samsung SM-S938U
Geekbench AI Score
558
Single Precision Score
540
Half Precision Score
1177
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Ivianson |
| Upload Date | April 29 2025 07:01 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938U |
| Model ID | samsung SM-S938U |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
438
81.5 IPS |
|
|
Image Classification (HP)
|
100% |
432
80.3 IPS |
|
|
Image Classification (Q)
|
99% |
1073
200.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
553
8.96 IPS |
|
|
Image Segmentation (HP)
|
100% |
559
9.06 IPS |
|
|
Image Segmentation (Q)
|
98% |
1051
17.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
691
0.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
576
0.67 IPS |
|
|
Pose Estimation (Q)
|
98% |
2114
2.48 IPS |
|
|
Object Detection (SP)
|
100% |
304
24.1 IPS |
|
|
Object Detection (HP)
|
100% |
337
26.7 IPS |
|
|
Object Detection (Q)
|
87% |
881
70.7 IPS |
|
|
Face Detection (SP)
|
100% |
852
10.1 IPS |
|
|
Face Detection (HP)
|
100% |
847
10.1 IPS |
|
|
Face Detection (Q)
|
97% |
1969
23.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
758
5.84 IPS |
|
|
Depth Estimation (HP)
|
99% |
594
4.58 IPS |
|
|
Depth Estimation (Q)
|
64% |
1260
11.4 IPS |
|
|
Style Transfer (SP)
|
100% |
1157
1.49 IPS |
|
|
Style Transfer (HP)
|
100% |
1091
1.40 IPS |
|
|
Style Transfer (Q)
|
98% |
2638
3.40 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
290
10.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
290
10.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1021
37.8 IPS |
|
|
Text Classification (SP)
|
100% |
369
492.2 IPS |
|
|
Text Classification (HP)
|
100% |
369
492.5 IPS |
|
|
Text Classification (Q)
|
91% |
670
900.0 IPS |
|
|
Machine Translation (SP)
|
100% |
727
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
771
13.3 IPS |
|
|
Machine Translation (Q)
|
57% |
547
13.4 IPS |
