samsung SM-S938B
Geekbench AI Score
1346
Single Precision Score
2180
Half Precision Score
2115
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | V-One |
| Upload Date | April 14 2025 09:17 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938B |
| Model ID | samsung SM-S938B |
| 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% |
757
140.7 IPS |
|
|
Image Classification (HP)
|
100% |
825
153.3 IPS |
|
|
Image Classification (Q)
|
99% |
942
175.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1568
25.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1728
28.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
1404
22.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1731
2.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
2969
3.46 IPS |
|
|
Pose Estimation (Q)
|
96% |
2968
3.48 IPS |
|
|
Object Detection (SP)
|
100% |
577
45.7 IPS |
|
|
Object Detection (HP)
|
100% |
1296
102.8 IPS |
|
|
Object Detection (Q)
|
86% |
1076
86.5 IPS |
|
|
Face Detection (SP)
|
100% |
3200
38.0 IPS |
|
|
Face Detection (HP)
|
100% |
3960
47.1 IPS |
|
|
Face Detection (Q)
|
97% |
4051
48.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1691
13.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
4949
38.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
4083
38.0 IPS |
|
|
Style Transfer (SP)
|
100% |
6290
8.09 IPS |
|
|
Style Transfer (HP)
|
100% |
13455
17.3 IPS |
|
|
Style Transfer (Q)
|
98% |
13368
17.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
675
24.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2299
84.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2319
85.9 IPS |
|
|
Text Classification (SP)
|
100% |
674
899.1 IPS |
|
|
Text Classification (HP)
|
100% |
689
919.3 IPS |
|
|
Text Classification (Q)
|
91% |
1115
1.50 KIPS |
|
|
Machine Translation (SP)
|
100% |
1070
18.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1061
18.3 IPS |
|
|
Machine Translation (Q)
|
57% |
744
18.2 IPS |
