Samsung Galaxy S22 Ultra
Geekbench AI Score
1266
Single Precision Score
1310
Half Precision Score
1979
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 17 2025 05:38 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 1 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S9080 |
| 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% |
1146
213.1 IPS |
|
|
Image Classification (HP)
|
100% |
1043
194.0 IPS |
|
|
Image Classification (Q)
|
100% |
1739
323.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
777
12.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1100
17.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1591
25.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1960
2.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
1961
2.29 IPS |
|
|
Pose Estimation (Q)
|
84% |
4138
4.91 IPS |
|
|
Object Detection (SP)
|
98% |
1029
81.9 IPS |
|
|
Object Detection (HP)
|
98% |
1029
81.9 IPS |
|
|
Object Detection (Q)
|
83% |
1394
112.6 IPS |
|
|
Face Detection (SP)
|
100% |
1838
21.8 IPS |
|
|
Face Detection (HP)
|
100% |
1845
21.9 IPS |
|
|
Face Detection (Q)
|
95% |
3012
36.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
1706
13.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
2235
17.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
3297
30.2 IPS |
|
|
Style Transfer (SP)
|
89% |
4483
5.82 IPS |
|
|
Style Transfer (HP)
|
89% |
4483
5.82 IPS |
|
|
Style Transfer (Q)
|
98% |
8393
10.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1049
38.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
878
32.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2080
77.1 IPS |
|
|
Text Classification (SP)
|
100% |
415
554.1 IPS |
|
|
Text Classification (HP)
|
99% |
413
550.6 IPS |
|
|
Text Classification (Q)
|
88% |
708
955.3 IPS |
|
|
Machine Translation (SP)
|
100% |
969
16.7 IPS |
|
|
Machine Translation (HP)
|
100% |
964
16.6 IPS |
|
|
Machine Translation (Q)
|
50% |
471
16.7 IPS |
