Samsung Galaxy S22 Ultra
Geekbench AI Score
1379
Single Precision Score
1412
Half Precision Score
2037
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 03 2025 08:14 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908B |
| 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 | 7.12 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
927
172.5 IPS |
|
|
Image Classification (HP)
|
100% |
1162
216.2 IPS |
|
|
Image Classification (Q)
|
100% |
1732
322.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1282
20.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1298
21.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
1911
31.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2150
2.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
2050
2.39 IPS |
|
|
Pose Estimation (Q)
|
84% |
4226
5.01 IPS |
|
|
Object Detection (SP)
|
98% |
1016
80.9 IPS |
|
|
Object Detection (HP)
|
98% |
1016
80.8 IPS |
|
|
Object Detection (Q)
|
83% |
1309
105.7 IPS |
|
|
Face Detection (SP)
|
100% |
1967
23.4 IPS |
|
|
Face Detection (HP)
|
100% |
2005
23.8 IPS |
|
|
Face Detection (Q)
|
95% |
3039
36.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
2233
17.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2251
17.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
3246
29.7 IPS |
|
|
Style Transfer (SP)
|
89% |
4756
6.17 IPS |
|
|
Style Transfer (HP)
|
89% |
4760
6.18 IPS |
|
|
Style Transfer (Q)
|
98% |
8675
11.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1067
39.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1067
39.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2128
78.8 IPS |
|
|
Text Classification (SP)
|
100% |
403
538.2 IPS |
|
|
Text Classification (HP)
|
99% |
418
558.5 IPS |
|
|
Text Classification (Q)
|
88% |
738
995.4 IPS |
|
|
Machine Translation (SP)
|
100% |
1073
18.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1054
18.2 IPS |
|
|
Machine Translation (Q)
|
50% |
501
17.8 IPS |
