Samsung Galaxy A53 5G
Geekbench ML Score
300
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 31 2025 02:45 PM |
| Views | 1 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
164
30.7 IPS |
|
|
Image Classification (F16)
|
100% |
296
55.4 IPS |
|
|
Image Classification (I8)
|
97% |
288
53.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
228
3.81 IPS |
|
|
Image Segmentation (F16)
|
100% |
377
6.29 IPS |
|
|
Image Segmentation (I8)
|
98% |
369
6.16 IPS |
|
|
Pose Estimation (F32)
|
100% |
148
0.18 IPS |
|
|
Pose Estimation (F16)
|
100% |
174
0.21 IPS |
|
|
Pose Estimation (I8)
|
100% |
173
0.21 IPS |
|
|
Object Detection (F32)
|
100% |
147
10.9 IPS |
|
|
Object Detection (F16)
|
100% |
243
18.1 IPS |
|
|
Object Detection (I8)
|
62% |
219
16.4 IPS |
|
|
Face Detection (F32)
|
100% |
551
6.55 IPS |
|
|
Face Detection (F16)
|
98% |
817
9.71 IPS |
|
|
Face Detection (I8)
|
86% |
763
9.07 IPS |
|
|
Depth Estimation (F32)
|
100% |
294
2.28 IPS |
|
|
Depth Estimation (F16)
|
100% |
379
2.94 IPS |
|
|
Depth Estimation (I8)
|
95% |
377
2.93 IPS |
|
|
Style Transfer (F32)
|
100% |
583
0.77 IPS |
|
|
Style Transfer (F16)
|
100% |
822
1.08 IPS |
|
|
Style Transfer (I8)
|
98% |
822
1.08 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
165
5.88 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
254
9.08 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
251
8.98 IPS |
|
|
Text Classification (F32)
|
100% |
156
223.6 IPS |
|
|
Text Classification (F16)
|
100% |
155
223.1 IPS |
|
|
Text Classification (I8)
|
92% |
312
448.5 IPS |
|
|
Machine Translation (F32)
|
100% |
286
5.26 IPS |
|
|
Machine Translation (F16)
|
100% |
283
5.21 IPS |
|
|
Machine Translation (I8)
|
64% |
367
6.75 IPS |
