Samsung Galaxy S22 Ultra
Geekbench AI Score
225
Single Precision Score
225
Half Precision Score
553
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | VenomF5 |
| Upload Date | July 25 2025 01:08 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 1 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
127
23.6 IPS |
|
|
Image Classification (HP)
|
100% |
123
22.9 IPS |
|
|
Image Classification (Q)
|
99% |
341
63.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
159
2.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
159
2.58 IPS |
|
|
Image Segmentation (Q)
|
98% |
361
5.87 IPS |
|
|
Pose Estimation (SP)
|
100% |
216
0.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
217
0.25 IPS |
|
|
Pose Estimation (Q)
|
98% |
860
1.01 IPS |
|
|
Object Detection (SP)
|
100% |
122
9.67 IPS |
|
|
Object Detection (HP)
|
100% |
122
9.68 IPS |
|
|
Object Detection (Q)
|
87% |
369
29.6 IPS |
|
|
Face Detection (SP)
|
100% |
342
4.07 IPS |
|
|
Face Detection (HP)
|
100% |
341
4.05 IPS |
|
|
Face Detection (Q)
|
97% |
815
9.72 IPS |
|
|
Depth Estimation (SP)
|
100% |
280
2.16 IPS |
|
|
Depth Estimation (HP)
|
99% |
282
2.17 IPS |
|
|
Depth Estimation (Q)
|
64% |
690
6.26 IPS |
|
|
Style Transfer (SP)
|
100% |
496
0.64 IPS |
|
|
Style Transfer (HP)
|
100% |
494
0.63 IPS |
|
|
Style Transfer (Q)
|
98% |
1526
1.97 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
165
6.09 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
165
6.07 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
617
22.8 IPS |
|
|
Text Classification (SP)
|
100% |
219
292.2 IPS |
|
|
Text Classification (HP)
|
100% |
218
291.2 IPS |
|
|
Text Classification (Q)
|
91% |
399
535.9 IPS |
|
|
Machine Translation (SP)
|
100% |
377
6.49 IPS |
|
|
Machine Translation (HP)
|
100% |
377
6.49 IPS |
|
|
Machine Translation (Q)
|
57% |
329
8.05 IPS |
