samsung SM-S938B
Geekbench AI Score
950
Single Precision Score
1693
Half Precision Score
1696
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | wolfcam |
| Upload Date | February 24 2025 02:33 PM |
| Views | 4 |
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% |
340
63.2 IPS |
|
|
Image Classification (HP)
|
100% |
873
162.3 IPS |
|
|
Image Classification (Q)
|
99% |
822
153.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1220
19.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1545
25.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1730
28.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1044
1.22 IPS |
|
|
Pose Estimation (HP)
|
100% |
1803
2.10 IPS |
|
|
Pose Estimation (Q)
|
96% |
1831
2.15 IPS |
|
|
Object Detection (SP)
|
100% |
394
31.3 IPS |
|
|
Object Detection (HP)
|
100% |
917
72.7 IPS |
|
|
Object Detection (Q)
|
86% |
941
75.6 IPS |
|
|
Face Detection (SP)
|
100% |
2220
26.4 IPS |
|
|
Face Detection (HP)
|
100% |
3591
42.7 IPS |
|
|
Face Detection (Q)
|
97% |
3979
47.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
1128
8.69 IPS |
|
|
Depth Estimation (HP)
|
99% |
3069
23.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
2511
23.3 IPS |
|
|
Style Transfer (SP)
|
100% |
3704
4.76 IPS |
|
|
Style Transfer (HP)
|
100% |
8268
10.6 IPS |
|
|
Style Transfer (Q)
|
98% |
8275
10.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
572
21.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1462
54.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1440
53.4 IPS |
|
|
Text Classification (SP)
|
100% |
659
879.6 IPS |
|
|
Text Classification (HP)
|
100% |
657
876.6 IPS |
|
|
Text Classification (Q)
|
91% |
1056
1.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
1014
17.5 IPS |
|
|
Machine Translation (HP)
|
100% |
995
17.1 IPS |
|
|
Machine Translation (Q)
|
57% |
642
15.7 IPS |
