Samsung Galaxy S22+
Geekbench AI Score
561
Single Precision Score
942
Half Precision Score
867
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | uditrpanchal |
| Upload Date | March 04 2026 06:06 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 1 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S22+ |
| Model ID | samsung SM-S906W |
| 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 | 7.05 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
391
72.8 IPS |
|
|
Image Classification (HP)
|
100% |
711
132.2 IPS |
|
|
Image Classification (Q)
|
99% |
594
110.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
690
11.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1227
19.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1055
17.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2394
2.79 IPS |
|
|
Pose Estimation (HP)
|
99% |
4380
5.11 IPS |
|
|
Pose Estimation (Q)
|
97% |
4097
4.80 IPS |
|
|
Object Detection (SP)
|
100% |
276
21.9 IPS |
|
|
Object Detection (HP)
|
99% |
378
30.0 IPS |
|
|
Object Detection (Q)
|
85% |
421
33.8 IPS |
|
|
Face Detection (SP)
|
100% |
1219
14.5 IPS |
|
|
Face Detection (HP)
|
100% |
2326
27.6 IPS |
|
|
Face Detection (Q)
|
97% |
2113
25.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1200
9.24 IPS |
|
|
Depth Estimation (HP)
|
98% |
2016
15.6 IPS |
|
|
Depth Estimation (Q)
|
65% |
1991
17.9 IPS |
|
|
Style Transfer (SP)
|
100% |
2865
3.68 IPS |
|
|
Style Transfer (HP)
|
100% |
5970
7.67 IPS |
|
|
Style Transfer (Q)
|
98% |
6051
7.80 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
502
18.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
978
36.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
979
36.3 IPS |
|
|
Text Classification (SP)
|
35% |
24
231.2 IPS |
|
|
Text Classification (HP)
|
35% |
33
295.6 IPS |
|
|
Text Classification (Q)
|
35% |
29
263.6 IPS |
|
|
Machine Translation (SP)
|
100% |
349
6.01 IPS |
|
|
Machine Translation (HP)
|
97% |
424
7.32 IPS |
|
|
Machine Translation (Q)
|
64% |
308
6.33 IPS |
