Samsung Galaxy S22 Ultra
Geekbench AI Score
1323
Single Precision Score
1341
Half Precision Score
1983
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 21 2025 03:59 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-S908N |
| 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% |
895
166.5 IPS |
|
|
Image Classification (HP)
|
100% |
960
178.5 IPS |
|
|
Image Classification (Q)
|
100% |
1373
255.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1038
16.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1041
16.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1788
29.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1960
2.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
1888
2.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
4182
4.96 IPS |
|
|
Object Detection (SP)
|
98% |
1044
83.1 IPS |
|
|
Object Detection (HP)
|
98% |
1037
82.5 IPS |
|
|
Object Detection (Q)
|
83% |
1395
112.6 IPS |
|
|
Face Detection (SP)
|
100% |
1910
22.7 IPS |
|
|
Face Detection (HP)
|
100% |
1913
22.7 IPS |
|
|
Face Detection (Q)
|
95% |
2998
35.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
2191
16.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
2210
17.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
3286
30.1 IPS |
|
|
Style Transfer (SP)
|
89% |
4569
5.93 IPS |
|
|
Style Transfer (HP)
|
89% |
4574
5.94 IPS |
|
|
Style Transfer (Q)
|
98% |
8644
11.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1037
38.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1072
39.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2138
79.2 IPS |
|
|
Text Classification (SP)
|
100% |
439
585.7 IPS |
|
|
Text Classification (HP)
|
99% |
439
586.0 IPS |
|
|
Text Classification (Q)
|
88% |
725
977.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1000
17.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1058
18.2 IPS |
|
|
Machine Translation (Q)
|
50% |
499
17.7 IPS |
