Samsung Galaxy S22
Geekbench ML Score
565
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 26 2024 09:18 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S901E |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
269
50.3 IPS |
|
|
Image Classification (F16)
|
100% |
272
50.9 IPS |
|
|
Image Classification (I8)
|
97% |
443
82.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
380
6.34 IPS |
|
|
Image Segmentation (F16)
|
100% |
386
6.45 IPS |
|
|
Image Segmentation (I8)
|
98% |
409
6.83 IPS |
|
|
Pose Estimation (F32)
|
100% |
602
0.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
586
0.71 IPS |
|
|
Pose Estimation (I8)
|
100% |
1675
2.03 IPS |
|
|
Object Detection (F32)
|
100% |
217
16.2 IPS |
|
|
Object Detection (F16)
|
100% |
252
18.8 IPS |
|
|
Object Detection (I8)
|
61% |
580
43.3 IPS |
|
|
Face Detection (F32)
|
100% |
630
7.49 IPS |
|
|
Face Detection (F16)
|
100% |
628
7.47 IPS |
|
|
Face Detection (I8)
|
86% |
965
11.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
692
5.37 IPS |
|
|
Depth Estimation (F16)
|
100% |
669
5.19 IPS |
|
|
Depth Estimation (I8)
|
95% |
1314
10.2 IPS |
|
|
Style Transfer (F32)
|
100% |
1372
1.80 IPS |
|
|
Style Transfer (F16)
|
100% |
1379
1.81 IPS |
|
|
Style Transfer (I8)
|
98% |
2856
3.76 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
438
15.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
431
15.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1134
40.5 IPS |
|
|
Text Classification (F32)
|
100% |
397
571.1 IPS |
|
|
Text Classification (F16)
|
100% |
394
566.7 IPS |
|
|
Text Classification (I8)
|
92% |
272
390.9 IPS |
|
|
Machine Translation (F32)
|
100% |
585
10.8 IPS |
|
|
Machine Translation (F16)
|
100% |
582
10.7 IPS |
|
|
Machine Translation (I8)
|
64% |
270
4.96 IPS |
