Samsung Galaxy S22
Geekbench ML Score
405
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 24 2024 04:12 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S901U1 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 7.06 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
186
34.9 IPS |
|
|
Image Classification (F16)
|
100% |
178
33.3 IPS |
|
|
Image Classification (I8)
|
97% |
528
98.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
213
3.55 IPS |
|
|
Image Segmentation (F16)
|
100% |
214
3.58 IPS |
|
|
Image Segmentation (I8)
|
98% |
517
8.63 IPS |
|
|
Pose Estimation (F32)
|
100% |
280
0.34 IPS |
|
|
Pose Estimation (F16)
|
100% |
277
0.34 IPS |
|
|
Pose Estimation (I8)
|
100% |
1186
1.44 IPS |
|
|
Object Detection (F32)
|
100% |
184
13.7 IPS |
|
|
Object Detection (F16)
|
100% |
182
13.6 IPS |
|
|
Object Detection (I8)
|
61% |
565
42.2 IPS |
|
|
Face Detection (F32)
|
100% |
464
5.52 IPS |
|
|
Face Detection (F16)
|
100% |
456
5.42 IPS |
|
|
Face Detection (I8)
|
86% |
1102
13.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
368
2.85 IPS |
|
|
Depth Estimation (F16)
|
100% |
370
2.87 IPS |
|
|
Depth Estimation (I8)
|
95% |
1174
9.11 IPS |
|
|
Style Transfer (F32)
|
100% |
634
0.83 IPS |
|
|
Style Transfer (F16)
|
100% |
633
0.83 IPS |
|
|
Style Transfer (I8)
|
98% |
1700
2.24 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
192
6.87 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
196
6.98 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
770
27.5 IPS |
|
|
Text Classification (F32)
|
100% |
257
368.6 IPS |
|
|
Text Classification (F16)
|
100% |
259
371.8 IPS |
|
|
Text Classification (I8)
|
92% |
488
700.6 IPS |
|
|
Machine Translation (F32)
|
100% |
430
7.91 IPS |
|
|
Machine Translation (F16)
|
100% |
416
7.66 IPS |
|
|
Machine Translation (I8)
|
64% |
546
10.0 IPS |
