samsung SM-S938B
Geekbench AI Score
710
Single Precision Score
715
Half Precision Score
1614
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 06 2025 01:23 AM |
| Views | 1 |
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% |
433
80.5 IPS |
|
|
Image Classification (HP)
|
100% |
413
76.9 IPS |
|
|
Image Classification (Q)
|
99% |
1063
198.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
545
8.83 IPS |
|
|
Image Segmentation (HP)
|
100% |
548
8.89 IPS |
|
|
Image Segmentation (Q)
|
98% |
1107
18.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
727
0.85 IPS |
|
|
Pose Estimation (HP)
|
100% |
723
0.84 IPS |
|
|
Pose Estimation (Q)
|
98% |
2879
3.37 IPS |
|
|
Object Detection (SP)
|
100% |
407
32.3 IPS |
|
|
Object Detection (HP)
|
100% |
412
32.6 IPS |
|
|
Object Detection (Q)
|
87% |
1112
89.2 IPS |
|
|
Face Detection (SP)
|
100% |
1017
12.1 IPS |
|
|
Face Detection (HP)
|
100% |
1014
12.1 IPS |
|
|
Face Detection (Q)
|
97% |
2543
30.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
910
7.01 IPS |
|
|
Depth Estimation (HP)
|
99% |
909
7.00 IPS |
|
|
Depth Estimation (Q)
|
64% |
2138
19.4 IPS |
|
|
Style Transfer (SP)
|
100% |
1549
1.99 IPS |
|
|
Style Transfer (HP)
|
100% |
1560
2.00 IPS |
|
|
Style Transfer (Q)
|
98% |
4059
5.23 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
457
16.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
507
18.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1806
66.9 IPS |
|
|
Text Classification (SP)
|
100% |
679
906.0 IPS |
|
|
Text Classification (HP)
|
100% |
688
918.5 IPS |
|
|
Text Classification (Q)
|
91% |
1090
1.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
1053
18.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1045
18.0 IPS |
|
|
Machine Translation (Q)
|
57% |
735
18.0 IPS |
