Samsung Galaxy S22
Geekbench AI Score
1358
Single Precision Score
1344
Half Precision Score
1909
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | paultissue |
| Upload Date | September 03 2025 11:58 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 1 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S901U |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 7.05 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1179
219.3 IPS |
|
|
Image Classification (HP)
|
100% |
1120
208.4 IPS |
|
|
Image Classification (Q)
|
100% |
1570
291.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1230
19.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
1244
20.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1800
29.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2227
2.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
2051
2.39 IPS |
|
|
Pose Estimation (Q)
|
84% |
4189
4.97 IPS |
|
|
Object Detection (SP)
|
98% |
1072
85.3 IPS |
|
|
Object Detection (HP)
|
98% |
1073
85.4 IPS |
|
|
Object Detection (Q)
|
83% |
1421
114.8 IPS |
|
|
Face Detection (SP)
|
100% |
1983
23.6 IPS |
|
|
Face Detection (HP)
|
100% |
1735
20.6 IPS |
|
|
Face Detection (Q)
|
95% |
3036
36.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
1706
13.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
2280
17.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
2934
26.9 IPS |
|
|
Style Transfer (SP)
|
89% |
4585
5.95 IPS |
|
|
Style Transfer (HP)
|
89% |
4569
5.93 IPS |
|
|
Style Transfer (Q)
|
98% |
8757
11.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1092
40.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
945
34.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1819
67.4 IPS |
|
|
Text Classification (SP)
|
100% |
380
507.5 IPS |
|
|
Text Classification (HP)
|
99% |
379
506.0 IPS |
|
|
Text Classification (Q)
|
88% |
616
830.4 IPS |
|
|
Machine Translation (SP)
|
100% |
961
16.6 IPS |
|
|
Machine Translation (HP)
|
100% |
971
16.7 IPS |
|
|
Machine Translation (Q)
|
50% |
438
15.6 IPS |
