Samsung Galaxy S22
Geekbench ML Score
656
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 Corporate for Android AArch64
Result Information
| Upload Date | December 08 2023 03:46 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S901W |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
304
56.9 IPS |
|
|
Image Classification (F16)
|
100% |
344
64.3 IPS |
|
|
Image Classification (I8)
|
97% |
411
77.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
722
12.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
969
16.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
866
14.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
660
0.80 IPS |
|
|
Pose Estimation (F16)
|
100% |
1117
1.35 IPS |
|
|
Pose Estimation (I8)
|
100% |
1176
1.42 IPS |
|
|
Object Detection (F32)
|
100% |
87
6.46 IPS |
|
|
Object Detection (F16)
|
100% |
100
7.44 IPS |
|
|
Object Detection (I8)
|
62% |
97
7.22 IPS |
|
|
Face Detection (F32)
|
100% |
1677
19.9 IPS |
|
|
Face Detection (F16)
|
97% |
1817
21.6 IPS |
|
|
Face Detection (I8)
|
87% |
1426
17.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1026
7.96 IPS |
|
|
Depth Estimation (F16)
|
100% |
1942
15.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
1943
15.1 IPS |
|
|
Style Transfer (F32)
|
100% |
2582
3.40 IPS |
|
|
Style Transfer (F16)
|
100% |
5068
6.67 IPS |
|
|
Style Transfer (I8)
|
98% |
5108
6.72 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
328
11.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
442
15.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
423
15.1 IPS |
|
|
Text Classification (F32)
|
100% |
245
352.7 IPS |
|
|
Text Classification (F16)
|
100% |
248
356.8 IPS |
|
|
Text Classification (I8)
|
92% |
456
655.9 IPS |
|
|
Machine Translation (F32)
|
100% |
412
7.58 IPS |
|
|
Machine Translation (F16)
|
100% |
410
7.54 IPS |
|
|
Machine Translation (I8)
|
64% |
536
9.87 IPS |
