samsung SM-A546B
Geekbench ML Score
435
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 15 2024 04:52 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A546B |
| Model ID | samsung SM-A546B |
| 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% |
148
27.6 IPS |
|
|
Image Classification (F16)
|
100% |
186
34.8 IPS |
|
|
Image Classification (I8)
|
97% |
139
26.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
282
4.70 IPS |
|
|
Image Segmentation (F16)
|
100% |
261
4.37 IPS |
|
|
Image Segmentation (I8)
|
98% |
385
6.44 IPS |
|
|
Pose Estimation (F32)
|
100% |
454
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
456
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
2674
3.24 IPS |
|
|
Object Detection (F32)
|
100% |
250
18.6 IPS |
|
|
Object Detection (F16)
|
100% |
240
17.9 IPS |
|
|
Object Detection (I8)
|
61% |
686
51.2 IPS |
|
|
Face Detection (F32)
|
100% |
408
4.85 IPS |
|
|
Face Detection (F16)
|
100% |
394
4.69 IPS |
|
|
Face Detection (I8)
|
86% |
1086
12.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
396
3.07 IPS |
|
|
Depth Estimation (F16)
|
100% |
404
3.13 IPS |
|
|
Depth Estimation (I8)
|
95% |
1166
9.04 IPS |
|
|
Style Transfer (F32)
|
100% |
834
1.10 IPS |
|
|
Style Transfer (F16)
|
100% |
831
1.09 IPS |
|
|
Style Transfer (I8)
|
98% |
1968
2.59 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
338
12.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
315
11.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1152
41.2 IPS |
|
|
Text Classification (F32)
|
100% |
322
462.4 IPS |
|
|
Text Classification (F16)
|
100% |
295
424.3 IPS |
|
|
Text Classification (I8)
|
92% |
273
392.2 IPS |
|
|
Machine Translation (F32)
|
100% |
425
7.83 IPS |
|
|
Machine Translation (F16)
|
100% |
420
7.73 IPS |
|
|
Machine Translation (I8)
|
64% |
233
4.29 IPS |
