Samsung Galaxy S22
Geekbench ML Score
186
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 18 2024 06:43 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S901B |
| Motherboard | s5e9925 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.82 GHz |
| Cluster 1 | 4 Cores @ 1.82 GHz |
| Cluster 2 | 3 Cores @ 2.52 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.10 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
69
13.0 IPS |
|
|
Image Classification (F16)
|
100% |
70
13.2 IPS |
|
|
Image Classification (I8)
|
97% |
82
15.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
202
3.38 IPS |
|
|
Image Segmentation (F16)
|
100% |
203
3.40 IPS |
|
|
Image Segmentation (I8)
|
98% |
253
4.22 IPS |
|
|
Pose Estimation (F32)
|
100% |
522
0.63 IPS |
|
|
Pose Estimation (F16)
|
100% |
519
0.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
1391
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
100
7.45 IPS |
|
|
Object Detection (F16)
|
100% |
95
7.08 IPS |
|
|
Object Detection (I8)
|
61% |
134
9.98 IPS |
|
|
Face Detection (F32)
|
100% |
247
2.94 IPS |
|
|
Face Detection (F16)
|
100% |
232
2.76 IPS |
|
|
Face Detection (I8)
|
86% |
381
4.53 IPS |
|
|
Depth Estimation (F32)
|
100% |
273
2.12 IPS |
|
|
Depth Estimation (F16)
|
100% |
256
1.99 IPS |
|
|
Depth Estimation (I8)
|
95% |
452
3.50 IPS |
|
|
Style Transfer (F32)
|
100% |
960
1.26 IPS |
|
|
Style Transfer (F16)
|
100% |
963
1.27 IPS |
|
|
Style Transfer (I8)
|
98% |
1541
2.03 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
144
5.14 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
149
5.34 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
269
9.59 IPS |
|
|
Text Classification (F32)
|
100% |
40
57.6 IPS |
|
|
Text Classification (F16)
|
100% |
39
56.5 IPS |
|
|
Text Classification (I8)
|
92% |
30
42.4 IPS |
|
|
Machine Translation (F32)
|
100% |
62
1.15 IPS |
|
|
Machine Translation (F16)
|
100% |
57
1.04 IPS |
|
|
Machine Translation (I8)
|
64% |
74
1.36 IPS |
