samsung SM-S938U1
Geekbench AI Score
659
Single Precision Score
664
Half Precision Score
1445
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 20 2025 04:08 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938U1 |
| Model ID | samsung SM-S938U1 |
| 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% |
446
83.0 IPS |
|
|
Image Classification (HP)
|
100% |
445
82.7 IPS |
|
|
Image Classification (Q)
|
99% |
1101
205.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
569
9.22 IPS |
|
|
Image Segmentation (HP)
|
100% |
571
9.26 IPS |
|
|
Image Segmentation (Q)
|
98% |
1130
18.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
706
0.82 IPS |
|
|
Pose Estimation (HP)
|
100% |
736
0.86 IPS |
|
|
Pose Estimation (Q)
|
98% |
2688
3.15 IPS |
|
|
Object Detection (SP)
|
100% |
382
30.3 IPS |
|
|
Object Detection (HP)
|
100% |
383
30.4 IPS |
|
|
Object Detection (Q)
|
87% |
999
80.1 IPS |
|
|
Face Detection (SP)
|
100% |
917
10.9 IPS |
|
|
Face Detection (HP)
|
100% |
957
11.4 IPS |
|
|
Face Detection (Q)
|
97% |
2230
26.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
856
6.59 IPS |
|
|
Depth Estimation (HP)
|
99% |
814
6.27 IPS |
|
|
Depth Estimation (Q)
|
64% |
1864
16.9 IPS |
|
|
Style Transfer (SP)
|
100% |
1424
1.83 IPS |
|
|
Style Transfer (HP)
|
100% |
1290
1.66 IPS |
|
|
Style Transfer (Q)
|
98% |
3267
4.21 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
430
15.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
458
16.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1601
59.3 IPS |
|
|
Text Classification (SP)
|
100% |
538
718.7 IPS |
|
|
Text Classification (HP)
|
100% |
540
720.5 IPS |
|
|
Text Classification (Q)
|
91% |
829
1.11 KIPS |
|
|
Machine Translation (SP)
|
100% |
881
15.2 IPS |
|
|
Machine Translation (HP)
|
100% |
949
16.3 IPS |
|
|
Machine Translation (Q)
|
57% |
660
16.1 IPS |
