samsung SM-A556E
Geekbench ML Score
187
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 10 2024 06:55 PM |
| 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 | 11.17 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
89
16.7 IPS |
|
|
Image Classification (F16)
|
100% |
86
16.1 IPS |
|
|
Image Classification (I8)
|
97% |
271
50.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
257
4.29 IPS |
|
|
Image Segmentation (F16)
|
100% |
324
5.42 IPS |
|
|
Image Segmentation (I8)
|
98% |
330
5.51 IPS |
|
|
Pose Estimation (F32)
|
0
|
||
|
Pose Estimation (F16)
|
0
|
||
|
Pose Estimation (I8)
|
100% |
626
0.76 IPS |
|
|
Object Detection (F32)
|
100% |
95
7.09 IPS |
|
|
Object Detection (F16)
|
100% |
95
7.08 IPS |
|
|
Object Detection (I8)
|
61% |
302
22.6 IPS |
|
|
Face Detection (F32)
|
100% |
260
3.09 IPS |
|
|
Face Detection (F16)
|
100% |
261
3.11 IPS |
|
|
Face Detection (I8)
|
86% |
684
8.13 IPS |
|
|
Depth Estimation (F32)
|
100% |
203
1.58 IPS |
|
|
Depth Estimation (F16)
|
100% |
204
1.58 IPS |
|
|
Depth Estimation (I8)
|
95% |
670
5.20 IPS |
|
|
Style Transfer (F32)
|
100% |
360
0.47 IPS |
|
|
Style Transfer (F16)
|
100% |
357
0.47 IPS |
|
|
Style Transfer (I8)
|
98% |
1131
1.49 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
544
19.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
501
17.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
386
13.8 IPS |
|
|
Text Classification (F32)
|
100% |
119
170.6 IPS |
|
|
Text Classification (F16)
|
100% |
119
171.2 IPS |
|
|
Text Classification (I8)
|
92% |
296
425.0 IPS |
|
|
Machine Translation (F32)
|
100% |
223
4.10 IPS |
|
|
Machine Translation (F16)
|
100% |
225
4.13 IPS |
|
|
Machine Translation (I8)
|
64% |
385
7.08 IPS |
