Samsung Galaxy S22 Ultra
Geekbench AI Score
1651
Single Precision Score
1618
Half Precision Score
2479
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 20 2025 06:37 AM |
| Views | 7 |
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 Ultra |
| Model ID | samsung SM-S908U |
| 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% |
1358
252.5 IPS |
|
|
Image Classification (HP)
|
100% |
1330
247.3 IPS |
|
|
Image Classification (Q)
|
100% |
1972
366.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1431
23.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1356
22.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2117
34.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2345
2.74 IPS |
|
|
Pose Estimation (HP)
|
100% |
2325
2.71 IPS |
|
|
Pose Estimation (Q)
|
84% |
4780
5.67 IPS |
|
|
Object Detection (SP)
|
98% |
1232
98.0 IPS |
|
|
Object Detection (HP)
|
98% |
1262
100.4 IPS |
|
|
Object Detection (Q)
|
83% |
1761
142.3 IPS |
|
|
Face Detection (SP)
|
100% |
2189
26.0 IPS |
|
|
Face Detection (HP)
|
100% |
2218
26.4 IPS |
|
|
Face Detection (Q)
|
95% |
3855
46.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
2464
19.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
2386
18.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
3983
36.5 IPS |
|
|
Style Transfer (SP)
|
89% |
5251
6.82 IPS |
|
|
Style Transfer (HP)
|
89% |
5245
6.81 IPS |
|
|
Style Transfer (Q)
|
98% |
10155
13.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1257
46.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1243
45.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2355
87.3 IPS |
|
|
Text Classification (SP)
|
100% |
567
756.3 IPS |
|
|
Text Classification (HP)
|
99% |
580
773.7 IPS |
|
|
Text Classification (Q)
|
88% |
1141
1.54 KIPS |
|
|
Machine Translation (SP)
|
100% |
1334
23.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1165
20.1 IPS |
|
|
Machine Translation (Q)
|
50% |
597
21.2 IPS |
