Samsung Galaxy S22+
Geekbench AI Score
1241
Single Precision Score
1206
Half Precision Score
1836
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 11 2024 02:15 AM |
| Views | 1 |
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-S906B |
| 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% |
933
173.6 IPS |
|
|
Image Classification (HP)
|
100% |
957
178.0 IPS |
|
|
Image Classification (Q)
|
100% |
1342
249.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1078
17.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
791
12.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1429
23.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1921
2.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
1917
2.24 IPS |
|
|
Pose Estimation (Q)
|
84% |
3943
4.68 IPS |
|
|
Object Detection (SP)
|
98% |
842
67.0 IPS |
|
|
Object Detection (HP)
|
98% |
941
74.9 IPS |
|
|
Object Detection (Q)
|
83% |
1185
95.7 IPS |
|
|
Face Detection (SP)
|
100% |
1722
20.5 IPS |
|
|
Face Detection (HP)
|
100% |
1708
20.3 IPS |
|
|
Face Detection (Q)
|
95% |
2830
33.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
2068
16.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
2074
16.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
3235
29.6 IPS |
|
|
Style Transfer (SP)
|
89% |
4537
5.89 IPS |
|
|
Style Transfer (HP)
|
89% |
4372
5.68 IPS |
|
|
Style Transfer (Q)
|
98% |
7902
10.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
981
36.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
978
36.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2063
76.4 IPS |
|
|
Text Classification (SP)
|
100% |
390
520.8 IPS |
|
|
Text Classification (HP)
|
99% |
373
497.2 IPS |
|
|
Text Classification (Q)
|
88% |
726
978.9 IPS |
|
|
Machine Translation (SP)
|
100% |
865
14.9 IPS |
|
|
Machine Translation (HP)
|
100% |
844
14.5 IPS |
|
|
Machine Translation (Q)
|
50% |
450
16.0 IPS |
