samsung SM-S938U1
Geekbench AI Score
761
Single Precision Score
27870
Half Precision Score
63054
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 20 2025 11:02 PM |
| Views | 13 |
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% |
476
88.5 IPS |
|
|
Image Classification (HP)
|
100% |
21506
4.00 KIPS |
|
|
Image Classification (Q)
|
97% |
49599
9.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
613
9.94 IPS |
|
|
Image Segmentation (HP)
|
100% |
13686
221.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
42776
695.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
789
0.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
123622
144.2 IPS |
|
|
Pose Estimation (Q)
|
98% |
480220
562.1 IPS |
|
|
Object Detection (SP)
|
100% |
437
34.6 IPS |
|
|
Object Detection (HP)
|
100% |
19738
1.57 KIPS |
|
|
Object Detection (Q)
|
85% |
22942
1.85 KIPS |
|
|
Face Detection (SP)
|
100% |
1116
13.3 IPS |
|
|
Face Detection (HP)
|
100% |
44453
528.2 IPS |
|
|
Face Detection (Q)
|
97% |
162770
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
969
7.47 IPS |
|
|
Depth Estimation (HP)
|
99% |
84891
654.0 IPS |
|
|
Depth Estimation (Q)
|
63% |
147441
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1605
2.06 IPS |
|
|
Style Transfer (HP)
|
98% |
98971
127.6 IPS |
|
|
Style Transfer (Q)
|
98% |
495981
639.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
507
18.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54948
2.03 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
135141
5.01 KIPS |
|
|
Text Classification (SP)
|
100% |
682
910.5 IPS |
|
|
Text Classification (HP)
|
100% |
3937
5.25 KIPS |
|
|
Text Classification (Q)
|
93% |
8053
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1086
18.7 IPS |
|
|
Machine Translation (HP)
|
100% |
4874
84.0 IPS |
|
|
Machine Translation (Q)
|
56% |
3281
84.5 IPS |
