Samsung Galaxy S22 Ultra
Geekbench AI Score
1166
Single Precision Score
1165
Half Precision Score
1759
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 26 2025 02:54 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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 | 10.27 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
807
150.1 IPS |
|
|
Image Classification (HP)
|
100% |
862
160.3 IPS |
|
|
Image Classification (Q)
|
100% |
1234
229.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
797
12.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
785
12.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
1436
23.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1804
2.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
1834
2.14 IPS |
|
|
Pose Estimation (Q)
|
84% |
3371
4.00 IPS |
|
|
Object Detection (SP)
|
98% |
852
67.8 IPS |
|
|
Object Detection (HP)
|
98% |
812
64.6 IPS |
|
|
Object Detection (Q)
|
83% |
1132
91.4 IPS |
|
|
Face Detection (SP)
|
100% |
1776
21.1 IPS |
|
|
Face Detection (HP)
|
100% |
1778
21.1 IPS |
|
|
Face Detection (Q)
|
95% |
2876
34.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
2074
16.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
1970
15.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
2992
27.4 IPS |
|
|
Style Transfer (SP)
|
89% |
4412
5.73 IPS |
|
|
Style Transfer (HP)
|
89% |
4398
5.71 IPS |
|
|
Style Transfer (Q)
|
98% |
7874
10.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
925
34.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
930
34.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2001
74.1 IPS |
|
|
Text Classification (SP)
|
100% |
381
508.9 IPS |
|
|
Text Classification (HP)
|
99% |
379
505.8 IPS |
|
|
Text Classification (Q)
|
88% |
736
992.2 IPS |
|
|
Machine Translation (SP)
|
100% |
826
14.2 IPS |
|
|
Machine Translation (HP)
|
100% |
842
14.5 IPS |
|
|
Machine Translation (Q)
|
50% |
421
14.9 IPS |
