Samsung Galaxy S22 Ultra
Geekbench AI Score
445
Single Precision Score
737
Half Precision Score
761
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | malasa |
| Upload Date | August 16 2024 02:31 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 1 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908E |
| 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% |
205
38.1 IPS |
|
|
Image Classification (HP)
|
100% |
365
68.0 IPS |
|
|
Image Classification (Q)
|
97% |
346
64.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
424
6.87 IPS |
|
|
Image Segmentation (HP)
|
100% |
723
11.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
692
11.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
312
0.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
855
1.00 IPS |
|
|
Pose Estimation (Q)
|
95% |
843
0.99 IPS |
|
|
Object Detection (SP)
|
100% |
218
17.3 IPS |
|
|
Object Detection (HP)
|
100% |
426
33.8 IPS |
|
|
Object Detection (Q)
|
86% |
413
33.2 IPS |
|
|
Face Detection (SP)
|
100% |
1105
13.1 IPS |
|
|
Face Detection (HP)
|
100% |
1466
17.4 IPS |
|
|
Face Detection (Q)
|
97% |
1708
20.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
898
6.92 IPS |
|
|
Depth Estimation (HP)
|
99% |
1759
13.6 IPS |
|
|
Depth Estimation (Q)
|
75% |
1665
13.5 IPS |
|
|
Style Transfer (SP)
|
100% |
1739
2.24 IPS |
|
|
Style Transfer (HP)
|
100% |
4252
5.47 IPS |
|
|
Style Transfer (Q)
|
98% |
3272
4.22 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
270
9.97 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
414
15.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
423
15.7 IPS |
|
|
Text Classification (SP)
|
100% |
265
353.7 IPS |
|
|
Text Classification (HP)
|
100% |
268
358.3 IPS |
|
|
Text Classification (Q)
|
91% |
526
706.6 IPS |
|
|
Machine Translation (SP)
|
100% |
418
7.19 IPS |
|
|
Machine Translation (HP)
|
100% |
409
7.04 IPS |
|
|
Machine Translation (Q)
|
57% |
379
9.26 IPS |
