Samsung Galaxy S22 Ultra
Geekbench AI Score
217
Single Precision Score
214
Half Precision Score
516
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | purity |
| Upload Date | August 15 2024 09:48 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
180
33.4 IPS |
|
|
Image Classification (HP)
|
100% |
182
33.8 IPS |
|
|
Image Classification (Q)
|
97% |
465
86.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
205
3.33 IPS |
|
|
Image Segmentation (HP)
|
100% |
197
3.19 IPS |
|
|
Image Segmentation (Q)
|
98% |
429
6.97 IPS |
|
|
Pose Estimation (SP)
|
100% |
231
0.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
218
0.25 IPS |
|
|
Pose Estimation (Q)
|
98% |
870
1.02 IPS |
|
|
Object Detection (SP)
|
100% |
122
9.69 IPS |
|
|
Object Detection (HP)
|
100% |
124
9.83 IPS |
|
|
Object Detection (Q)
|
89% |
376
30.1 IPS |
|
|
Face Detection (SP)
|
100% |
345
4.10 IPS |
|
|
Face Detection (HP)
|
100% |
340
4.04 IPS |
|
|
Face Detection (Q)
|
97% |
813
9.69 IPS |
|
|
Depth Estimation (SP)
|
100% |
286
2.20 IPS |
|
|
Depth Estimation (HP)
|
100% |
284
2.19 IPS |
|
|
Depth Estimation (Q)
|
73% |
687
5.62 IPS |
|
|
Style Transfer (SP)
|
100% |
450
0.58 IPS |
|
|
Style Transfer (HP)
|
100% |
447
0.57 IPS |
|
|
Style Transfer (Q)
|
98% |
1144
1.48 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
121
4.48 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
120
4.42 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
440
16.3 IPS |
|
|
Text Classification (SP)
|
100% |
153
204.4 IPS |
|
|
Text Classification (HP)
|
100% |
152
203.1 IPS |
|
|
Text Classification (Q)
|
91% |
302
406.2 IPS |
|
|
Machine Translation (SP)
|
100% |
273
4.71 IPS |
|
|
Machine Translation (HP)
|
100% |
273
4.70 IPS |
|
|
Machine Translation (Q)
|
57% |
242
5.92 IPS |
