Samsung Galaxy A52S 5G
Geekbench ML Score
308
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 04 2024 07:51 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy A52S 5G |
| Model ID | samsung SM-A528B |
| Motherboard | lahaina |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.19 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
167
31.3 IPS |
|
|
Image Classification (F16)
|
100% |
213
39.8 IPS |
|
|
Image Classification (I8)
|
97% |
205
38.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
277
4.63 IPS |
|
|
Image Segmentation (F16)
|
100% |
336
5.61 IPS |
|
|
Image Segmentation (I8)
|
98% |
332
5.55 IPS |
|
|
Pose Estimation (F32)
|
100% |
255
0.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
179
0.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
179
0.22 IPS |
|
|
Object Detection (F32)
|
100% |
135
10.1 IPS |
|
|
Object Detection (F16)
|
100% |
160
11.9 IPS |
|
|
Object Detection (I8)
|
62% |
156
11.7 IPS |
|
|
Face Detection (F32)
|
100% |
571
6.79 IPS |
|
|
Face Detection (F16)
|
97% |
816
9.70 IPS |
|
|
Face Detection (I8)
|
87% |
773
9.19 IPS |
|
|
Depth Estimation (F32)
|
100% |
406
3.15 IPS |
|
|
Depth Estimation (F16)
|
100% |
598
4.64 IPS |
|
|
Depth Estimation (I8)
|
95% |
594
4.61 IPS |
|
|
Style Transfer (F32)
|
100% |
785
1.03 IPS |
|
|
Style Transfer (F16)
|
100% |
1356
1.78 IPS |
|
|
Style Transfer (I8)
|
98% |
1333
1.75 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
178
6.36 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
305
10.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
322
11.5 IPS |
|
|
Text Classification (F32)
|
100% |
126
180.9 IPS |
|
|
Text Classification (F16)
|
100% |
126
181.6 IPS |
|
|
Text Classification (I8)
|
92% |
237
340.0 IPS |
|
|
Machine Translation (F32)
|
100% |
235
4.32 IPS |
|
|
Machine Translation (F16)
|
100% |
231
4.25 IPS |
|
|
Machine Translation (I8)
|
64% |
296
5.45 IPS |
