samsung SM-S938B
Geekbench AI Score
2555
Single Precision Score
2562
Half Precision Score
4740
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 12 2025 10:55 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1835
341.3 IPS |
|
|
Image Classification (HP)
|
100% |
1841
342.4 IPS |
|
|
Image Classification (Q)
|
100% |
4296
799.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2175
35.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2244
36.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
5179
84.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
5048
5.89 IPS |
|
|
Pose Estimation (HP)
|
100% |
5112
5.96 IPS |
|
|
Pose Estimation (Q)
|
84% |
12213
14.5 IPS |
|
|
Object Detection (SP)
|
98% |
1548
123.2 IPS |
|
|
Object Detection (HP)
|
98% |
1551
123.4 IPS |
|
|
Object Detection (Q)
|
83% |
3399
274.6 IPS |
|
|
Face Detection (SP)
|
100% |
3770
44.8 IPS |
|
|
Face Detection (HP)
|
100% |
3883
46.1 IPS |
|
|
Face Detection (Q)
|
95% |
9106
108.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
4207
32.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
4060
31.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
10109
92.6 IPS |
|
|
Style Transfer (SP)
|
89% |
11205
14.5 IPS |
|
|
Style Transfer (HP)
|
89% |
11211
14.6 IPS |
|
|
Style Transfer (Q)
|
98% |
23199
29.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2167
80.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2143
79.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5806
215.1 IPS |
|
|
Text Classification (SP)
|
100% |
853
1.14 KIPS |
|
|
Text Classification (HP)
|
99% |
850
1.14 KIPS |
|
|
Text Classification (Q)
|
88% |
972
1.31 KIPS |
|
|
Machine Translation (SP)
|
100% |
1160
20.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1157
19.9 IPS |
|
|
Machine Translation (Q)
|
50% |
515
18.3 IPS |
