Samsung Galaxy S22 Ultra
Geekbench AI Score
1353
Single Precision Score
1350
Half Precision Score
1966
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 17 2024 02:27 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908B |
| 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 | 7.12 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
889
165.3 IPS |
|
|
Image Classification (HP)
|
100% |
972
180.7 IPS |
|
|
Image Classification (Q)
|
100% |
1394
259.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1070
17.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1071
17.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
1506
24.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2056
2.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
2051
2.39 IPS |
|
|
Pose Estimation (Q)
|
84% |
4220
5.01 IPS |
|
|
Object Detection (SP)
|
98% |
1014
80.7 IPS |
|
|
Object Detection (HP)
|
98% |
929
74.0 IPS |
|
|
Object Detection (Q)
|
83% |
1406
113.6 IPS |
|
|
Face Detection (SP)
|
100% |
2007
23.8 IPS |
|
|
Face Detection (HP)
|
100% |
2009
23.9 IPS |
|
|
Face Detection (Q)
|
95% |
3035
36.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
2272
17.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2256
17.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
3297
30.2 IPS |
|
|
Style Transfer (SP)
|
89% |
4752
6.17 IPS |
|
|
Style Transfer (HP)
|
89% |
4719
6.13 IPS |
|
|
Style Transfer (Q)
|
98% |
8685
11.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1071
39.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1077
39.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2139
79.2 IPS |
|
|
Text Classification (SP)
|
100% |
419
559.3 IPS |
|
|
Text Classification (HP)
|
99% |
420
560.3 IPS |
|
|
Text Classification (Q)
|
88% |
745
1.00 KIPS |
|
|
Machine Translation (SP)
|
100% |
1073
18.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1052
18.1 IPS |
|
|
Machine Translation (Q)
|
50% |
501
17.8 IPS |
