samsung SM-A556E
Geekbench ML Score
189
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 18 2024 11:17 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
91
17.0 IPS |
|
|
Image Classification (F16)
|
100% |
91
17.0 IPS |
|
|
Image Classification (I8)
|
97% |
288
53.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
253
4.22 IPS |
|
|
Image Segmentation (F16)
|
100% |
329
5.50 IPS |
|
|
Image Segmentation (I8)
|
98% |
331
5.53 IPS |
|
|
Pose Estimation (F32)
|
0
|
||
|
Pose Estimation (F16)
|
0
|
||
|
Pose Estimation (I8)
|
100% |
601
0.73 IPS |
|
|
Object Detection (F32)
|
100% |
95
7.08 IPS |
|
|
Object Detection (F16)
|
100% |
95
7.11 IPS |
|
|
Object Detection (I8)
|
61% |
309
23.1 IPS |
|
|
Face Detection (F32)
|
100% |
261
3.11 IPS |
|
|
Face Detection (F16)
|
100% |
262
3.12 IPS |
|
|
Face Detection (I8)
|
86% |
692
8.23 IPS |
|
|
Depth Estimation (F32)
|
100% |
207
1.61 IPS |
|
|
Depth Estimation (F16)
|
100% |
207
1.60 IPS |
|
|
Depth Estimation (I8)
|
95% |
682
5.29 IPS |
|
|
Style Transfer (F32)
|
100% |
366
0.48 IPS |
|
|
Style Transfer (F16)
|
100% |
368
0.48 IPS |
|
|
Style Transfer (I8)
|
98% |
1138
1.50 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
558
19.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
515
18.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
391
14.0 IPS |
|
|
Text Classification (F32)
|
100% |
119
171.2 IPS |
|
|
Text Classification (F16)
|
100% |
119
171.5 IPS |
|
|
Text Classification (I8)
|
92% |
295
424.0 IPS |
|
|
Machine Translation (F32)
|
100% |
226
4.16 IPS |
|
|
Machine Translation (F16)
|
100% |
225
4.15 IPS |
|
|
Machine Translation (I8)
|
64% |
388
7.14 IPS |
