samsung SM-S926N
Geekbench ML Score
1723
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 02:13 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S926N |
| Model ID | samsung SM-S926N |
| Motherboard | s5e9945 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.59 GHz |
| Cluster 3 | 2 Cores @ 2.90 GHz |
| Cluster 4 | 1 Core @ 3.21 GHz |
| Memory Information | |
|---|---|
| Size | 10.95 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
589
110.3 IPS |
|
|
Image Classification (F16)
|
100% |
804
150.4 IPS |
|
|
Image Classification (I8)
|
99% |
727
136.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1590
26.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
2033
34.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1997
33.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
3461
4.19 IPS |
|
|
Pose Estimation (F16)
|
100% |
4049
4.90 IPS |
|
|
Pose Estimation (I8)
|
100% |
4016
4.86 IPS |
|
|
Object Detection (F32)
|
100% |
693
51.7 IPS |
|
|
Object Detection (F16)
|
100% |
679
50.7 IPS |
|
|
Object Detection (I8)
|
58% |
418
31.2 IPS |
|
|
Face Detection (F32)
|
100% |
2800
33.3 IPS |
|
|
Face Detection (F16)
|
97% |
3590
42.7 IPS |
|
|
Face Detection (I8)
|
86% |
3219
38.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
3314
25.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
3756
29.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
3667
28.4 IPS |
|
|
Style Transfer (F32)
|
100% |
9229
12.1 IPS |
|
|
Style Transfer (F16)
|
100% |
13166
17.3 IPS |
|
|
Style Transfer (I8)
|
98% |
12996
17.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1777
63.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2223
79.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2219
79.2 IPS |
|
|
Text Classification (F32)
|
100% |
388
557.6 IPS |
|
|
Text Classification (F16)
|
100% |
395
568.1 IPS |
|
|
Text Classification (I8)
|
92% |
659
946.9 IPS |
|
|
Machine Translation (F32)
|
100% |
597
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
584
10.8 IPS |
|
|
Machine Translation (I8)
|
64% |
697
12.8 IPS |
