samsung SM-S938B
Geekbench AI Score
478
Single Precision Score
459
Half Precision Score
969
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | mohanadsinan |
| Upload Date | February 06 2025 10:54 PM |
| Views | 2 |
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% |
424
78.8 IPS |
|
|
Image Classification (HP)
|
100% |
426
79.2 IPS |
|
|
Image Classification (Q)
|
99% |
864
161.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
463
7.50 IPS |
|
|
Image Segmentation (HP)
|
100% |
378
6.12 IPS |
|
|
Image Segmentation (Q)
|
98% |
727
11.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
461
0.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
426
0.50 IPS |
|
|
Pose Estimation (Q)
|
98% |
1690
1.98 IPS |
|
|
Object Detection (SP)
|
100% |
240
19.0 IPS |
|
|
Object Detection (HP)
|
100% |
240
19.0 IPS |
|
|
Object Detection (Q)
|
87% |
628
50.4 IPS |
|
|
Face Detection (SP)
|
100% |
691
8.21 IPS |
|
|
Face Detection (HP)
|
100% |
693
8.24 IPS |
|
|
Face Detection (Q)
|
97% |
1563
18.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
589
4.54 IPS |
|
|
Depth Estimation (HP)
|
99% |
494
3.81 IPS |
|
|
Depth Estimation (Q)
|
64% |
1058
9.60 IPS |
|
|
Style Transfer (SP)
|
100% |
1006
1.29 IPS |
|
|
Style Transfer (HP)
|
100% |
902
1.16 IPS |
|
|
Style Transfer (Q)
|
98% |
2278
2.94 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
246
9.08 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
313
11.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1104
40.9 IPS |
|
|
Text Classification (SP)
|
100% |
399
533.0 IPS |
|
|
Text Classification (HP)
|
100% |
400
533.5 IPS |
|
|
Text Classification (Q)
|
91% |
615
827.3 IPS |
|
|
Machine Translation (SP)
|
100% |
721
12.4 IPS |
|
|
Machine Translation (HP)
|
100% |
656
11.3 IPS |
|
|
Machine Translation (Q)
|
57% |
431
10.5 IPS |
