samsung SM-S931N
Geekbench AI Score
2962
Single Precision Score
2961
Half Precision Score
5257
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 24 2025 07:09 PM |
| Views | 3 |
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% |
2142
398.4 IPS |
|
|
Image Classification (HP)
|
100% |
2147
399.3 IPS |
|
|
Image Classification (Q)
|
100% |
4681
870.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2570
41.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2502
40.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
5403
87.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
5727
6.68 IPS |
|
|
Pose Estimation (HP)
|
100% |
5537
6.46 IPS |
|
|
Pose Estimation (Q)
|
84% |
13235
15.7 IPS |
|
|
Object Detection (SP)
|
98% |
1799
143.2 IPS |
|
|
Object Detection (HP)
|
98% |
1820
144.9 IPS |
|
|
Object Detection (Q)
|
83% |
4002
323.3 IPS |
|
|
Face Detection (SP)
|
100% |
4522
53.7 IPS |
|
|
Face Detection (HP)
|
100% |
4649
55.2 IPS |
|
|
Face Detection (Q)
|
95% |
10014
119.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
4799
37.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
4812
37.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
11091
101.6 IPS |
|
|
Style Transfer (SP)
|
89% |
12220
15.9 IPS |
|
|
Style Transfer (HP)
|
89% |
11766
15.3 IPS |
|
|
Style Transfer (Q)
|
98% |
25680
33.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2469
91.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2569
94.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6921
256.4 IPS |
|
|
Text Classification (SP)
|
100% |
989
1.32 KIPS |
|
|
Text Classification (HP)
|
99% |
1008
1.35 KIPS |
|
|
Text Classification (Q)
|
88% |
1055
1.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
1417
24.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1406
24.2 IPS |
|
|
Machine Translation (Q)
|
50% |
578
20.5 IPS |
