Samsung Galaxy A52S 5G
Geekbench ML Score
218
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 02 2024 09:43 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 | 5.25 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
93
17.3 IPS |
|
|
Image Classification (F16)
|
100% |
93
17.4 IPS |
|
|
Image Classification (I8)
|
97% |
279
52.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
124
2.07 IPS |
|
|
Image Segmentation (F16)
|
100% |
121
2.02 IPS |
|
|
Image Segmentation (I8)
|
98% |
268
4.47 IPS |
|
|
Pose Estimation (F32)
|
100% |
165
0.20 IPS |
|
|
Pose Estimation (F16)
|
100% |
165
0.20 IPS |
|
|
Pose Estimation (I8)
|
100% |
611
0.74 IPS |
|
|
Object Detection (F32)
|
100% |
96
7.16 IPS |
|
|
Object Detection (F16)
|
100% |
95
7.11 IPS |
|
|
Object Detection (I8)
|
61% |
270
20.2 IPS |
|
|
Face Detection (F32)
|
100% |
245
2.91 IPS |
|
|
Face Detection (F16)
|
100% |
245
2.91 IPS |
|
|
Face Detection (I8)
|
86% |
560
6.65 IPS |
|
|
Depth Estimation (F32)
|
100% |
211
1.63 IPS |
|
|
Depth Estimation (F16)
|
100% |
209
1.62 IPS |
|
|
Depth Estimation (I8)
|
95% |
595
4.62 IPS |
|
|
Style Transfer (F32)
|
100% |
362
0.48 IPS |
|
|
Style Transfer (F16)
|
100% |
365
0.48 IPS |
|
|
Style Transfer (I8)
|
98% |
959
1.26 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
113
4.05 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
109
3.89 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
379
13.5 IPS |
|
|
Text Classification (F32)
|
100% |
133
190.6 IPS |
|
|
Text Classification (F16)
|
100% |
132
189.8 IPS |
|
|
Text Classification (I8)
|
92% |
260
373.1 IPS |
|
|
Machine Translation (F32)
|
100% |
232
4.26 IPS |
|
|
Machine Translation (F16)
|
100% |
231
4.26 IPS |
|
|
Machine Translation (I8)
|
64% |
292
5.37 IPS |
