Sony Xperia 5
Geekbench ML Score
384
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 27 2024 04:15 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Sony Xperia 5 |
| Model ID | Sony J9210 |
| Motherboard | msmnile |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 13 part 2052 revision 14 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 5.36 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
246
46.0 IPS |
|
|
Image Classification (F16)
|
100% |
207
38.8 IPS |
|
|
Image Classification (I8)
|
97% |
349
65.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
280
4.68 IPS |
|
|
Image Segmentation (F16)
|
100% |
275
4.59 IPS |
|
|
Image Segmentation (I8)
|
98% |
357
5.97 IPS |
|
|
Pose Estimation (F32)
|
100% |
384
0.47 IPS |
|
|
Pose Estimation (F16)
|
100% |
365
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1692
2.05 IPS |
|
|
Object Detection (F32)
|
100% |
195
14.5 IPS |
|
|
Object Detection (F16)
|
100% |
202
15.1 IPS |
|
|
Object Detection (I8)
|
61% |
379
28.3 IPS |
|
|
Face Detection (F32)
|
100% |
472
5.61 IPS |
|
|
Face Detection (F16)
|
100% |
452
5.37 IPS |
|
|
Face Detection (I8)
|
86% |
745
8.86 IPS |
|
|
Depth Estimation (F32)
|
100% |
406
3.15 IPS |
|
|
Depth Estimation (F16)
|
100% |
392
3.04 IPS |
|
|
Depth Estimation (I8)
|
95% |
793
6.15 IPS |
|
|
Style Transfer (F32)
|
100% |
634
0.83 IPS |
|
|
Style Transfer (F16)
|
100% |
633
0.83 IPS |
|
|
Style Transfer (I8)
|
98% |
1941
2.55 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
200
7.13 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
215
7.68 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
810
28.9 IPS |
|
|
Text Classification (F32)
|
100% |
269
386.2 IPS |
|
|
Text Classification (F16)
|
100% |
259
372.5 IPS |
|
|
Text Classification (I8)
|
92% |
207
296.9 IPS |
|
|
Machine Translation (F32)
|
100% |
433
7.96 IPS |
|
|
Machine Translation (F16)
|
100% |
409
7.53 IPS |
|
|
Machine Translation (I8)
|
64% |
148
2.72 IPS |
