samsung SM-S938B
Geekbench AI Score
1144
Single Precision Score
1936
Half Precision Score
1803
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | ManuCH |
| Upload Date | May 10 2025 04:24 PM |
| Views | 7 |
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% |
573
106.6 IPS |
|
|
Image Classification (HP)
|
100% |
1350
251.0 IPS |
|
|
Image Classification (Q)
|
99% |
790
147.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1480
24.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1506
24.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
1641
26.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1716
2.00 IPS |
|
|
Pose Estimation (HP)
|
100% |
2192
2.56 IPS |
|
|
Pose Estimation (Q)
|
96% |
2344
2.75 IPS |
|
|
Object Detection (SP)
|
100% |
497
39.5 IPS |
|
|
Object Detection (HP)
|
100% |
1143
90.7 IPS |
|
|
Object Detection (Q)
|
86% |
1154
92.7 IPS |
|
|
Face Detection (SP)
|
100% |
2756
32.7 IPS |
|
|
Face Detection (HP)
|
100% |
3610
42.9 IPS |
|
|
Face Detection (Q)
|
97% |
3713
44.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1606
12.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
4831
37.3 IPS |
|
|
Depth Estimation (Q)
|
63% |
3781
35.1 IPS |
|
|
Style Transfer (SP)
|
100% |
5525
7.10 IPS |
|
|
Style Transfer (HP)
|
100% |
11754
15.1 IPS |
|
|
Style Transfer (Q)
|
98% |
11281
14.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
616
22.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2013
74.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1870
69.3 IPS |
|
|
Text Classification (SP)
|
100% |
465
620.5 IPS |
|
|
Text Classification (HP)
|
100% |
459
612.6 IPS |
|
|
Text Classification (Q)
|
91% |
717
963.8 IPS |
|
|
Machine Translation (SP)
|
100% |
763
13.1 IPS |
|
|
Machine Translation (HP)
|
100% |
769
13.3 IPS |
|
|
Machine Translation (Q)
|
57% |
490
12.0 IPS |
