Samsung Galaxy S22 Ultra
Geekbench AI Score
1379
Single Precision Score
1321
Half Precision Score
2018
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 20 2025 08:17 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 10.27 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1386
257.8 IPS |
|
|
Image Classification (HP)
|
100% |
1212
225.4 IPS |
|
|
Image Classification (Q)
|
100% |
1868
347.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1334
21.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1309
21.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2122
34.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2313
2.70 IPS |
|
|
Pose Estimation (HP)
|
100% |
2226
2.60 IPS |
|
|
Pose Estimation (Q)
|
84% |
5009
5.94 IPS |
|
|
Object Detection (SP)
|
98% |
1186
94.3 IPS |
|
|
Object Detection (HP)
|
98% |
941
74.9 IPS |
|
|
Object Detection (Q)
|
83% |
1249
100.9 IPS |
|
|
Face Detection (SP)
|
100% |
1609
19.1 IPS |
|
|
Face Detection (HP)
|
100% |
1932
23.0 IPS |
|
|
Face Detection (Q)
|
95% |
3448
41.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
2287
17.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2241
17.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
3051
27.9 IPS |
|
|
Style Transfer (SP)
|
89% |
4405
5.72 IPS |
|
|
Style Transfer (HP)
|
89% |
4100
5.32 IPS |
|
|
Style Transfer (Q)
|
98% |
7544
9.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
938
34.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
929
34.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2033
75.3 IPS |
|
|
Text Classification (SP)
|
100% |
373
497.9 IPS |
|
|
Text Classification (HP)
|
99% |
383
511.1 IPS |
|
|
Text Classification (Q)
|
88% |
708
954.6 IPS |
|
|
Machine Translation (SP)
|
100% |
865
14.9 IPS |
|
|
Machine Translation (HP)
|
100% |
771
13.3 IPS |
|
|
Machine Translation (Q)
|
50% |
397
14.1 IPS |
