samsung SM-S931B
Geekbench AI Score
2853
Single Precision Score
2881
Half Precision Score
5148
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 19 2025 10:30 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S931B |
| Model ID | samsung SM-S931B |
| 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% |
1954
363.3 IPS |
|
|
Image Classification (HP)
|
100% |
2097
390.0 IPS |
|
|
Image Classification (Q)
|
100% |
4606
856.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2534
41.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2561
41.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
5317
86.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5785
6.75 IPS |
|
|
Pose Estimation (HP)
|
100% |
5593
6.53 IPS |
|
|
Pose Estimation (Q)
|
84% |
14014
16.6 IPS |
|
|
Object Detection (SP)
|
98% |
1760
140.1 IPS |
|
|
Object Detection (HP)
|
98% |
1821
144.9 IPS |
|
|
Object Detection (Q)
|
83% |
4116
332.5 IPS |
|
|
Face Detection (SP)
|
100% |
4548
54.0 IPS |
|
|
Face Detection (HP)
|
100% |
4577
54.4 IPS |
|
|
Face Detection (Q)
|
95% |
10205
121.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
4855
37.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
4833
37.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
10685
97.9 IPS |
|
|
Style Transfer (SP)
|
89% |
12295
16.0 IPS |
|
|
Style Transfer (HP)
|
89% |
11754
15.3 IPS |
|
|
Style Transfer (Q)
|
98% |
24961
32.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1915
70.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2063
76.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6328
234.5 IPS |
|
|
Text Classification (SP)
|
100% |
949
1.27 KIPS |
|
|
Text Classification (HP)
|
99% |
967
1.29 KIPS |
|
|
Text Classification (Q)
|
88% |
1095
1.48 KIPS |
|
|
Machine Translation (SP)
|
100% |
1437
24.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1393
24.0 IPS |
|
|
Machine Translation (Q)
|
50% |
491
17.4 IPS |
