100% |
573
107.3 IPS |
|
|
Image Classification (I8)
|
97% |
972
181.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
741
12.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
752
12.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
697
11.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1527
1.85 IPS |
|
|
Pose Estimation (F16)
|
100% |
1526
1.85 IPS |
|
|
Pose Estimation (I8)
|
100% |
5512
6.67 IPS |
|
|
Object Detection (F32)
|
100% |
616
46.0 IPS |
|
|
Object Detection (F16)
|
100% |
621
46.4 IPS |
|
|
Object Detection (I8)
|
61% |
1367
102.0 IPS |
|
|
Face Detection (F32)
|
100% |
1402
16.7 IPS |
|
|
Face Detection (F16)
|
100% |
1394
16.6 IPS |
|
|
Face Detection (I8)
|
86% |
2253
26.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1444
11.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
1438
11.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
2297
17.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2600
3.42 IPS |
|
|
Style Transfer (F16)
|
100% |
2656
3.49 IPS |
|
|
Style Transfer (I8)
|
98% |
5841
7.68 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
941
33.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
935
33.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2200
78.6 IPS |
|
|
Text Classification (F32)
|
100% |
762
1.09 KIPS |
|
|
Text Classification (F16)
|
100% |
710
1.02 KIPS |
|
|
Text Classification (I8)
|
92% |
485
696.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1482
27.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1481
27.2 IPS |
|
|
Machine Translation (I8)
|
64% |
457
8.42 IPS |
