Samsung Galaxy S22 Ultra
Geekbench AI Score
1380
Single Precision Score
1374
Half Precision Score
2003
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 03:52 PM |
| Views | 7 |
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-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% |
1222
227.3 IPS |
|
|
Image Classification (HP)
|
100% |
1192
221.6 IPS |
|
|
Image Classification (Q)
|
100% |
1685
313.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1256
20.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1239
20.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1915
31.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2004
2.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
1940
2.26 IPS |
|
|
Pose Estimation (Q)
|
84% |
4106
4.87 IPS |
|
|
Object Detection (SP)
|
98% |
1007
80.1 IPS |
|
|
Object Detection (HP)
|
98% |
1005
79.9 IPS |
|
|
Object Detection (Q)
|
83% |
1318
106.5 IPS |
|
|
Face Detection (SP)
|
100% |
1838
21.8 IPS |
|
|
Face Detection (HP)
|
100% |
1912
22.7 IPS |
|
|
Face Detection (Q)
|
95% |
2855
34.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
2160
16.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2168
16.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
3072
28.1 IPS |
|
|
Style Transfer (SP)
|
89% |
4356
5.66 IPS |
|
|
Style Transfer (HP)
|
89% |
4374
5.68 IPS |
|
|
Style Transfer (Q)
|
98% |
8639
11.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1024
37.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1015
37.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2129
78.9 IPS |
|
|
Text Classification (SP)
|
100% |
438
585.3 IPS |
|
|
Text Classification (HP)
|
99% |
436
581.7 IPS |
|
|
Text Classification (Q)
|
88% |
777
1.05 KIPS |
|
|
Machine Translation (SP)
|
100% |
1050
18.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1039
17.9 IPS |
|
|
Machine Translation (Q)
|
50% |
475
16.9 IPS |
