samsung SM-S938U1
Geekbench AI Score
748
Single Precision Score
27869
Half Precision Score
62927
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 21 2025 03:05 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% |
468
87.1 IPS |
|
|
Image Classification (HP)
|
100% |
21348
3.97 KIPS |
|
|
Image Classification (Q)
|
97% |
49642
9.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
597
9.68 IPS |
|
|
Image Segmentation (HP)
|
100% |
13700
222.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
42517
691.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
771
0.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
123774
144.4 IPS |
|
|
Pose Estimation (Q)
|
98% |
480151
562.0 IPS |
|
|
Object Detection (SP)
|
100% |
429
34.0 IPS |
|
|
Object Detection (HP)
|
100% |
19965
1.58 KIPS |
|
|
Object Detection (Q)
|
85% |
22903
1.84 KIPS |
|
|
Face Detection (SP)
|
100% |
1091
13.0 IPS |
|
|
Face Detection (HP)
|
100% |
44327
526.7 IPS |
|
|
Face Detection (Q)
|
97% |
161950
1.93 KIPS |
|
|
Depth Estimation (SP)
|
100% |
952
7.33 IPS |
|
|
Depth Estimation (HP)
|
99% |
84821
653.5 IPS |
|
|
Depth Estimation (Q)
|
63% |
147579
1.37 KIPS |
|
|
Style Transfer (SP)
|
100% |
1591
2.04 IPS |
|
|
Style Transfer (HP)
|
98% |
98949
127.6 IPS |
|
|
Style Transfer (Q)
|
98% |
494701
637.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
511
18.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54811
2.02 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134906
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
658
877.9 IPS |
|
|
Text Classification (HP)
|
100% |
3932
5.25 KIPS |
|
|
Text Classification (Q)
|
93% |
8050
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1079
18.6 IPS |
|
|
Machine Translation (HP)
|
100% |
4878
84.0 IPS |
|
|
Machine Translation (Q)
|
56% |
3267
84.2 IPS |
