Samsung Galaxy A53 5G
Geekbench ML Score
175
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 18 2024 08:49 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy A53 5G |
| Model ID | samsung SM-A536E |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
26
4.93 IPS |
|
|
Image Classification (F16)
|
100% |
41
7.74 IPS |
|
|
Image Classification (I8)
|
97% |
85
15.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
145
2.42 IPS |
|
|
Image Segmentation (F16)
|
100% |
154
2.57 IPS |
|
|
Image Segmentation (I8)
|
98% |
276
4.61 IPS |
|
|
Pose Estimation (F32)
|
100% |
351
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
356
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1902
2.30 IPS |
|
|
Object Detection (F32)
|
100% |
71
5.29 IPS |
|
|
Object Detection (F16)
|
100% |
76
5.66 IPS |
|
|
Object Detection (I8)
|
61% |
162
12.1 IPS |
|
|
Face Detection (F32)
|
100% |
200
2.38 IPS |
|
|
Face Detection (F16)
|
100% |
192
2.28 IPS |
|
|
Face Detection (I8)
|
86% |
355
4.22 IPS |
|
|
Depth Estimation (F32)
|
100% |
234
1.81 IPS |
|
|
Depth Estimation (F16)
|
100% |
229
1.78 IPS |
|
|
Depth Estimation (I8)
|
95% |
487
3.78 IPS |
|
|
Style Transfer (F32)
|
100% |
637
0.84 IPS |
|
|
Style Transfer (F16)
|
100% |
633
0.83 IPS |
|
|
Style Transfer (I8)
|
98% |
1417
1.86 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
112
3.99 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
112
3.99 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
479
17.1 IPS |
|
|
Text Classification (F32)
|
100% |
60
86.3 IPS |
|
|
Text Classification (F16)
|
100% |
54
77.7 IPS |
|
|
Text Classification (I8)
|
92% |
46
66.0 IPS |
|
|
Machine Translation (F32)
|
100% |
104
1.92 IPS |
|
|
Machine Translation (F16)
|
100% |
108
1.99 IPS |
|
|
Machine Translation (I8)
|
64% |
93
1.71 IPS |
