samsung SM-S938U1
Geekbench AI Score
760
Single Precision Score
27776
Half Precision Score
62967
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 22 2025 01:17 AM |
| 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% |
477
88.7 IPS |
|
|
Image Classification (HP)
|
100% |
21298
3.96 KIPS |
|
|
Image Classification (Q)
|
97% |
49608
9.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
611
9.91 IPS |
|
|
Image Segmentation (HP)
|
100% |
13682
221.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
42563
692.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
792
0.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
123674
144.3 IPS |
|
|
Pose Estimation (Q)
|
98% |
480587
562.5 IPS |
|
|
Object Detection (SP)
|
100% |
438
34.7 IPS |
|
|
Object Detection (HP)
|
100% |
19747
1.57 KIPS |
|
|
Object Detection (Q)
|
85% |
22934
1.85 KIPS |
|
|
Face Detection (SP)
|
100% |
1109
13.2 IPS |
|
|
Face Detection (HP)
|
100% |
44372
527.2 IPS |
|
|
Face Detection (Q)
|
97% |
163054
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
975
7.51 IPS |
|
|
Depth Estimation (HP)
|
99% |
84852
653.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
147362
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1605
2.06 IPS |
|
|
Style Transfer (HP)
|
98% |
98990
127.6 IPS |
|
|
Style Transfer (Q)
|
98% |
493692
636.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
505
18.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
53542
1.98 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
135012
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
678
905.5 IPS |
|
|
Text Classification (HP)
|
100% |
3933
5.25 KIPS |
|
|
Text Classification (Q)
|
93% |
8052
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1082
18.6 IPS |
|
|
Machine Translation (HP)
|
100% |
4894
84.3 IPS |
|
|
Machine Translation (Q)
|
56% |
3265
84.1 IPS |
