samsung SM-S938B
Geekbench AI Score
1334
Single Precision Score
2342
Half Precision Score
2079
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Swanne |
| Upload Date | February 11 2025 06:36 PM |
| Views | 26 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
729
135.7 IPS |
|
|
Image Classification (HP)
|
100% |
1049
195.2 IPS |
|
|
Image Classification (Q)
|
99% |
797
148.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1524
24.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
3236
52.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
1892
30.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1708
1.99 IPS |
|
|
Pose Estimation (HP)
|
100% |
2971
3.47 IPS |
|
|
Pose Estimation (Q)
|
96% |
2962
3.47 IPS |
|
|
Object Detection (SP)
|
100% |
574
45.6 IPS |
|
|
Object Detection (HP)
|
100% |
1172
93.0 IPS |
|
|
Object Detection (Q)
|
86% |
1056
84.8 IPS |
|
|
Face Detection (SP)
|
100% |
3209
38.1 IPS |
|
|
Face Detection (HP)
|
100% |
4026
47.8 IPS |
|
|
Face Detection (Q)
|
97% |
3665
43.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
1688
13.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
4935
38.1 IPS |
|
|
Depth Estimation (Q)
|
63% |
4054
37.7 IPS |
|
|
Style Transfer (SP)
|
100% |
6278
8.07 IPS |
|
|
Style Transfer (HP)
|
100% |
13431
17.3 IPS |
|
|
Style Transfer (Q)
|
98% |
13366
17.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
682
25.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2264
83.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2227
82.5 IPS |
|
|
Text Classification (SP)
|
100% |
681
909.2 IPS |
|
|
Text Classification (HP)
|
100% |
677
904.0 IPS |
|
|
Text Classification (Q)
|
91% |
1076
1.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
1041
17.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1030
17.7 IPS |
|
|
Machine Translation (Q)
|
57% |
675
16.5 IPS |
