Samsung Galaxy S22
Geekbench AI Score
242
Single Precision Score
240
Half Precision Score
589
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | PorywaczPiotrus |
| Upload Date | January 08 2026 10:29 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
179
33.4 IPS |
|
|
Image Classification (HP)
|
100% |
178
33.1 IPS |
|
|
Image Classification (Q)
|
99% |
521
97.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
229
3.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
228
3.70 IPS |
|
|
Image Segmentation (Q)
|
98% |
552
8.97 IPS |
|
|
Pose Estimation (SP)
|
100% |
296
0.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
269
0.31 IPS |
|
|
Pose Estimation (Q)
|
98% |
954
1.12 IPS |
|
|
Object Detection (SP)
|
100% |
127
10.1 IPS |
|
|
Object Detection (HP)
|
100% |
128
10.1 IPS |
|
|
Object Detection (Q)
|
87% |
402
32.3 IPS |
|
|
Face Detection (SP)
|
100% |
359
4.27 IPS |
|
|
Face Detection (HP)
|
100% |
361
4.29 IPS |
|
|
Face Detection (Q)
|
97% |
852
10.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
295
2.27 IPS |
|
|
Depth Estimation (HP)
|
99% |
297
2.29 IPS |
|
|
Depth Estimation (Q)
|
64% |
762
6.92 IPS |
|
|
Style Transfer (SP)
|
100% |
520
0.67 IPS |
|
|
Style Transfer (HP)
|
100% |
525
0.68 IPS |
|
|
Style Transfer (Q)
|
98% |
1330
1.71 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
143
5.28 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
142
5.25 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
552
20.5 IPS |
|
|
Text Classification (SP)
|
100% |
183
244.0 IPS |
|
|
Text Classification (HP)
|
100% |
182
243.5 IPS |
|
|
Text Classification (Q)
|
91% |
338
454.8 IPS |
|
|
Machine Translation (SP)
|
100% |
319
5.50 IPS |
|
|
Machine Translation (HP)
|
100% |
321
5.53 IPS |
|
|
Machine Translation (Q)
|
57% |
287
7.00 IPS |
