samsung SM-S938U1
Geekbench AI Score
760
Single Precision Score
27790
Half Precision Score
62951
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 22 2025 01:34 AM |
| Views | 15 |
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% |
480
89.2 IPS |
|
|
Image Classification (HP)
|
100% |
21591
4.02 KIPS |
|
|
Image Classification (Q)
|
97% |
49651
9.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
615
9.98 IPS |
|
|
Image Segmentation (HP)
|
100% |
13758
223.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
42467
690.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
789
0.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
123459
144.1 IPS |
|
|
Pose Estimation (Q)
|
98% |
480349
562.2 IPS |
|
|
Object Detection (SP)
|
100% |
436
34.6 IPS |
|
|
Object Detection (HP)
|
100% |
19737
1.57 KIPS |
|
|
Object Detection (Q)
|
85% |
22942
1.85 KIPS |
|
|
Face Detection (SP)
|
100% |
1111
13.2 IPS |
|
|
Face Detection (HP)
|
100% |
44260
525.9 IPS |
|
|
Face Detection (Q)
|
97% |
162842
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
965
7.43 IPS |
|
|
Depth Estimation (HP)
|
99% |
84560
651.5 IPS |
|
|
Depth Estimation (Q)
|
63% |
146291
1.35 KIPS |
|
|
Style Transfer (SP)
|
100% |
1596
2.05 IPS |
|
|
Style Transfer (HP)
|
98% |
99014
127.7 IPS |
|
|
Style Transfer (Q)
|
98% |
496125
639.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
503
18.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
53784
1.99 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134963
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
681
908.9 IPS |
|
|
Text Classification (HP)
|
100% |
3920
5.23 KIPS |
|
|
Text Classification (Q)
|
93% |
8084
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1082
18.6 IPS |
|
|
Machine Translation (HP)
|
100% |
4859
83.7 IPS |
|
|
Machine Translation (Q)
|
56% |
3262
84.0 IPS |
