samsung SM-S938U1
Geekbench AI Score
753
Single Precision Score
27888
Half Precision Score
62952
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 21 2025 04:09 AM |
| Views | 11 |
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% |
21627
4.02 KIPS |
|
|
Image Classification (Q)
|
97% |
49630
9.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
611
9.91 IPS |
|
|
Image Segmentation (HP)
|
100% |
13759
223.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
42406
689.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
786
0.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
121572
141.9 IPS |
|
|
Pose Estimation (Q)
|
98% |
480536
562.4 IPS |
|
|
Object Detection (SP)
|
100% |
431
34.2 IPS |
|
|
Object Detection (HP)
|
100% |
19976
1.58 KIPS |
|
|
Object Detection (Q)
|
85% |
22925
1.85 KIPS |
|
|
Face Detection (SP)
|
100% |
1100
13.1 IPS |
|
|
Face Detection (HP)
|
100% |
44529
529.1 IPS |
|
|
Face Detection (Q)
|
97% |
162949
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
955
7.36 IPS |
|
|
Depth Estimation (HP)
|
99% |
85027
655.1 IPS |
|
|
Depth Estimation (Q)
|
63% |
146904
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1595
2.05 IPS |
|
|
Style Transfer (HP)
|
98% |
98903
127.5 IPS |
|
|
Style Transfer (Q)
|
98% |
496274
639.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
503
18.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54786
2.02 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134982
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
658
878.5 IPS |
|
|
Text Classification (HP)
|
100% |
3920
5.23 KIPS |
|
|
Text Classification (Q)
|
93% |
8060
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1081
18.6 IPS |
|
|
Machine Translation (HP)
|
100% |
4897
84.4 IPS |
|
|
Machine Translation (Q)
|
56% |
3262
84.0 IPS |
