samsung SM-S938U1
Geekbench AI Score
757
Single Precision Score
27737
Half Precision Score
62962
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 22 2025 12:51 AM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| 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% |
471
87.7 IPS |
|
|
Image Classification (HP)
|
100% |
21200
3.94 KIPS |
|
|
Image Classification (Q)
|
97% |
49673
9.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
605
9.80 IPS |
|
|
Image Segmentation (HP)
|
100% |
13295
215.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
42542
691.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
785
0.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
123640
144.3 IPS |
|
|
Pose Estimation (Q)
|
98% |
480035
561.9 IPS |
|
|
Object Detection (SP)
|
100% |
435
34.5 IPS |
|
|
Object Detection (HP)
|
100% |
19751
1.57 KIPS |
|
|
Object Detection (Q)
|
85% |
22845
1.84 KIPS |
|
|
Face Detection (SP)
|
100% |
1104
13.1 IPS |
|
|
Face Detection (HP)
|
100% |
44453
528.2 IPS |
|
|
Face Detection (Q)
|
97% |
162648
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
965
7.44 IPS |
|
|
Depth Estimation (HP)
|
99% |
84925
654.3 IPS |
|
|
Depth Estimation (Q)
|
63% |
146755
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1598
2.05 IPS |
|
|
Style Transfer (HP)
|
98% |
99081
127.8 IPS |
|
|
Style Transfer (Q)
|
98% |
496429
640.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
510
18.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54646
2.02 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
135021
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
676
902.7 IPS |
|
|
Text Classification (HP)
|
100% |
3919
5.23 KIPS |
|
|
Text Classification (Q)
|
93% |
8051
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1085
18.7 IPS |
|
|
Machine Translation (HP)
|
100% |
4889
84.2 IPS |
|
|
Machine Translation (Q)
|
56% |
3280
84.5 IPS |
