samsung SM-A556E
Geekbench ML Score
474
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 18 2024 11:22 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A556E |
| Model ID | samsung SM-A556E |
| Motherboard | s5e8845 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 2.05 GHz |
| Cluster 1 | 4 Cores @ 2.05 GHz |
| Cluster 2 | 4 Cores @ 2.75 GHz |
| Memory Information | |
|---|---|
| Size | 7.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
175
32.8 IPS |
|
|
Image Classification (F16)
|
100% |
260
48.7 IPS |
|
|
Image Classification (I8)
|
99% |
245
45.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
444
7.42 IPS |
|
|
Image Segmentation (F16)
|
100% |
600
10.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
589
9.84 IPS |
|
|
Pose Estimation (F32)
|
100% |
385
0.47 IPS |
|
|
Pose Estimation (F16)
|
100% |
484
0.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
500
0.61 IPS |
|
|
Object Detection (F32)
|
100% |
272
20.3 IPS |
|
|
Object Detection (F16)
|
100% |
354
26.5 IPS |
|
|
Object Detection (I8)
|
58% |
343
25.6 IPS |
|
|
Face Detection (F32)
|
100% |
912
10.8 IPS |
|
|
Face Detection (F16)
|
97% |
1153
13.7 IPS |
|
|
Face Detection (I8)
|
86% |
1053
12.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
681
5.28 IPS |
|
|
Depth Estimation (F16)
|
100% |
940
7.29 IPS |
|
|
Depth Estimation (I8)
|
95% |
919
7.13 IPS |
|
|
Style Transfer (F32)
|
100% |
1876
2.47 IPS |
|
|
Style Transfer (F16)
|
100% |
2093
2.75 IPS |
|
|
Style Transfer (I8)
|
98% |
2106
2.77 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
353
12.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
483
17.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
469
16.8 IPS |
|
|
Text Classification (F32)
|
100% |
119
171.4 IPS |
|
|
Text Classification (F16)
|
100% |
120
172.3 IPS |
|
|
Text Classification (I8)
|
92% |
295
424.0 IPS |
|
|
Machine Translation (F32)
|
100% |
224
4.13 IPS |
|
|
Machine Translation (F16)
|
100% |
227
4.17 IPS |
|
|
Machine Translation (I8)
|
64% |
391
7.19 IPS |
