Samsung Galaxy A53 5G
Geekbench ML Score
260
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 01 2025 01:07 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy A53 5G |
| Model ID | samsung SM-A536B |
| Motherboard | s5e8825 |
| 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 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
112
20.9 IPS |
|
|
Image Classification (F16)
|
100% |
110
20.5 IPS |
|
|
Image Classification (I8)
|
97% |
301
56.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
193
3.23 IPS |
|
|
Image Segmentation (F16)
|
100% |
266
4.44 IPS |
|
|
Image Segmentation (I8)
|
98% |
342
5.72 IPS |
|
|
Pose Estimation (F32)
|
100% |
665
0.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
2318
2.81 IPS |
|
|
Pose Estimation (I8)
|
100% |
744
0.90 IPS |
|
|
Object Detection (F32)
|
100% |
113
8.46 IPS |
|
|
Object Detection (F16)
|
100% |
109
8.12 IPS |
|
|
Object Detection (I8)
|
61% |
330
24.6 IPS |
|
|
Face Detection (F32)
|
100% |
270
3.21 IPS |
|
|
Face Detection (F16)
|
100% |
268
3.19 IPS |
|
|
Face Detection (I8)
|
86% |
649
7.72 IPS |
|
|
Depth Estimation (F32)
|
100% |
228
1.77 IPS |
|
|
Depth Estimation (F16)
|
100% |
225
1.74 IPS |
|
|
Depth Estimation (I8)
|
95% |
714
5.54 IPS |
|
|
Style Transfer (F32)
|
100% |
461
0.61 IPS |
|
|
Style Transfer (F16)
|
100% |
465
0.61 IPS |
|
|
Style Transfer (I8)
|
98% |
365
0.48 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
266
9.51 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
379
13.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
450
16.1 IPS |
|
|
Text Classification (F32)
|
100% |
41
59.6 IPS |
|
|
Text Classification (F16)
|
100% |
49
69.8 IPS |
|
|
Text Classification (I8)
|
92% |
33
47.9 IPS |
|
|
Machine Translation (F32)
|
100% |
269
4.94 IPS |
|
|
Machine Translation (F16)
|
100% |
262
4.82 IPS |
|
|
Machine Translation (I8)
|
64% |
360
6.63 IPS |
