Samsung Galaxy S22
Geekbench AI Score
1133
Single Precision Score
1137
Half Precision Score
1662
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | thoppe |
| Upload Date | March 29 2025 12:21 AM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 2200 |
| 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 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
630
117.2 IPS |
|
|
Image Classification (HP)
|
100% |
710
132.1 IPS |
|
|
Image Classification (Q)
|
100% |
961
178.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
784
12.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
747
12.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1251
20.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1810
2.11 IPS |
|
|
Pose Estimation (HP)
|
100% |
1836
2.14 IPS |
|
|
Pose Estimation (Q)
|
84% |
3303
3.92 IPS |
|
|
Object Detection (SP)
|
98% |
861
68.6 IPS |
|
|
Object Detection (HP)
|
98% |
866
68.9 IPS |
|
|
Object Detection (Q)
|
83% |
1123
90.7 IPS |
|
|
Face Detection (SP)
|
100% |
1768
21.0 IPS |
|
|
Face Detection (HP)
|
100% |
1768
21.0 IPS |
|
|
Face Detection (Q)
|
95% |
2830
33.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
1935
14.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
1853
14.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
2916
26.7 IPS |
|
|
Style Transfer (SP)
|
89% |
4371
5.67 IPS |
|
|
Style Transfer (HP)
|
89% |
4362
5.66 IPS |
|
|
Style Transfer (Q)
|
98% |
7542
9.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
990
36.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
924
34.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2001
74.2 IPS |
|
|
Text Classification (SP)
|
100% |
379
506.4 IPS |
|
|
Text Classification (HP)
|
99% |
403
538.4 IPS |
|
|
Text Classification (Q)
|
88% |
720
971.3 IPS |
|
|
Machine Translation (SP)
|
100% |
808
13.9 IPS |
|
|
Machine Translation (HP)
|
100% |
810
14.0 IPS |
|
|
Machine Translation (Q)
|
50% |
404
14.4 IPS |
