samsung SM-S938N
Geekbench AI Score
2894
Single Precision Score
2911
Half Precision Score
5169
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | July 15 2025 12:32 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938N |
| Model ID | samsung SM-S938N |
| 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 | 14.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1927
358.3 IPS |
|
|
Image Classification (HP)
|
100% |
2005
373.0 IPS |
|
|
Image Classification (Q)
|
100% |
4675
869.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2530
41.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2502
40.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
5370
87.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
5742
6.70 IPS |
|
|
Pose Estimation (HP)
|
100% |
5526
6.45 IPS |
|
|
Pose Estimation (Q)
|
84% |
13933
16.5 IPS |
|
|
Object Detection (SP)
|
98% |
1664
132.4 IPS |
|
|
Object Detection (HP)
|
98% |
1754
139.6 IPS |
|
|
Object Detection (Q)
|
83% |
3938
318.1 IPS |
|
|
Face Detection (SP)
|
100% |
4591
54.5 IPS |
|
|
Face Detection (HP)
|
100% |
4556
54.1 IPS |
|
|
Face Detection (Q)
|
95% |
9999
119.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
4887
37.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
4954
38.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
11152
102.1 IPS |
|
|
Style Transfer (SP)
|
89% |
12256
15.9 IPS |
|
|
Style Transfer (HP)
|
89% |
12050
15.6 IPS |
|
|
Style Transfer (Q)
|
98% |
26401
34.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2484
91.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2437
90.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6649
246.4 IPS |
|
|
Text Classification (SP)
|
100% |
936
1.25 KIPS |
|
|
Text Classification (HP)
|
99% |
968
1.29 KIPS |
|
|
Text Classification (Q)
|
88% |
969
1.31 KIPS |
|
|
Machine Translation (SP)
|
100% |
1388
23.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1402
24.1 IPS |
|
|
Machine Translation (Q)
|
50% |
522
18.5 IPS |
