samsung SM-S938B
Geekbench AI Score
2936
Single Precision Score
2772
Half Precision Score
4926
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Quiltermatt |
| Upload Date | February 04 2025 09:15 PM |
| Views | 7 |
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% |
2212
411.4 IPS |
|
|
Image Classification (HP)
|
100% |
2156
400.9 IPS |
|
|
Image Classification (Q)
|
100% |
4603
856.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2606
42.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2543
41.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
5504
89.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5837
6.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
5497
6.41 IPS |
|
|
Pose Estimation (Q)
|
84% |
14101
16.7 IPS |
|
|
Object Detection (SP)
|
98% |
1747
139.0 IPS |
|
|
Object Detection (HP)
|
98% |
1817
144.5 IPS |
|
|
Object Detection (Q)
|
83% |
4230
341.7 IPS |
|
|
Face Detection (SP)
|
100% |
4521
53.7 IPS |
|
|
Face Detection (HP)
|
100% |
4585
54.5 IPS |
|
|
Face Detection (Q)
|
95% |
9971
119.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
4876
37.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
4692
36.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
10928
100.1 IPS |
|
|
Style Transfer (SP)
|
89% |
12042
15.6 IPS |
|
|
Style Transfer (HP)
|
89% |
12200
15.8 IPS |
|
|
Style Transfer (Q)
|
98% |
26423
34.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2405
88.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2311
85.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4741
175.7 IPS |
|
|
Text Classification (SP)
|
100% |
906
1.21 KIPS |
|
|
Text Classification (HP)
|
99% |
579
772.3 IPS |
|
|
Text Classification (Q)
|
88% |
707
952.9 IPS |
|
|
Machine Translation (SP)
|
100% |
1400
24.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1397
24.1 IPS |
|
|
Machine Translation (Q)
|
50% |
578
20.5 IPS |
