samsung SM-S938U1
Geekbench AI Score
765
Single Precision Score
27906
Half Precision Score
62959
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 21 2025 06:15 AM |
| 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% |
481
89.5 IPS |
|
|
Image Classification (HP)
|
100% |
21565
4.01 KIPS |
|
|
Image Classification (Q)
|
97% |
49595
9.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
618
10.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
13711
222.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
42339
688.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
798
0.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
123852
144.5 IPS |
|
|
Pose Estimation (Q)
|
98% |
480007
561.8 IPS |
|
|
Object Detection (SP)
|
100% |
441
34.9 IPS |
|
|
Object Detection (HP)
|
100% |
19848
1.57 KIPS |
|
|
Object Detection (Q)
|
85% |
22934
1.85 KIPS |
|
|
Face Detection (SP)
|
100% |
1122
13.3 IPS |
|
|
Face Detection (HP)
|
100% |
44430
527.9 IPS |
|
|
Face Detection (Q)
|
97% |
163003
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
979
7.55 IPS |
|
|
Depth Estimation (HP)
|
99% |
84987
654.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
147395
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1613
2.07 IPS |
|
|
Style Transfer (HP)
|
98% |
98766
127.4 IPS |
|
|
Style Transfer (Q)
|
98% |
495135
638.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
515
19.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54928
2.03 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
135033
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
666
889.1 IPS |
|
|
Text Classification (HP)
|
100% |
3923
5.24 KIPS |
|
|
Text Classification (Q)
|
93% |
8047
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1093
18.8 IPS |
|
|
Machine Translation (HP)
|
100% |
4904
84.5 IPS |
|
|
Machine Translation (Q)
|
56% |
3275
84.4 IPS |
