samsung SM-S938B
Geekbench AI Score
722
Single Precision Score
703
Half Precision Score
1560
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | angelpradomx |
| Upload Date | June 01 2025 03:57 AM |
| Views | 6 |
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% |
448
83.3 IPS |
|
|
Image Classification (HP)
|
100% |
451
83.9 IPS |
|
|
Image Classification (Q)
|
99% |
1130
210.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
585
9.49 IPS |
|
|
Image Segmentation (HP)
|
100% |
584
9.47 IPS |
|
|
Image Segmentation (Q)
|
98% |
1163
18.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
780
0.91 IPS |
|
|
Pose Estimation (HP)
|
100% |
755
0.88 IPS |
|
|
Pose Estimation (Q)
|
98% |
2906
3.40 IPS |
|
|
Object Detection (SP)
|
100% |
416
33.0 IPS |
|
|
Object Detection (HP)
|
100% |
428
33.9 IPS |
|
|
Object Detection (Q)
|
87% |
1135
91.1 IPS |
|
|
Face Detection (SP)
|
100% |
1055
12.5 IPS |
|
|
Face Detection (HP)
|
100% |
1052
12.5 IPS |
|
|
Face Detection (Q)
|
97% |
2539
30.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
935
7.20 IPS |
|
|
Depth Estimation (HP)
|
99% |
854
6.58 IPS |
|
|
Depth Estimation (Q)
|
64% |
1984
18.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1593
2.05 IPS |
|
|
Style Transfer (HP)
|
100% |
1490
1.92 IPS |
|
|
Style Transfer (Q)
|
98% |
3901
5.03 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
496
18.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
441
16.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1601
59.3 IPS |
|
|
Text Classification (SP)
|
100% |
575
768.1 IPS |
|
|
Text Classification (HP)
|
100% |
577
770.2 IPS |
|
|
Text Classification (Q)
|
91% |
888
1.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
1016
17.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1026
17.7 IPS |
|
|
Machine Translation (Q)
|
57% |
708
17.3 IPS |
