samsung SM-S938U1
Geekbench AI Score
756
Single Precision Score
27845
Half Precision Score
62823
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 21 2025 02:34 PM |
| 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% |
474
88.1 IPS |
|
|
Image Classification (HP)
|
100% |
21474
3.99 KIPS |
|
|
Image Classification (Q)
|
97% |
49446
9.23 KIPS |
|
|
Image Segmentation (SP)
|
100% |
612
9.92 IPS |
|
|
Image Segmentation (HP)
|
100% |
13764
223.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
42472
690.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
792
0.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
122908
143.4 IPS |
|
|
Pose Estimation (Q)
|
98% |
480110
561.9 IPS |
|
|
Object Detection (SP)
|
100% |
437
34.6 IPS |
|
|
Object Detection (HP)
|
100% |
19753
1.57 KIPS |
|
|
Object Detection (Q)
|
85% |
22902
1.84 KIPS |
|
|
Face Detection (SP)
|
100% |
1117
13.3 IPS |
|
|
Face Detection (HP)
|
100% |
44424
527.9 IPS |
|
|
Face Detection (Q)
|
97% |
162879
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
969
7.47 IPS |
|
|
Depth Estimation (HP)
|
99% |
84588
651.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
146455
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1599
2.06 IPS |
|
|
Style Transfer (HP)
|
98% |
99149
127.9 IPS |
|
|
Style Transfer (Q)
|
98% |
495435
638.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
500
18.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54854
2.03 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134977
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
660
881.5 IPS |
|
|
Text Classification (HP)
|
100% |
3927
5.24 KIPS |
|
|
Text Classification (Q)
|
93% |
8039
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1077
18.5 IPS |
|
|
Machine Translation (HP)
|
100% |
4866
83.8 IPS |
|
|
Machine Translation (Q)
|
56% |
3234
83.3 IPS |
