samsung SM-S938B
Geekbench AI Score
2258
Single Precision Score
2803
Half Precision Score
4897
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 15 2025 03:17 AM |
| 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% |
262
48.8 IPS |
|
|
Image Classification (HP)
|
100% |
1731
322.0 IPS |
|
|
Image Classification (Q)
|
100% |
3916
728.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2171
35.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2138
34.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
4726
76.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
4041
4.72 IPS |
|
|
Pose Estimation (HP)
|
100% |
5577
6.51 IPS |
|
|
Pose Estimation (Q)
|
84% |
12882
15.3 IPS |
|
|
Object Detection (SP)
|
98% |
1740
138.5 IPS |
|
|
Object Detection (HP)
|
98% |
1758
139.9 IPS |
|
|
Object Detection (Q)
|
83% |
3451
278.8 IPS |
|
|
Face Detection (SP)
|
100% |
4545
54.0 IPS |
|
|
Face Detection (HP)
|
100% |
4602
54.7 IPS |
|
|
Face Detection (Q)
|
95% |
9610
114.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
4743
36.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
4686
36.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
10749
98.5 IPS |
|
|
Style Transfer (SP)
|
89% |
11883
15.4 IPS |
|
|
Style Transfer (HP)
|
89% |
11560
15.0 IPS |
|
|
Style Transfer (Q)
|
98% |
23267
30.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2458
90.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2456
90.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6638
246.0 IPS |
|
|
Text Classification (SP)
|
100% |
972
1.30 KIPS |
|
|
Text Classification (HP)
|
99% |
970
1.29 KIPS |
|
|
Text Classification (Q)
|
88% |
1064
1.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
1412
24.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1392
24.0 IPS |
|
|
Machine Translation (Q)
|
50% |
568
20.2 IPS |
