Samsung Galaxy S22 Ultra
Geekbench AI Score
1385
Single Precision Score
1367
Half Precision Score
1955
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | October 11 2024 06:17 AM |
| Views | 10 |
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% |
1085
201.8 IPS |
|
|
Image Classification (HP)
|
100% |
973
180.9 IPS |
|
|
Image Classification (Q)
|
100% |
1329
247.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1071
17.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1038
16.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1513
24.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1989
2.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2006
2.34 IPS |
|
|
Pose Estimation (Q)
|
84% |
4157
4.93 IPS |
|
|
Object Detection (SP)
|
98% |
1047
83.3 IPS |
|
|
Object Detection (HP)
|
98% |
1045
83.2 IPS |
|
|
Object Detection (Q)
|
83% |
1376
111.2 IPS |
|
|
Face Detection (SP)
|
100% |
2007
23.9 IPS |
|
|
Face Detection (HP)
|
100% |
2035
24.2 IPS |
|
|
Face Detection (Q)
|
95% |
3009
35.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
2231
17.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
2271
17.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
3295
30.2 IPS |
|
|
Style Transfer (SP)
|
89% |
4636
6.02 IPS |
|
|
Style Transfer (HP)
|
89% |
4644
6.03 IPS |
|
|
Style Transfer (Q)
|
98% |
8762
11.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1100
40.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1101
40.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2147
79.6 IPS |
|
|
Text Classification (SP)
|
100% |
417
556.2 IPS |
|
|
Text Classification (HP)
|
99% |
411
549.0 IPS |
|
|
Text Classification (Q)
|
88% |
781
1.05 KIPS |
|
|
Machine Translation (SP)
|
100% |
1130
19.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1109
19.1 IPS |
|
|
Machine Translation (Q)
|
50% |
487
17.3 IPS |
