samsung SM-A556E
Geekbench ML Score
188
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 16 2025 10:48 PM |
| Views | 4 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
90
16.9 IPS |
|
|
Image Classification (F16)
|
100% |
89
16.6 IPS |
|
|
Image Classification (I8)
|
97% |
286
53.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
253
4.22 IPS |
|
|
Image Segmentation (F16)
|
100% |
318
5.31 IPS |
|
|
Image Segmentation (I8)
|
98% |
329
5.50 IPS |
|
|
Pose Estimation (F32)
|
0
|
||
|
Pose Estimation (F16)
|
0
|
||
|
Pose Estimation (I8)
|
100% |
612
0.74 IPS |
|
|
Object Detection (F32)
|
100% |
93
6.95 IPS |
|
|
Object Detection (F16)
|
100% |
95
7.10 IPS |
|
|
Object Detection (I8)
|
61% |
312
23.3 IPS |
|
|
Face Detection (F32)
|
100% |
261
3.10 IPS |
|
|
Face Detection (F16)
|
100% |
262
3.11 IPS |
|
|
Face Detection (I8)
|
86% |
682
8.10 IPS |
|
|
Depth Estimation (F32)
|
100% |
204
1.58 IPS |
|
|
Depth Estimation (F16)
|
100% |
203
1.57 IPS |
|
|
Depth Estimation (I8)
|
95% |
668
5.18 IPS |
|
|
Style Transfer (F32)
|
100% |
361
0.48 IPS |
|
|
Style Transfer (F16)
|
100% |
358
0.47 IPS |
|
|
Style Transfer (I8)
|
98% |
1127
1.48 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
576
20.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
509
18.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
387
13.8 IPS |
|
|
Text Classification (F32)
|
100% |
118
169.5 IPS |
|
|
Text Classification (F16)
|
100% |
119
171.5 IPS |
|
|
Text Classification (I8)
|
92% |
290
416.3 IPS |
|
|
Machine Translation (F32)
|
100% |
226
4.16 IPS |
|
|
Machine Translation (F16)
|
100% |
226
4.16 IPS |
|
|
Machine Translation (I8)
|
64% |
389
7.16 IPS |
