samsung SM-S931B
Geekbench ML Score
1658
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 17 2025 10:24 PM |
| Views | 2 |
System Information
| 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 |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
790
147.8 IPS |
|
|
Image Classification (F16)
|
100% |
1980
370.6 IPS |
|
|
Image Classification (I8)
|
100% |
904
169.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1081
18.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1395
23.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1408
23.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1659
2.01 IPS |
|
|
Pose Estimation (F16)
|
100% |
2615
3.17 IPS |
|
|
Pose Estimation (I8)
|
100% |
2612
3.16 IPS |
|
|
Object Detection (F32)
|
100% |
378
28.2 IPS |
|
|
Object Detection (F16)
|
100% |
523
39.0 IPS |
|
|
Object Detection (I8)
|
59% |
459
34.3 IPS |
|
|
Face Detection (F32)
|
100% |
3210
38.2 IPS |
|
|
Face Detection (F16)
|
97% |
5716
68.0 IPS |
|
|
Face Detection (I8)
|
86% |
4842
57.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1682
13.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
4937
38.3 IPS |
|
|
Depth Estimation (I8)
|
94% |
4704
36.5 IPS |
|
|
Style Transfer (F32)
|
100% |
5718
7.52 IPS |
|
|
Style Transfer (F16)
|
100% |
12737
16.8 IPS |
|
|
Style Transfer (I8)
|
98% |
12690
16.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
655
23.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1152
41.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1093
39.0 IPS |
|
|
Text Classification (F32)
|
100% |
646
928.1 IPS |
|
|
Text Classification (F16)
|
100% |
660
949.0 IPS |
|
|
Text Classification (I8)
|
92% |
1045
1.50 KIPS |
|
|
Machine Translation (F32)
|
100% |
1055
19.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1024
18.8 IPS |
|
|
Machine Translation (I8)
|
64% |
989
18.2 IPS |
