samsung SM-S938B
Geekbench AI Score
2856
Single Precision Score
2829
Half Precision Score
5161
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 19 2025 12:29 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1902
353.7 IPS |
|
|
Image Classification (HP)
|
100% |
1990
370.1 IPS |
|
|
Image Classification (Q)
|
100% |
4370
812.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2351
38.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2352
38.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
5227
85.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
5723
6.68 IPS |
|
|
Pose Estimation (HP)
|
100% |
5466
6.38 IPS |
|
|
Pose Estimation (Q)
|
84% |
13775
16.3 IPS |
|
|
Object Detection (SP)
|
98% |
1749
139.2 IPS |
|
|
Object Detection (HP)
|
98% |
1738
138.3 IPS |
|
|
Object Detection (Q)
|
83% |
3969
320.6 IPS |
|
|
Face Detection (SP)
|
100% |
4452
52.9 IPS |
|
|
Face Detection (HP)
|
100% |
4310
51.2 IPS |
|
|
Face Detection (Q)
|
95% |
10007
119.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
4671
36.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
4620
35.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
10693
97.9 IPS |
|
|
Style Transfer (SP)
|
89% |
11671
15.2 IPS |
|
|
Style Transfer (HP)
|
89% |
11625
15.1 IPS |
|
|
Style Transfer (Q)
|
98% |
24980
32.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2417
89.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2360
87.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6666
247.0 IPS |
|
|
Text Classification (SP)
|
100% |
985
1.31 KIPS |
|
|
Text Classification (HP)
|
99% |
986
1.32 KIPS |
|
|
Text Classification (Q)
|
88% |
1071
1.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
1399
24.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1371
23.6 IPS |
|
|
Machine Translation (Q)
|
50% |
563
20.0 IPS |
