samsung SM-S937N
Geekbench AI Score
2572
Single Precision Score
2364
Half Precision Score
4254
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 21 2025 04:59 AM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-S937N |
| Model ID | samsung SM-S937N |
| 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 | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1869
347.6 IPS |
|
|
Image Classification (HP)
|
100% |
1835
341.3 IPS |
|
|
Image Classification (Q)
|
100% |
4173
776.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2115
34.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2118
34.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
4973
80.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
5251
6.13 IPS |
|
|
Pose Estimation (HP)
|
100% |
5108
5.96 IPS |
|
|
Pose Estimation (Q)
|
84% |
13801
16.4 IPS |
|
|
Object Detection (SP)
|
98% |
1421
113.1 IPS |
|
|
Object Detection (HP)
|
98% |
1425
113.4 IPS |
|
|
Object Detection (Q)
|
83% |
3198
258.3 IPS |
|
|
Face Detection (SP)
|
100% |
3945
46.9 IPS |
|
|
Face Detection (HP)
|
100% |
4308
51.2 IPS |
|
|
Face Detection (Q)
|
95% |
8760
104.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
4448
34.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
3404
26.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
6848
62.7 IPS |
|
|
Style Transfer (SP)
|
89% |
11374
14.8 IPS |
|
|
Style Transfer (HP)
|
89% |
8459
11.0 IPS |
|
|
Style Transfer (Q)
|
98% |
18305
23.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2009
74.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1959
72.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4363
161.7 IPS |
|
|
Text Classification (SP)
|
100% |
799
1.07 KIPS |
|
|
Text Classification (HP)
|
99% |
800
1.07 KIPS |
|
|
Text Classification (Q)
|
88% |
1021
1.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
1342
23.1 IPS |
|
|
Machine Translation (HP)
|
100% |
992
17.1 IPS |
|
|
Machine Translation (Q)
|
50% |
434
15.4 IPS |
