samsung SM-S938B
Geekbench AI Score
2783
Single Precision Score
2877
Half Precision Score
5025
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | angelpradomx |
| Upload Date | June 01 2025 03:18 AM |
| Views | 4 |
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% |
1571
292.2 IPS |
|
|
Image Classification (HP)
|
100% |
2043
379.9 IPS |
|
|
Image Classification (Q)
|
100% |
3809
708.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2354
38.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2492
40.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
5262
85.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
5583
6.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
5461
6.37 IPS |
|
|
Pose Estimation (Q)
|
84% |
13457
16.0 IPS |
|
|
Object Detection (SP)
|
98% |
1756
139.8 IPS |
|
|
Object Detection (HP)
|
98% |
1738
138.3 IPS |
|
|
Object Detection (Q)
|
83% |
4095
330.8 IPS |
|
|
Face Detection (SP)
|
100% |
4415
52.5 IPS |
|
|
Face Detection (HP)
|
100% |
4592
54.6 IPS |
|
|
Face Detection (Q)
|
95% |
9604
114.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
4667
36.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
4697
36.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
10424
95.5 IPS |
|
|
Style Transfer (SP)
|
89% |
11467
14.9 IPS |
|
|
Style Transfer (HP)
|
89% |
11686
15.2 IPS |
|
|
Style Transfer (Q)
|
98% |
24108
31.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2453
90.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2425
89.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6744
249.9 IPS |
|
|
Text Classification (SP)
|
100% |
988
1.32 KIPS |
|
|
Text Classification (HP)
|
99% |
976
1.30 KIPS |
|
|
Text Classification (Q)
|
88% |
1048
1.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
1346
23.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1350
23.2 IPS |
|
|
Machine Translation (Q)
|
50% |
545
19.3 IPS |
