samsung SM-S938B
Geekbench AI Score
669
Single Precision Score
679
Half Precision Score
1495
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | sipos |
| Upload Date | March 12 2025 12:16 PM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
419
77.8 IPS |
|
|
Image Classification (HP)
|
100% |
421
78.2 IPS |
|
|
Image Classification (Q)
|
99% |
1054
196.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
541
8.78 IPS |
|
|
Image Segmentation (HP)
|
100% |
542
8.78 IPS |
|
|
Image Segmentation (Q)
|
98% |
1077
17.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
720
0.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
714
0.83 IPS |
|
|
Pose Estimation (Q)
|
98% |
2622
3.07 IPS |
|
|
Object Detection (SP)
|
100% |
379
30.1 IPS |
|
|
Object Detection (HP)
|
100% |
406
32.2 IPS |
|
|
Object Detection (Q)
|
87% |
1113
89.3 IPS |
|
|
Face Detection (SP)
|
100% |
1000
11.9 IPS |
|
|
Face Detection (HP)
|
100% |
996
11.8 IPS |
|
|
Face Detection (Q)
|
97% |
2490
29.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
891
6.86 IPS |
|
|
Depth Estimation (HP)
|
99% |
851
6.55 IPS |
|
|
Depth Estimation (Q)
|
64% |
1841
16.7 IPS |
|
|
Style Transfer (SP)
|
100% |
1543
1.98 IPS |
|
|
Style Transfer (HP)
|
100% |
1406
1.81 IPS |
|
|
Style Transfer (Q)
|
98% |
3567
4.60 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
401
14.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
456
16.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1599
59.2 IPS |
|
|
Text Classification (SP)
|
100% |
576
769.3 IPS |
|
|
Text Classification (HP)
|
100% |
577
770.3 IPS |
|
|
Text Classification (Q)
|
91% |
887
1.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
922
15.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1009
17.4 IPS |
|
|
Machine Translation (Q)
|
57% |
726
17.8 IPS |
