Samsung Galaxy S22
Geekbench AI Score
207
Single Precision Score
216
Half Precision Score
549
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | petergrip |
| Upload Date | August 16 2024 07:30 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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% |
86
15.9 IPS |
|
|
Image Classification (HP)
|
100% |
105
19.5 IPS |
|
|
Image Classification (Q)
|
97% |
300
55.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
138
2.23 IPS |
|
|
Image Segmentation (HP)
|
100% |
138
2.23 IPS |
|
|
Image Segmentation (Q)
|
98% |
314
5.11 IPS |
|
|
Pose Estimation (SP)
|
100% |
190
0.22 IPS |
|
|
Pose Estimation (HP)
|
100% |
193
0.22 IPS |
|
|
Pose Estimation (Q)
|
98% |
939
1.10 IPS |
|
|
Object Detection (SP)
|
100% |
129
10.2 IPS |
|
|
Object Detection (HP)
|
100% |
129
10.2 IPS |
|
|
Object Detection (Q)
|
89% |
403
32.3 IPS |
|
|
Face Detection (SP)
|
100% |
359
4.27 IPS |
|
|
Face Detection (HP)
|
100% |
362
4.30 IPS |
|
|
Face Detection (Q)
|
97% |
849
10.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
300
2.31 IPS |
|
|
Depth Estimation (HP)
|
100% |
299
2.30 IPS |
|
|
Depth Estimation (Q)
|
73% |
838
6.85 IPS |
|
|
Style Transfer (SP)
|
100% |
526
0.68 IPS |
|
|
Style Transfer (HP)
|
100% |
526
0.68 IPS |
|
|
Style Transfer (Q)
|
98% |
1339
1.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
148
5.45 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
143
5.30 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
541
20.0 IPS |
|
|
Text Classification (SP)
|
100% |
182
242.7 IPS |
|
|
Text Classification (HP)
|
100% |
182
242.7 IPS |
|
|
Text Classification (Q)
|
91% |
340
457.5 IPS |
|
|
Machine Translation (SP)
|
100% |
337
5.80 IPS |
|
|
Machine Translation (HP)
|
100% |
426
7.34 IPS |
|
|
Machine Translation (Q)
|
57% |
404
9.87 IPS |
