Samsung Galaxy A53 5G
Geekbench ML Score
223
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 31 2025 02:26 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
167
31.3 IPS |
|
|
Image Classification (F16)
|
100% |
184
34.5 IPS |
|
|
Image Classification (I8)
|
97% |
344
64.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
205
3.43 IPS |
|
|
Image Segmentation (F16)
|
100% |
212
3.54 IPS |
|
|
Image Segmentation (I8)
|
98% |
232
3.87 IPS |
|
|
Pose Estimation (F32)
|
100% |
353
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
357
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
2025
2.45 IPS |
|
|
Object Detection (F32)
|
100% |
220
16.4 IPS |
|
|
Object Detection (F16)
|
100% |
223
16.7 IPS |
|
|
Object Detection (I8)
|
61% |
135
10.1 IPS |
|
|
Face Detection (F32)
|
100% |
291
3.46 IPS |
|
|
Face Detection (F16)
|
100% |
293
3.49 IPS |
|
|
Face Detection (I8)
|
86% |
624
7.42 IPS |
|
|
Depth Estimation (F32)
|
100% |
351
2.72 IPS |
|
|
Depth Estimation (F16)
|
100% |
334
2.59 IPS |
|
|
Depth Estimation (I8)
|
95% |
339
2.63 IPS |
|
|
Style Transfer (F32)
|
100% |
618
0.81 IPS |
|
|
Style Transfer (F16)
|
100% |
620
0.82 IPS |
|
|
Style Transfer (I8)
|
98% |
1694
2.23 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
211
7.53 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
239
8.54 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
225
8.05 IPS |
|
|
Text Classification (F32)
|
100% |
35
49.8 IPS |
|
|
Text Classification (F16)
|
100% |
34
49.0 IPS |
|
|
Text Classification (I8)
|
92% |
30
42.4 IPS |
|
|
Machine Translation (F32)
|
100% |
67
1.22 IPS |
|
|
Machine Translation (F16)
|
100% |
62
1.15 IPS |
|
|
Machine Translation (I8)
|
64% |
76
1.40 IPS |
