Samsung Galaxy S22 Ultra
Geekbench AI Score
1267
Single Precision Score
1241
Half Precision Score
1797
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | October 22 2025 06:40 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 1 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908W |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 10.94 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1256
233.7 IPS |
|
|
Image Classification (HP)
|
100% |
1188
221.0 IPS |
|
|
Image Classification (Q)
|
100% |
1751
325.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1172
19.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1195
19.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
1807
29.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1977
2.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
1728
2.02 IPS |
|
|
Pose Estimation (Q)
|
84% |
3571
4.23 IPS |
|
|
Object Detection (SP)
|
98% |
889
70.8 IPS |
|
|
Object Detection (HP)
|
98% |
889
70.7 IPS |
|
|
Object Detection (Q)
|
83% |
1188
95.9 IPS |
|
|
Face Detection (SP)
|
100% |
1654
19.7 IPS |
|
|
Face Detection (HP)
|
100% |
1616
19.2 IPS |
|
|
Face Detection (Q)
|
95% |
2563
30.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
1932
14.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
1947
15.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
2810
25.7 IPS |
|
|
Style Transfer (SP)
|
89% |
3963
5.14 IPS |
|
|
Style Transfer (HP)
|
89% |
3970
5.15 IPS |
|
|
Style Transfer (Q)
|
98% |
7250
9.35 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
932
34.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
931
34.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1813
67.2 IPS |
|
|
Text Classification (SP)
|
100% |
373
497.9 IPS |
|
|
Text Classification (HP)
|
99% |
371
495.4 IPS |
|
|
Text Classification (Q)
|
88% |
655
882.8 IPS |
|
|
Machine Translation (SP)
|
100% |
943
16.2 IPS |
|
|
Machine Translation (HP)
|
100% |
925
15.9 IPS |
|
|
Machine Translation (Q)
|
50% |
422
15.0 IPS |
