samsung SM-S936U1
Geekbench ML Score
928
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 29 2025 03:21 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% |
424
79.4 IPS |
|
|
Image Classification (F16)
|
100% |
414
77.5 IPS |
|
|
Image Classification (I8)
|
97% |
1093
204.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
536
8.96 IPS |
|
|
Image Segmentation (F16)
|
100% |
533
8.91 IPS |
|
|
Image Segmentation (I8)
|
98% |
1092
18.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
740
0.90 IPS |
|
|
Pose Estimation (F16)
|
100% |
727
0.88 IPS |
|
|
Pose Estimation (I8)
|
100% |
2964
3.59 IPS |
|
|
Object Detection (F32)
|
100% |
388
29.0 IPS |
|
|
Object Detection (F16)
|
100% |
388
29.0 IPS |
|
|
Object Detection (I8)
|
61% |
1014
75.7 IPS |
|
|
Face Detection (F32)
|
100% |
960
11.4 IPS |
|
|
Face Detection (F16)
|
100% |
1079
12.8 IPS |
|
|
Face Detection (I8)
|
86% |
2584
30.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
950
7.37 IPS |
|
|
Depth Estimation (F16)
|
100% |
941
7.30 IPS |
|
|
Depth Estimation (I8)
|
95% |
2688
20.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1586
2.09 IPS |
|
|
Style Transfer (F16)
|
100% |
1570
2.06 IPS |
|
|
Style Transfer (I8)
|
98% |
4470
5.88 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
534
19.1 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% |
533
766.2 IPS |
|
|
Text Classification (I8)
|
92% |
830
1.19 KIPS |
|
|
Machine Translation (F32)
|
100% |
925
17.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1071
19.7 IPS |
|
|
Machine Translation (I8)
|
64% |
1049
19.3 IPS |
