Samsung Galaxy S22
Geekbench AI Score
1255
Single Precision Score
1208
Half Precision Score
1758
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 20 2024 08:22 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1188
221.0 IPS |
|
|
Image Classification (HP)
|
100% |
1085
201.7 IPS |
|
|
Image Classification (Q)
|
100% |
1789
332.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1201
19.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1173
19.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
1978
32.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2307
2.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
2178
2.54 IPS |
|
|
Pose Estimation (Q)
|
84% |
3807
4.52 IPS |
|
|
Object Detection (SP)
|
98% |
834
66.4 IPS |
|
|
Object Detection (HP)
|
98% |
774
61.6 IPS |
|
|
Object Detection (Q)
|
83% |
892
72.1 IPS |
|
|
Face Detection (SP)
|
100% |
1632
19.4 IPS |
|
|
Face Detection (HP)
|
100% |
1619
19.2 IPS |
|
|
Face Detection (Q)
|
95% |
2495
29.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
1845
14.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2091
16.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
2752
25.2 IPS |
|
|
Style Transfer (SP)
|
89% |
4414
5.73 IPS |
|
|
Style Transfer (HP)
|
89% |
4431
5.75 IPS |
|
|
Style Transfer (Q)
|
98% |
7543
9.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1010
37.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
847
31.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1827
67.7 IPS |
|
|
Text Classification (SP)
|
100% |
343
458.5 IPS |
|
|
Text Classification (HP)
|
99% |
299
399.6 IPS |
|
|
Text Classification (Q)
|
88% |
605
816.0 IPS |
|
|
Machine Translation (SP)
|
100% |
772
13.3 IPS |
|
|
Machine Translation (HP)
|
100% |
816
14.1 IPS |
|
|
Machine Translation (Q)
|
50% |
410
14.6 IPS |
