Samsung Galaxy A52
Geekbench ML Score
235
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 27 2024 07:10 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
102
19.1 IPS |
|
|
Image Classification (F16)
|
100% |
165
30.8 IPS |
|
|
Image Classification (I8)
|
97% |
171
32.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
121
2.03 IPS |
|
|
Image Segmentation (F16)
|
100% |
209
3.50 IPS |
|
|
Image Segmentation (I8)
|
98% |
209
3.49 IPS |
|
|
Pose Estimation (F32)
|
100% |
191
0.23 IPS |
|
|
Pose Estimation (F16)
|
100% |
259
0.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
262
0.32 IPS |
|
|
Object Detection (F32)
|
100% |
93
6.92 IPS |
|
|
Object Detection (F16)
|
100% |
133
9.95 IPS |
|
|
Object Detection (I8)
|
62% |
138
10.3 IPS |
|
|
Face Detection (F32)
|
100% |
240
2.85 IPS |
|
|
Face Detection (F16)
|
97% |
444
5.28 IPS |
|
|
Face Detection (I8)
|
87% |
459
5.46 IPS |
|
|
Depth Estimation (F32)
|
100% |
239
1.85 IPS |
|
|
Depth Estimation (F16)
|
100% |
407
3.16 IPS |
|
|
Depth Estimation (I8)
|
95% |
410
3.18 IPS |
|
|
Style Transfer (F32)
|
100% |
464
0.61 IPS |
|
|
Style Transfer (F16)
|
100% |
975
1.28 IPS |
|
|
Style Transfer (I8)
|
98% |
971
1.28 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
119
4.23 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
192
6.86 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
191
6.83 IPS |
|
|
Text Classification (F32)
|
100% |
147
210.6 IPS |
|
|
Text Classification (F16)
|
100% |
147
210.7 IPS |
|
|
Text Classification (I8)
|
92% |
250
360.0 IPS |
|
|
Machine Translation (F32)
|
100% |
262
4.83 IPS |
|
|
Machine Translation (F16)
|
100% |
266
4.89 IPS |
|
|
Machine Translation (I8)
|
64% |
291
5.36 IPS |
