Samsung Galaxy S22 Ultra
Geekbench AI Score
1727
Single Precision Score
1633
Half Precision Score
2671
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 17 2025 01:30 PM |
| Views | 2 |
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 | 10.27 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1338
248.9 IPS |
|
|
Image Classification (HP)
|
100% |
1166
216.8 IPS |
|
|
Image Classification (Q)
|
100% |
2196
408.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1528
24.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1496
24.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2440
39.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2544
2.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
2493
2.91 IPS |
|
|
Pose Estimation (Q)
|
84% |
5439
6.45 IPS |
|
|
Object Detection (SP)
|
98% |
1251
99.6 IPS |
|
|
Object Detection (HP)
|
98% |
1159
92.2 IPS |
|
|
Object Detection (Q)
|
83% |
1949
157.4 IPS |
|
|
Face Detection (SP)
|
100% |
2408
28.6 IPS |
|
|
Face Detection (HP)
|
100% |
2359
28.0 IPS |
|
|
Face Detection (Q)
|
95% |
4292
51.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
2712
21.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
2479
19.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
4363
40.0 IPS |
|
|
Style Transfer (SP)
|
89% |
5842
7.58 IPS |
|
|
Style Transfer (HP)
|
89% |
5641
7.32 IPS |
|
|
Style Transfer (Q)
|
98% |
11841
15.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1345
49.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1351
49.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2916
108.1 IPS |
|
|
Text Classification (SP)
|
100% |
582
777.2 IPS |
|
|
Text Classification (HP)
|
99% |
558
745.1 IPS |
|
|
Text Classification (Q)
|
88% |
1019
1.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
1218
21.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1076
18.5 IPS |
|
|
Machine Translation (Q)
|
50% |
494
17.5 IPS |
