samsung SM-A356E
Geekbench ML Score
411
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 21 2024 07:47 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A356E |
| Model ID | samsung SM-A356E |
| Motherboard | s5e8835 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
238
44.4 IPS |
|
|
Image Classification (F16)
|
100% |
227
42.5 IPS |
|
|
Image Classification (I8)
|
97% |
132
24.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
236
3.93 IPS |
|
|
Image Segmentation (F16)
|
100% |
263
4.40 IPS |
|
|
Image Segmentation (I8)
|
98% |
333
5.57 IPS |
|
|
Pose Estimation (F32)
|
100% |
449
0.54 IPS |
|
|
Pose Estimation (F16)
|
100% |
449
0.54 IPS |
|
|
Pose Estimation (I8)
|
100% |
2453
2.97 IPS |
|
|
Object Detection (F32)
|
100% |
276
20.6 IPS |
|
|
Object Detection (F16)
|
100% |
270
20.2 IPS |
|
|
Object Detection (I8)
|
61% |
723
54.0 IPS |
|
|
Face Detection (F32)
|
100% |
334
3.98 IPS |
|
|
Face Detection (F16)
|
100% |
336
4.00 IPS |
|
|
Face Detection (I8)
|
86% |
528
6.27 IPS |
|
|
Depth Estimation (F32)
|
100% |
428
3.32 IPS |
|
|
Depth Estimation (F16)
|
100% |
448
3.47 IPS |
|
|
Depth Estimation (I8)
|
95% |
912
7.07 IPS |
|
|
Style Transfer (F32)
|
100% |
858
1.13 IPS |
|
|
Style Transfer (F16)
|
100% |
840
1.11 IPS |
|
|
Style Transfer (I8)
|
98% |
2197
2.89 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
380
13.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
323
11.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
958
34.2 IPS |
|
|
Text Classification (F32)
|
100% |
348
499.8 IPS |
|
|
Text Classification (F16)
|
100% |
343
493.5 IPS |
|
|
Text Classification (I8)
|
92% |
296
424.8 IPS |
|
|
Machine Translation (F32)
|
100% |
328
6.04 IPS |
|
|
Machine Translation (F16)
|
100% |
276
5.08 IPS |
|
|
Machine Translation (I8)
|
64% |
114
2.11 IPS |
