Samsung Galaxy S22
Geekbench ML Score
432
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 30 2024 01:16 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S901N |
| 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 | 7.05 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
184
34.5 IPS |
|
|
Image Classification (F16)
|
100% |
190
35.5 IPS |
|
|
Image Classification (I8)
|
97% |
535
100.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
228
3.81 IPS |
|
|
Image Segmentation (F16)
|
100% |
234
3.91 IPS |
|
|
Image Segmentation (I8)
|
98% |
567
9.48 IPS |
|
|
Pose Estimation (F32)
|
100% |
295
0.36 IPS |
|
|
Pose Estimation (F16)
|
100% |
305
0.37 IPS |
|
|
Pose Estimation (I8)
|
100% |
1315
1.59 IPS |
|
|
Object Detection (F32)
|
100% |
199
14.9 IPS |
|
|
Object Detection (F16)
|
100% |
200
14.9 IPS |
|
|
Object Detection (I8)
|
61% |
588
43.9 IPS |
|
|
Face Detection (F32)
|
100% |
498
5.92 IPS |
|
|
Face Detection (F16)
|
100% |
489
5.81 IPS |
|
|
Face Detection (I8)
|
86% |
1269
15.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
404
3.13 IPS |
|
|
Depth Estimation (F16)
|
100% |
405
3.14 IPS |
|
|
Depth Estimation (I8)
|
95% |
1269
9.84 IPS |
|
|
Style Transfer (F32)
|
100% |
671
0.88 IPS |
|
|
Style Transfer (F16)
|
100% |
672
0.88 IPS |
|
|
Style Transfer (I8)
|
98% |
1813
2.39 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
207
7.40 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
208
7.43 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
833
29.7 IPS |
|
|
Text Classification (F32)
|
100% |
269
386.1 IPS |
|
|
Text Classification (F16)
|
100% |
269
386.4 IPS |
|
|
Text Classification (I8)
|
92% |
488
701.8 IPS |
|
|
Machine Translation (F32)
|
100% |
452
8.32 IPS |
|
|
Machine Translation (F16)
|
100% |
435
8.01 IPS |
|
|
Machine Translation (I8)
|
64% |
574
10.6 IPS |
