Samsung Galaxy S22
Geekbench AI Score
295
Single Precision Score
295
Half Precision Score
759
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | PorywaczPiotrus |
| Upload Date | January 08 2026 10:02 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S901B |
| 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% |
181
33.6 IPS |
|
|
Image Classification (HP)
|
100% |
179
33.3 IPS |
|
|
Image Classification (Q)
|
99% |
530
98.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
228
3.70 IPS |
|
|
Image Segmentation (HP)
|
100% |
230
3.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
556
9.05 IPS |
|
|
Pose Estimation (SP)
|
100% |
298
0.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
308
0.36 IPS |
|
|
Pose Estimation (Q)
|
98% |
1267
1.48 IPS |
|
|
Object Detection (SP)
|
100% |
172
13.6 IPS |
|
|
Object Detection (HP)
|
100% |
173
13.8 IPS |
|
|
Object Detection (Q)
|
87% |
564
45.3 IPS |
|
|
Face Detection (SP)
|
100% |
457
5.43 IPS |
|
|
Face Detection (HP)
|
100% |
461
5.48 IPS |
|
|
Face Detection (Q)
|
97% |
1171
14.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
380
2.93 IPS |
|
|
Depth Estimation (HP)
|
99% |
383
2.95 IPS |
|
|
Depth Estimation (Q)
|
64% |
1009
9.15 IPS |
|
|
Style Transfer (SP)
|
100% |
660
0.85 IPS |
|
|
Style Transfer (HP)
|
100% |
664
0.85 IPS |
|
|
Style Transfer (Q)
|
98% |
1717
2.21 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
191
7.04 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
188
6.95 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
775
28.7 IPS |
|
|
Text Classification (SP)
|
100% |
261
347.8 IPS |
|
|
Text Classification (HP)
|
100% |
261
348.0 IPS |
|
|
Text Classification (Q)
|
91% |
494
664.1 IPS |
|
|
Machine Translation (SP)
|
100% |
417
7.19 IPS |
|
|
Machine Translation (HP)
|
100% |
404
6.96 IPS |
|
|
Machine Translation (Q)
|
57% |
393
9.60 IPS |
