Samsung Galaxy S22 Ultra
Geekbench AI Score
1505
Single Precision Score
1482
Half Precision Score
2183
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 06 2025 08:59 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 1 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908N |
| 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 | 10.94 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1324
246.3 IPS |
|
|
Image Classification (HP)
|
100% |
1233
229.3 IPS |
|
|
Image Classification (Q)
|
100% |
1934
359.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1438
23.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1454
23.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
2106
34.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2253
2.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
2244
2.62 IPS |
|
|
Pose Estimation (Q)
|
84% |
4794
5.69 IPS |
|
|
Object Detection (SP)
|
98% |
1088
86.6 IPS |
|
|
Object Detection (HP)
|
98% |
1102
87.7 IPS |
|
|
Object Detection (Q)
|
83% |
1613
130.3 IPS |
|
|
Face Detection (SP)
|
100% |
2318
27.5 IPS |
|
|
Face Detection (HP)
|
100% |
2280
27.1 IPS |
|
|
Face Detection (Q)
|
95% |
3543
42.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
2526
19.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
2480
19.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
3421
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
4725
6.13 IPS |
|
|
Style Transfer (HP)
|
89% |
4527
5.88 IPS |
|
|
Style Transfer (Q)
|
98% |
8720
11.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1062
39.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1066
39.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2139
79.3 IPS |
|
|
Text Classification (SP)
|
100% |
422
562.7 IPS |
|
|
Text Classification (HP)
|
99% |
420
560.1 IPS |
|
|
Text Classification (Q)
|
88% |
728
982.1 IPS |
|
|
Machine Translation (SP)
|
100% |
1032
17.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1006
17.3 IPS |
|
|
Machine Translation (Q)
|
50% |
476
16.9 IPS |
