Samsung Galaxy S22
Geekbench AI Score
979
Single Precision Score
1783
Half Precision Score
1430
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Beamish |
| Upload Date | November 28 2025 09:27 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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% |
404
75.2 IPS |
|
|
Image Classification (HP)
|
100% |
673
125.2 IPS |
|
|
Image Classification (Q)
|
100% |
533
99.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
597
9.67 IPS |
|
|
Image Segmentation (HP)
|
100% |
1068
17.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
992
16.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
4098
4.78 IPS |
|
|
Pose Estimation (HP)
|
99% |
9146
10.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
8847
10.4 IPS |
|
|
Object Detection (SP)
|
100% |
425
33.7 IPS |
|
|
Object Detection (HP)
|
99% |
931
73.9 IPS |
|
|
Object Detection (Q)
|
85% |
840
67.6 IPS |
|
|
Face Detection (SP)
|
100% |
2448
29.1 IPS |
|
|
Face Detection (HP)
|
100% |
3719
44.2 IPS |
|
|
Face Detection (Q)
|
97% |
3096
36.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
2760
21.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
4914
38.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
3654
36.1 IPS |
|
|
Style Transfer (SP)
|
100% |
8659
11.1 IPS |
|
|
Style Transfer (HP)
|
100% |
15789
20.3 IPS |
|
|
Style Transfer (Q)
|
98% |
15740
20.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1729
63.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2863
105.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2903
107.6 IPS |
|
|
Text Classification (SP)
|
29% |
28
476.6 IPS |
|
|
Text Classification (HP)
|
35% |
68
615.7 IPS |
|
|
Text Classification (Q)
|
33% |
47
563.1 IPS |
|
|
Machine Translation (SP)
|
100% |
685
11.8 IPS |
|
|
Machine Translation (HP)
|
100% |
949
16.3 IPS |
|
|
Machine Translation (Q)
|
48% |
375
14.4 IPS |
