Samsung Galaxy S22 Ultra
Geekbench AI Score
1545
Single Precision Score
1546
Half Precision Score
2284
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | rbtree |
| Upload Date | January 18 2025 02:54 AM |
| Views | 7 |
| Notes | on battery |
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-S908U1 |
| 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% |
1088
202.3 IPS |
|
|
Image Classification (HP)
|
100% |
1093
203.3 IPS |
|
|
Image Classification (Q)
|
100% |
1625
302.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1215
19.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1215
19.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
1808
29.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2282
2.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
2202
2.57 IPS |
|
|
Pose Estimation (Q)
|
84% |
4968
5.89 IPS |
|
|
Object Detection (SP)
|
98% |
1123
89.4 IPS |
|
|
Object Detection (HP)
|
98% |
1123
89.4 IPS |
|
|
Object Detection (Q)
|
83% |
1529
123.5 IPS |
|
|
Face Detection (SP)
|
100% |
2275
27.0 IPS |
|
|
Face Detection (HP)
|
100% |
2335
27.7 IPS |
|
|
Face Detection (Q)
|
95% |
3559
42.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
2582
19.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
2596
20.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
3881
35.5 IPS |
|
|
Style Transfer (SP)
|
89% |
5218
6.77 IPS |
|
|
Style Transfer (HP)
|
89% |
5325
6.91 IPS |
|
|
Style Transfer (Q)
|
98% |
10426
13.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1249
46.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1251
46.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2557
94.8 IPS |
|
|
Text Classification (SP)
|
100% |
504
672.2 IPS |
|
|
Text Classification (HP)
|
99% |
502
670.2 IPS |
|
|
Text Classification (Q)
|
88% |
868
1.17 KIPS |
|
|
Machine Translation (SP)
|
100% |
1187
20.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1174
20.2 IPS |
|
|
Machine Translation (Q)
|
50% |
542
19.3 IPS |
