samsung SM-S936U1
Geekbench ML Score
1568
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 29 2025 03:14 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S936U1 |
| Model ID | samsung SM-S936U1 |
| 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% |
712
133.2 IPS |
|
|
Image Classification (F16)
|
100% |
663
124.1 IPS |
|
|
Image Classification (I8)
|
100% |
951
177.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
948
15.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1140
19.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1108
18.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1669
2.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
2895
3.51 IPS |
|
|
Pose Estimation (I8)
|
100% |
2920
3.54 IPS |
|
|
Object Detection (F32)
|
100% |
388
29.0 IPS |
|
|
Object Detection (F16)
|
100% |
457
34.1 IPS |
|
|
Object Detection (I8)
|
59% |
509
38.0 IPS |
|
|
Face Detection (F32)
|
100% |
3154
37.5 IPS |
|
|
Face Detection (F16)
|
97% |
4037
48.0 IPS |
|
|
Face Detection (I8)
|
86% |
4054
48.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1694
13.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
4948
38.4 IPS |
|
|
Depth Estimation (I8)
|
94% |
4910
38.1 IPS |
|
|
Style Transfer (F32)
|
100% |
6202
8.16 IPS |
|
|
Style Transfer (F16)
|
100% |
12924
17.0 IPS |
|
|
Style Transfer (I8)
|
98% |
12929
17.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
683
24.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1136
40.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1073
38.3 IPS |
|
|
Text Classification (F32)
|
100% |
660
949.0 IPS |
|
|
Text Classification (F16)
|
100% |
660
948.4 IPS |
|
|
Text Classification (I8)
|
92% |
1053
1.51 KIPS |
|
|
Machine Translation (F32)
|
100% |
1093
20.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1072
19.7 IPS |
|
|
Machine Translation (I8)
|
64% |
1076
19.8 IPS |
