Samsung Galaxy A52
Geekbench ML Score
363
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 27 2024 07:17 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy A52 |
| Model ID | samsung SM-A525F |
| Motherboard | atoll |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 15 part 2052 revision 15 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.32 GHz |
| Memory Information | |
|---|---|
| Size | 5.37 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
180
33.7 IPS |
|
|
Image Classification (F16)
|
100% |
178
33.4 IPS |
|
|
Image Classification (I8)
|
97% |
415
77.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
255
4.27 IPS |
|
|
Image Segmentation (F16)
|
100% |
252
4.21 IPS |
|
|
Image Segmentation (I8)
|
98% |
348
5.81 IPS |
|
|
Pose Estimation (F32)
|
100% |
339
0.41 IPS |
|
|
Pose Estimation (F16)
|
100% |
339
0.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1759
2.13 IPS |
|
|
Object Detection (F32)
|
100% |
201
15.0 IPS |
|
|
Object Detection (F16)
|
100% |
195
14.6 IPS |
|
|
Object Detection (I8)
|
61% |
518
38.7 IPS |
|
|
Face Detection (F32)
|
100% |
391
4.65 IPS |
|
|
Face Detection (F16)
|
100% |
390
4.64 IPS |
|
|
Face Detection (I8)
|
86% |
733
8.71 IPS |
|
|
Depth Estimation (F32)
|
100% |
333
2.58 IPS |
|
|
Depth Estimation (F16)
|
100% |
321
2.49 IPS |
|
|
Depth Estimation (I8)
|
95% |
846
6.56 IPS |
|
|
Style Transfer (F32)
|
100% |
476
0.63 IPS |
|
|
Style Transfer (F16)
|
100% |
572
0.75 IPS |
|
|
Style Transfer (I8)
|
98% |
1861
2.45 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
196
7.02 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
196
6.99 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
787
28.1 IPS |
|
|
Text Classification (F32)
|
100% |
224
322.3 IPS |
|
|
Text Classification (F16)
|
100% |
222
318.8 IPS |
|
|
Text Classification (I8)
|
92% |
206
296.7 IPS |
|
|
Machine Translation (F32)
|
100% |
402
7.41 IPS |
|
|
Machine Translation (F16)
|
100% |
428
7.87 IPS |
|
|
Machine Translation (I8)
|
64% |
204
3.76 IPS |
