Samsung Galaxy S22 Ultra
Geekbench AI Score
1295
Single Precision Score
1305
Half Precision Score
1840
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 18 2024 02:43 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 1 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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% |
972
180.8 IPS |
|
|
Image Classification (HP)
|
100% |
986
183.3 IPS |
|
|
Image Classification (Q)
|
100% |
1390
258.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1023
16.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1050
17.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
1493
24.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1976
2.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
2031
2.37 IPS |
|
|
Pose Estimation (Q)
|
84% |
4118
4.88 IPS |
|
|
Object Detection (SP)
|
98% |
1059
84.3 IPS |
|
|
Object Detection (HP)
|
98% |
1055
83.9 IPS |
|
|
Object Detection (Q)
|
83% |
1404
113.4 IPS |
|
|
Face Detection (SP)
|
100% |
2009
23.9 IPS |
|
|
Face Detection (HP)
|
100% |
1975
23.5 IPS |
|
|
Face Detection (Q)
|
95% |
2958
35.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
2271
17.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2222
17.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
3293
30.2 IPS |
|
|
Style Transfer (SP)
|
89% |
4588
5.96 IPS |
|
|
Style Transfer (HP)
|
89% |
4516
5.86 IPS |
|
|
Style Transfer (Q)
|
98% |
7451
9.61 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
938
34.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
925
34.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1785
66.1 IPS |
|
|
Text Classification (SP)
|
100% |
378
504.8 IPS |
|
|
Text Classification (HP)
|
99% |
379
505.8 IPS |
|
|
Text Classification (Q)
|
88% |
668
901.5 IPS |
|
|
Machine Translation (SP)
|
100% |
863
14.9 IPS |
|
|
Machine Translation (HP)
|
100% |
933
16.1 IPS |
|
|
Machine Translation (Q)
|
50% |
430
15.2 IPS |
