samsung SM-S938U1
Geekbench AI Score
758
Single Precision Score
27811
Half Precision Score
62897
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 21 2025 03:58 PM |
| Views | 12 |
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
88.6 IPS |
|
|
Image Classification (HP)
|
100% |
21349
3.97 KIPS |
|
|
Image Classification (Q)
|
97% |
49617
9.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
611
9.90 IPS |
|
|
Image Segmentation (HP)
|
100% |
13723
222.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
42292
687.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
788
0.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
123175
143.7 IPS |
|
|
Pose Estimation (Q)
|
98% |
479640
561.4 IPS |
|
|
Object Detection (SP)
|
100% |
436
34.6 IPS |
|
|
Object Detection (HP)
|
100% |
19675
1.56 KIPS |
|
|
Object Detection (Q)
|
85% |
22943
1.85 KIPS |
|
|
Face Detection (SP)
|
100% |
1114
13.2 IPS |
|
|
Face Detection (HP)
|
100% |
44181
525.0 IPS |
|
|
Face Detection (Q)
|
97% |
162402
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
964
7.43 IPS |
|
|
Depth Estimation (HP)
|
99% |
84917
654.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
147341
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1600
2.06 IPS |
|
|
Style Transfer (HP)
|
98% |
99049
127.7 IPS |
|
|
Style Transfer (Q)
|
98% |
496237
639.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
513
18.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54927
2.03 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134913
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
664
886.1 IPS |
|
|
Text Classification (HP)
|
100% |
3927
5.24 KIPS |
|
|
Text Classification (Q)
|
93% |
8093
10.9 KIPS |
|
|
Machine Translation (SP)
|
100% |
1075
18.5 IPS |
|
|
Machine Translation (HP)
|
100% |
4865
83.8 IPS |
|
|
Machine Translation (Q)
|
56% |
3237
83.4 IPS |
