samsung SM-S938N
Geekbench AI Score
2770
Single Precision Score
2726
Half Precision Score
4597
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | March 28 2025 12:48 PM |
| Views | 4 |
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 | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1996
371.3 IPS |
|
|
Image Classification (HP)
|
100% |
2006
373.1 IPS |
|
|
Image Classification (Q)
|
100% |
4444
826.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2418
39.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2373
38.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
5318
86.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5527
6.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
5340
6.23 IPS |
|
|
Pose Estimation (Q)
|
84% |
13047
15.5 IPS |
|
|
Object Detection (SP)
|
98% |
1731
137.8 IPS |
|
|
Object Detection (HP)
|
98% |
1670
132.9 IPS |
|
|
Object Detection (Q)
|
83% |
3858
311.6 IPS |
|
|
Face Detection (SP)
|
100% |
4339
51.6 IPS |
|
|
Face Detection (HP)
|
100% |
4357
51.8 IPS |
|
|
Face Detection (Q)
|
95% |
9028
107.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
4579
35.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
4803
37.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
10654
97.6 IPS |
|
|
Style Transfer (SP)
|
89% |
11435
14.8 IPS |
|
|
Style Transfer (HP)
|
89% |
11573
15.0 IPS |
|
|
Style Transfer (Q)
|
98% |
24305
31.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2282
84.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1911
70.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5047
187.0 IPS |
|
|
Text Classification (SP)
|
100% |
799
1.07 KIPS |
|
|
Text Classification (HP)
|
99% |
838
1.12 KIPS |
|
|
Text Classification (Q)
|
88% |
524
706.5 IPS |
|
|
Machine Translation (SP)
|
100% |
1394
24.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1379
23.8 IPS |
|
|
Machine Translation (Q)
|
50% |
574
20.4 IPS |
