samsung SM-S931N
Geekbench AI Score
2805
Single Precision Score
2805
Half Precision Score
4820
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 18 2025 12:30 PM |
| Views | 1 |
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% |
2110
392.4 IPS |
|
|
Image Classification (HP)
|
100% |
2068
384.5 IPS |
|
|
Image Classification (Q)
|
100% |
4371
812.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2557
41.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2511
40.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
5368
87.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
5642
6.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
5546
6.47 IPS |
|
|
Pose Estimation (Q)
|
84% |
13416
15.9 IPS |
|
|
Object Detection (SP)
|
98% |
1807
143.8 IPS |
|
|
Object Detection (HP)
|
98% |
1757
139.8 IPS |
|
|
Object Detection (Q)
|
83% |
4014
324.2 IPS |
|
|
Face Detection (SP)
|
100% |
4519
53.7 IPS |
|
|
Face Detection (HP)
|
100% |
4306
51.2 IPS |
|
|
Face Detection (Q)
|
95% |
9538
113.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
4877
37.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
4811
37.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
10938
100.2 IPS |
|
|
Style Transfer (SP)
|
89% |
11678
15.2 IPS |
|
|
Style Transfer (HP)
|
89% |
11635
15.1 IPS |
|
|
Style Transfer (Q)
|
98% |
23602
30.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2267
83.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1959
72.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5240
194.2 IPS |
|
|
Text Classification (SP)
|
100% |
669
892.8 IPS |
|
|
Text Classification (HP)
|
99% |
922
1.23 KIPS |
|
|
Text Classification (Q)
|
88% |
1031
1.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
1407
24.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1372
23.6 IPS |
|
|
Machine Translation (Q)
|
50% |
403
14.3 IPS |
