samsung SM-S936U1
Geekbench ML Score
913
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 29 2025 03:19 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
427
79.9 IPS |
|
|
Image Classification (F16)
|
100% |
416
77.8 IPS |
|
|
Image Classification (I8)
|
97% |
1079
201.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
538
8.98 IPS |
|
|
Image Segmentation (F16)
|
100% |
534
8.93 IPS |
|
|
Image Segmentation (I8)
|
98% |
1096
18.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
739
0.89 IPS |
|
|
Pose Estimation (F16)
|
100% |
729
0.88 IPS |
|
|
Pose Estimation (I8)
|
100% |
2965
3.59 IPS |
|
|
Object Detection (F32)
|
100% |
342
25.6 IPS |
|
|
Object Detection (F16)
|
100% |
342
25.5 IPS |
|
|
Object Detection (I8)
|
61% |
892
66.6 IPS |
|
|
Face Detection (F32)
|
100% |
851
10.1 IPS |
|
|
Face Detection (F16)
|
100% |
1086
12.9 IPS |
|
|
Face Detection (I8)
|
86% |
2577
30.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
955
7.40 IPS |
|
|
Depth Estimation (F16)
|
100% |
942
7.31 IPS |
|
|
Depth Estimation (I8)
|
95% |
2638
20.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1590
2.09 IPS |
|
|
Style Transfer (F16)
|
100% |
1573
2.07 IPS |
|
|
Style Transfer (I8)
|
98% |
4447
5.85 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
530
18.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
472
16.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1661
59.3 IPS |
|
|
Text Classification (F32)
|
100% |
534
768.0 IPS |
|
|
Text Classification (F16)
|
100% |
535
768.5 IPS |
|
|
Text Classification (I8)
|
92% |
829
1.19 KIPS |
|
|
Machine Translation (F32)
|
100% |
911
16.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1066
19.6 IPS |
|
|
Machine Translation (I8)
|
64% |
1084
20.0 IPS |
