Samsung Galaxy A52S 5G
Geekbench ML Score
559
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 04 2024 07:34 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
267
50.0 IPS |
|
|
Image Classification (F16)
|
100% |
264
49.5 IPS |
|
|
Image Classification (I8)
|
97% |
652
122.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
360
6.02 IPS |
|
|
Image Segmentation (F16)
|
100% |
354
5.91 IPS |
|
|
Image Segmentation (I8)
|
98% |
514
8.58 IPS |
|
|
Pose Estimation (F32)
|
100% |
522
0.63 IPS |
|
|
Pose Estimation (F16)
|
100% |
511
0.62 IPS |
|
|
Pose Estimation (I8)
|
100% |
2639
3.20 IPS |
|
|
Object Detection (F32)
|
100% |
291
21.7 IPS |
|
|
Object Detection (F16)
|
100% |
284
21.2 IPS |
|
|
Object Detection (I8)
|
61% |
746
55.7 IPS |
|
|
Face Detection (F32)
|
100% |
510
6.07 IPS |
|
|
Face Detection (F16)
|
100% |
525
6.24 IPS |
|
|
Face Detection (I8)
|
86% |
1464
17.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
536
4.16 IPS |
|
|
Depth Estimation (F16)
|
100% |
538
4.17 IPS |
|
|
Depth Estimation (I8)
|
95% |
1401
10.9 IPS |
|
|
Style Transfer (F32)
|
100% |
929
1.22 IPS |
|
|
Style Transfer (F16)
|
100% |
920
1.21 IPS |
|
|
Style Transfer (I8)
|
98% |
2510
3.30 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
359
12.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
356
12.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1149
41.0 IPS |
|
|
Text Classification (F32)
|
100% |
341
489.6 IPS |
|
|
Text Classification (F16)
|
100% |
347
498.3 IPS |
|
|
Text Classification (I8)
|
92% |
306
439.7 IPS |
|
|
Machine Translation (F32)
|
100% |
622
11.4 IPS |
|
|
Machine Translation (F16)
|
100% |
626
11.5 IPS |
|
|
Machine Translation (I8)
|
64% |
292
5.38 IPS |
