Samsung Galaxy S22
Geekbench AI Score
982
Single Precision Score
1139
Half Precision Score
1166
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | petergrip |
| Upload Date | August 16 2024 07:11 AM |
| Views | 33 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
385
71.6 IPS |
|
|
Image Classification (HP)
|
100% |
456
84.8 IPS |
|
|
Image Classification (Q)
|
99% |
431
80.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1212
19.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1474
23.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1426
23.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1790
2.09 IPS |
|
|
Pose Estimation (HP)
|
100% |
2265
2.64 IPS |
|
|
Pose Estimation (Q)
|
96% |
2383
2.79 IPS |
|
|
Object Detection (SP)
|
100% |
450
35.7 IPS |
|
|
Object Detection (HP)
|
100% |
492
39.0 IPS |
|
|
Object Detection (Q)
|
89% |
368
29.4 IPS |
|
|
Face Detection (SP)
|
100% |
1885
22.4 IPS |
|
|
Face Detection (HP)
|
100% |
1885
22.4 IPS |
|
|
Face Detection (Q)
|
97% |
1872
22.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
2110
16.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2651
20.4 IPS |
|
|
Depth Estimation (Q)
|
73% |
2336
19.1 IPS |
|
|
Style Transfer (SP)
|
100% |
5626
7.23 IPS |
|
|
Style Transfer (HP)
|
100% |
7573
9.73 IPS |
|
|
Style Transfer (Q)
|
98% |
7802
10.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
995
36.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1288
47.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1349
50.0 IPS |
|
|
Text Classification (SP)
|
100% |
249
332.1 IPS |
|
|
Text Classification (HP)
|
100% |
252
335.8 IPS |
|
|
Text Classification (Q)
|
91% |
487
654.3 IPS |
|
|
Machine Translation (SP)
|
100% |
404
6.96 IPS |
|
|
Machine Translation (HP)
|
100% |
402
6.93 IPS |
|
|
Machine Translation (Q)
|
57% |
386
9.44 IPS |
