samsung SM-S931N
Geekbench AI Score
1232
Single Precision Score
2043
Half Precision Score
2045
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 13 2025 10:42 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S931N |
| Model ID | samsung SM-S931N |
| 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% |
718
133.6 IPS |
|
|
Image Classification (HP)
|
100% |
1223
227.4 IPS |
|
|
Image Classification (Q)
|
99% |
1436
267.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1558
25.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1733
28.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
2028
33.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1575
1.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
2502
2.92 IPS |
|
|
Pose Estimation (Q)
|
96% |
2500
2.93 IPS |
|
|
Object Detection (SP)
|
100% |
499
39.6 IPS |
|
|
Object Detection (HP)
|
100% |
1175
93.2 IPS |
|
|
Object Detection (Q)
|
86% |
1156
92.9 IPS |
|
|
Face Detection (SP)
|
100% |
2774
33.0 IPS |
|
|
Face Detection (HP)
|
100% |
3580
42.5 IPS |
|
|
Face Detection (Q)
|
97% |
3754
44.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1512
11.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
4162
32.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
3443
32.0 IPS |
|
|
Style Transfer (SP)
|
100% |
5162
6.64 IPS |
|
|
Style Transfer (HP)
|
100% |
10930
14.1 IPS |
|
|
Style Transfer (Q)
|
98% |
11055
14.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
632
23.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1892
69.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1652
61.2 IPS |
|
|
Text Classification (SP)
|
100% |
662
883.5 IPS |
|
|
Text Classification (HP)
|
100% |
662
884.0 IPS |
|
|
Text Classification (Q)
|
91% |
1036
1.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
1012
17.4 IPS |
|
|
Machine Translation (HP)
|
100% |
997
17.2 IPS |
|
|
Machine Translation (Q)
|
57% |
624
15.3 IPS |
