samsung SM-S938U
Geekbench AI Score
702
Single Precision Score
700
Half Precision Score
1568
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | sam09966 |
| Upload Date | May 04 2025 06:00 PM |
| Views | 7 |
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% |
433
80.6 IPS |
|
|
Image Classification (HP)
|
100% |
433
80.6 IPS |
|
|
Image Classification (Q)
|
99% |
1080
201.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
545
8.83 IPS |
|
|
Image Segmentation (HP)
|
100% |
559
9.06 IPS |
|
|
Image Segmentation (Q)
|
98% |
1117
18.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
734
0.86 IPS |
|
|
Pose Estimation (HP)
|
100% |
724
0.84 IPS |
|
|
Pose Estimation (Q)
|
98% |
2830
3.31 IPS |
|
|
Object Detection (SP)
|
100% |
400
31.8 IPS |
|
|
Object Detection (HP)
|
100% |
404
32.0 IPS |
|
|
Object Detection (Q)
|
87% |
1105
88.6 IPS |
|
|
Face Detection (SP)
|
100% |
989
11.8 IPS |
|
|
Face Detection (HP)
|
100% |
969
11.5 IPS |
|
|
Face Detection (Q)
|
97% |
2402
28.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
879
6.78 IPS |
|
|
Depth Estimation (HP)
|
99% |
863
6.65 IPS |
|
|
Depth Estimation (Q)
|
64% |
1931
17.5 IPS |
|
|
Style Transfer (SP)
|
100% |
1524
1.96 IPS |
|
|
Style Transfer (HP)
|
100% |
1516
1.95 IPS |
|
|
Style Transfer (Q)
|
98% |
4223
5.45 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
471
17.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
479
17.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1754
65.0 IPS |
|
|
Text Classification (SP)
|
100% |
664
885.9 IPS |
|
|
Text Classification (HP)
|
100% |
658
878.5 IPS |
|
|
Text Classification (Q)
|
91% |
1052
1.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
1018
17.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1007
17.3 IPS |
|
|
Machine Translation (Q)
|
57% |
661
16.2 IPS |
