samsung SM-S931N
Geekbench AI Score
2338
Single Precision Score
2304
Half Precision Score
3165
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 13 2025 10:45 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1675
311.6 IPS |
|
|
Image Classification (HP)
|
100% |
1644
305.8 IPS |
|
|
Image Classification (Q)
|
100% |
2003
372.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2050
33.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2122
34.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
1839
29.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2954
3.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
3962
4.62 IPS |
|
|
Pose Estimation (Q)
|
84% |
7458
8.85 IPS |
|
|
Object Detection (SP)
|
98% |
1419
112.9 IPS |
|
|
Object Detection (HP)
|
98% |
1387
110.4 IPS |
|
|
Object Detection (Q)
|
83% |
3157
255.0 IPS |
|
|
Face Detection (SP)
|
100% |
3766
44.7 IPS |
|
|
Face Detection (HP)
|
100% |
3991
47.4 IPS |
|
|
Face Detection (Q)
|
95% |
7308
87.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
4532
35.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
4531
35.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
8634
79.1 IPS |
|
|
Style Transfer (SP)
|
89% |
9991
13.0 IPS |
|
|
Style Transfer (HP)
|
89% |
7539
9.79 IPS |
|
|
Style Transfer (Q)
|
98% |
15558
20.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1681
62.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1608
59.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4758
176.3 IPS |
|
|
Text Classification (SP)
|
100% |
881
1.18 KIPS |
|
|
Text Classification (HP)
|
99% |
798
1.06 KIPS |
|
|
Text Classification (Q)
|
88% |
649
875.6 IPS |
|
|
Machine Translation (SP)
|
100% |
1345
23.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1260
21.7 IPS |
|
|
Machine Translation (Q)
|
50% |
384
13.6 IPS |
