Samsung Galaxy S22+
Geekbench AI Score
975
Single Precision Score
765
Half Precision Score
782
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | ShowXTech |
| Upload Date | June 18 2025 01:53 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S22+ |
| Model ID | samsung SM-S906B |
| Motherboard | s5e9925 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.82 GHz |
| Cluster 1 | 4 Cores @ 1.82 GHz |
| Cluster 2 | 3 Cores @ 2.52 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.10 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
411
76.4 IPS |
|
|
Image Classification (HP)
|
100% |
288
53.6 IPS |
|
|
Image Classification (Q)
|
99% |
275
51.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1267
20.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1069
17.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
1036
16.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1836
2.14 IPS |
|
|
Pose Estimation (HP)
|
100% |
1120
1.31 IPS |
|
|
Pose Estimation (Q)
|
96% |
1066
1.25 IPS |
|
|
Object Detection (SP)
|
100% |
427
33.9 IPS |
|
|
Object Detection (HP)
|
100% |
337
26.8 IPS |
|
|
Object Detection (Q)
|
86% |
336
27.0 IPS |
|
|
Face Detection (SP)
|
100% |
1960
23.3 IPS |
|
|
Face Detection (HP)
|
100% |
1867
22.2 IPS |
|
|
Face Detection (Q)
|
97% |
1673
20.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
2088
16.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1384
10.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
1177
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
5472
7.03 IPS |
|
|
Style Transfer (HP)
|
100% |
3450
4.43 IPS |
|
|
Style Transfer (Q)
|
98% |
3462
4.46 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
933
34.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
722
26.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
710
26.3 IPS |
|
|
Text Classification (SP)
|
100% |
234
312.9 IPS |
|
|
Text Classification (HP)
|
100% |
242
322.7 IPS |
|
|
Text Classification (Q)
|
91% |
477
640.8 IPS |
|
|
Machine Translation (SP)
|
100% |
389
6.70 IPS |
|
|
Machine Translation (HP)
|
100% |
382
6.58 IPS |
|
|
Machine Translation (Q)
|
57% |
366
8.95 IPS |
