samsung SM-S938B
Geekbench AI Score
2871
Single Precision Score
2895
Half Precision Score
5237
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 22 2025 10:01 AM |
| Views | 4 |
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% |
1988
369.8 IPS |
|
|
Image Classification (HP)
|
100% |
2087
388.2 IPS |
|
|
Image Classification (Q)
|
100% |
4674
869.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2506
40.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2524
40.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
5476
89.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
5639
6.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
5544
6.47 IPS |
|
|
Pose Estimation (Q)
|
84% |
13830
16.4 IPS |
|
|
Object Detection (SP)
|
98% |
1708
135.9 IPS |
|
|
Object Detection (HP)
|
98% |
1729
137.6 IPS |
|
|
Object Detection (Q)
|
83% |
4013
324.1 IPS |
|
|
Face Detection (SP)
|
100% |
4506
53.5 IPS |
|
|
Face Detection (HP)
|
100% |
4400
52.3 IPS |
|
|
Face Detection (Q)
|
95% |
9887
118.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
4673
36.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
4698
36.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
10810
99.0 IPS |
|
|
Style Transfer (SP)
|
89% |
11636
15.1 IPS |
|
|
Style Transfer (HP)
|
89% |
11570
15.0 IPS |
|
|
Style Transfer (Q)
|
98% |
25415
32.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2399
88.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2523
93.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6492
240.6 IPS |
|
|
Text Classification (SP)
|
100% |
992
1.32 KIPS |
|
|
Text Classification (HP)
|
99% |
987
1.32 KIPS |
|
|
Text Classification (Q)
|
88% |
1072
1.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
1360
23.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1377
23.7 IPS |
|
|
Machine Translation (Q)
|
50% |
578
20.5 IPS |
