samsung SM-A546B
Geekbench ML Score
411
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 04:25 PM |
| Views | 1 |
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% |
116
21.8 IPS |
|
|
Image Classification (F16)
|
100% |
226
42.3 IPS |
|
|
Image Classification (I8)
|
97% |
98
18.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
261
4.36 IPS |
|
|
Image Segmentation (F16)
|
100% |
254
4.23 IPS |
|
|
Image Segmentation (I8)
|
98% |
338
5.65 IPS |
|
|
Pose Estimation (F32)
|
100% |
481
0.58 IPS |
|
|
Pose Estimation (F16)
|
100% |
470
0.57 IPS |
|
|
Pose Estimation (I8)
|
100% |
2446
2.96 IPS |
|
|
Object Detection (F32)
|
100% |
272
20.3 IPS |
|
|
Object Detection (F16)
|
100% |
254
19.0 IPS |
|
|
Object Detection (I8)
|
61% |
857
64.0 IPS |
|
|
Face Detection (F32)
|
100% |
337
4.00 IPS |
|
|
Face Detection (F16)
|
100% |
336
4.00 IPS |
|
|
Face Detection (I8)
|
86% |
595
7.07 IPS |
|
|
Depth Estimation (F32)
|
100% |
437
3.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
388
3.01 IPS |
|
|
Depth Estimation (I8)
|
95% |
1090
8.45 IPS |
|
|
Style Transfer (F32)
|
100% |
866
1.14 IPS |
|
|
Style Transfer (F16)
|
100% |
858
1.13 IPS |
|
|
Style Transfer (I8)
|
98% |
2223
2.92 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
317
11.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
304
10.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
675
24.1 IPS |
|
|
Text Classification (F32)
|
100% |
407
585.4 IPS |
|
|
Text Classification (F16)
|
100% |
353
506.6 IPS |
|
|
Text Classification (I8)
|
92% |
465
667.7 IPS |
|
|
Machine Translation (F32)
|
100% |
450
8.28 IPS |
|
|
Machine Translation (F16)
|
100% |
371
6.82 IPS |
|
|
Machine Translation (I8)
|
64% |
93
1.71 IPS |
