samsung SM-S938B
Geekbench AI Score
2550
Single Precision Score
2824
Half Precision Score
4269
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 07 2025 10:14 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% |
1848
343.6 IPS |
|
|
Image Classification (HP)
|
100% |
1891
351.7 IPS |
|
|
Image Classification (Q)
|
100% |
2999
557.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2146
34.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2266
36.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
1170
19.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
3045
3.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
5419
6.32 IPS |
|
|
Pose Estimation (Q)
|
84% |
14080
16.7 IPS |
|
|
Object Detection (SP)
|
98% |
1720
136.9 IPS |
|
|
Object Detection (HP)
|
98% |
1717
136.7 IPS |
|
|
Object Detection (Q)
|
83% |
3983
321.7 IPS |
|
|
Face Detection (SP)
|
100% |
3106
36.9 IPS |
|
|
Face Detection (HP)
|
100% |
4457
53.0 IPS |
|
|
Face Detection (Q)
|
95% |
9431
112.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
4588
35.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
4695
36.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
10814
99.0 IPS |
|
|
Style Transfer (SP)
|
89% |
12026
15.6 IPS |
|
|
Style Transfer (HP)
|
89% |
12028
15.6 IPS |
|
|
Style Transfer (Q)
|
98% |
25843
33.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2398
88.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2403
88.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6739
249.7 IPS |
|
|
Text Classification (SP)
|
100% |
977
1.30 KIPS |
|
|
Text Classification (HP)
|
99% |
978
1.31 KIPS |
|
|
Text Classification (Q)
|
88% |
1035
1.40 KIPS |
|
|
Machine Translation (SP)
|
100% |
1396
24.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1371
23.6 IPS |
|
|
Machine Translation (Q)
|
50% |
556
19.8 IPS |
