samsung SM-S938B
Geekbench AI Score
448
Single Precision Score
432
Half Precision Score
945
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | wolfcam |
| Upload Date | February 24 2025 02:47 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% |
415
77.1 IPS |
|
|
Image Classification (HP)
|
100% |
412
76.5 IPS |
|
|
Image Classification (Q)
|
99% |
1039
193.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
532
8.63 IPS |
|
|
Image Segmentation (HP)
|
100% |
379
6.14 IPS |
|
|
Image Segmentation (Q)
|
98% |
721
11.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
382
0.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
371
0.43 IPS |
|
|
Pose Estimation (Q)
|
98% |
1823
2.13 IPS |
|
|
Object Detection (SP)
|
100% |
264
21.0 IPS |
|
|
Object Detection (HP)
|
100% |
241
19.1 IPS |
|
|
Object Detection (Q)
|
87% |
626
50.2 IPS |
|
|
Face Detection (SP)
|
100% |
560
6.66 IPS |
|
|
Face Detection (HP)
|
100% |
560
6.66 IPS |
|
|
Face Detection (Q)
|
97% |
1418
16.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
538
4.14 IPS |
|
|
Depth Estimation (HP)
|
99% |
489
3.76 IPS |
|
|
Depth Estimation (Q)
|
64% |
897
8.14 IPS |
|
|
Style Transfer (SP)
|
100% |
847
1.09 IPS |
|
|
Style Transfer (HP)
|
100% |
773
0.99 IPS |
|
|
Style Transfer (Q)
|
98% |
1979
2.55 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
245
9.04 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
311
11.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1106
41.0 IPS |
|
|
Text Classification (SP)
|
100% |
384
513.0 IPS |
|
|
Text Classification (HP)
|
100% |
369
492.0 IPS |
|
|
Text Classification (Q)
|
91% |
567
762.6 IPS |
|
|
Machine Translation (SP)
|
100% |
614
10.6 IPS |
|
|
Machine Translation (HP)
|
100% |
677
11.7 IPS |
|
|
Machine Translation (Q)
|
57% |
422
10.3 IPS |
