Samsung Galaxy S22
Geekbench ML Score
336
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 04:32 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 | 7.06 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
144
26.9 IPS |
|
|
Image Classification (F16)
|
100% |
143
26.7 IPS |
|
|
Image Classification (I8)
|
97% |
414
77.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
188
3.15 IPS |
|
|
Image Segmentation (F16)
|
100% |
189
3.15 IPS |
|
|
Image Segmentation (I8)
|
98% |
432
7.21 IPS |
|
|
Pose Estimation (F32)
|
100% |
252
0.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
254
0.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
1029
1.25 IPS |
|
|
Object Detection (F32)
|
100% |
147
11.0 IPS |
|
|
Object Detection (F16)
|
100% |
148
11.0 IPS |
|
|
Object Detection (I8)
|
61% |
428
31.9 IPS |
|
|
Face Detection (F32)
|
100% |
397
4.72 IPS |
|
|
Face Detection (F16)
|
100% |
396
4.71 IPS |
|
|
Face Detection (I8)
|
86% |
946
11.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
326
2.53 IPS |
|
|
Depth Estimation (F16)
|
100% |
339
2.63 IPS |
|
|
Depth Estimation (I8)
|
95% |
956
7.41 IPS |
|
|
Style Transfer (F32)
|
100% |
575
0.76 IPS |
|
|
Style Transfer (F16)
|
100% |
567
0.75 IPS |
|
|
Style Transfer (I8)
|
98% |
1421
1.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
164
5.86 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
163
5.84 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
608
21.7 IPS |
|
|
Text Classification (F32)
|
100% |
193
277.8 IPS |
|
|
Text Classification (F16)
|
100% |
193
278.1 IPS |
|
|
Text Classification (I8)
|
92% |
352
506.0 IPS |
|
|
Machine Translation (F32)
|
100% |
351
6.46 IPS |
|
|
Machine Translation (F16)
|
100% |
352
6.48 IPS |
|
|
Machine Translation (I8)
|
64% |
429
7.90 IPS |
