samsung SM-S938B
Geekbench AI Score
1212
Single Precision Score
2139
Half Precision Score
2071
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 07 2025 10:18 PM |
| Views | 1 |
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% |
661
122.9 IPS |
|
|
Image Classification (HP)
|
100% |
1681
312.6 IPS |
|
|
Image Classification (Q)
|
99% |
1661
309.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1449
23.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2023
32.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1829
29.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1695
1.98 IPS |
|
|
Pose Estimation (HP)
|
100% |
2550
2.98 IPS |
|
|
Pose Estimation (Q)
|
96% |
2489
2.92 IPS |
|
|
Object Detection (SP)
|
100% |
505
40.1 IPS |
|
|
Object Detection (HP)
|
100% |
1177
93.4 IPS |
|
|
Object Detection (Q)
|
86% |
1010
81.1 IPS |
|
|
Face Detection (SP)
|
100% |
2861
34.0 IPS |
|
|
Face Detection (HP)
|
100% |
3540
42.1 IPS |
|
|
Face Detection (Q)
|
97% |
4680
55.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1669
12.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
4948
38.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
4057
37.7 IPS |
|
|
Style Transfer (SP)
|
100% |
5775
7.42 IPS |
|
|
Style Transfer (HP)
|
100% |
12067
15.5 IPS |
|
|
Style Transfer (Q)
|
98% |
11066
14.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
646
23.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1953
72.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1919
71.1 IPS |
|
|
Text Classification (SP)
|
100% |
538
718.7 IPS |
|
|
Text Classification (HP)
|
100% |
539
720.0 IPS |
|
|
Text Classification (Q)
|
91% |
833
1.12 KIPS |
|
|
Machine Translation (SP)
|
100% |
873
15.0 IPS |
|
|
Machine Translation (HP)
|
100% |
883
15.2 IPS |
|
|
Machine Translation (Q)
|
57% |
566
13.8 IPS |
