Samsung Galaxy S22 Ultra
Geekbench AI Score
222
Single Precision Score
219
Half Precision Score
532
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | laidbackdev |
| Upload Date | August 21 2024 05:06 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| 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% |
166
30.9 IPS |
|
|
Image Classification (HP)
|
100% |
152
28.3 IPS |
|
|
Image Classification (Q)
|
97% |
386
72.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
171
2.78 IPS |
|
|
Image Segmentation (HP)
|
100% |
161
2.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
378
6.14 IPS |
|
|
Pose Estimation (SP)
|
100% |
218
0.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
220
0.26 IPS |
|
|
Pose Estimation (Q)
|
98% |
891
1.04 IPS |
|
|
Object Detection (SP)
|
100% |
124
9.82 IPS |
|
|
Object Detection (HP)
|
100% |
124
9.81 IPS |
|
|
Object Detection (Q)
|
89% |
378
30.3 IPS |
|
|
Face Detection (SP)
|
100% |
343
4.07 IPS |
|
|
Face Detection (HP)
|
100% |
352
4.18 IPS |
|
|
Face Detection (Q)
|
97% |
816
9.73 IPS |
|
|
Depth Estimation (SP)
|
100% |
291
2.24 IPS |
|
|
Depth Estimation (HP)
|
100% |
292
2.25 IPS |
|
|
Depth Estimation (Q)
|
73% |
807
6.60 IPS |
|
|
Style Transfer (SP)
|
100% |
503
0.65 IPS |
|
|
Style Transfer (HP)
|
100% |
509
0.65 IPS |
|
|
Style Transfer (Q)
|
98% |
1275
1.64 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
135
5.00 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
135
4.99 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
505
18.7 IPS |
|
|
Text Classification (SP)
|
100% |
177
236.6 IPS |
|
|
Text Classification (HP)
|
100% |
178
237.7 IPS |
|
|
Text Classification (Q)
|
91% |
325
437.3 IPS |
|
|
Machine Translation (SP)
|
100% |
321
5.53 IPS |
|
|
Machine Translation (HP)
|
100% |
312
5.37 IPS |
|
|
Machine Translation (Q)
|
57% |
272
6.65 IPS |
