samsung SM-A525M
Geekbench ML Score
274
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 03:47 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A525M |
| Model ID | samsung SM-A525M |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
155
29.0 IPS |
|
|
Image Classification (F16)
|
99% |
220
41.2 IPS |
|
|
Image Classification (I8)
|
97% |
502
94.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
188
3.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
263
4.40 IPS |
|
|
Image Segmentation (I8)
|
98% |
554
9.25 IPS |
|
|
Pose Estimation (F32)
|
100% |
466
0.56 IPS |
|
|
Pose Estimation (F16)
|
100% |
1071
1.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
3542
4.29 IPS |
|
|
Object Detection (F32)
|
100% |
175
13.1 IPS |
|
|
Object Detection (F16)
|
100% |
245
18.3 IPS |
|
|
Object Detection (I8)
|
59% |
511
38.1 IPS |
|
|
Face Detection (F32)
|
100% |
360
4.28 IPS |
|
|
Face Detection (F16)
|
97% |
435
5.17 IPS |
|
|
Face Detection (I8)
|
88% |
1385
16.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
297
2.30 IPS |
|
|
Depth Estimation (F16)
|
100% |
353
2.74 IPS |
|
|
Depth Estimation (I8)
|
82% |
2799
21.7 IPS |
|
|
Style Transfer (F32)
|
100% |
475
0.63 IPS |
|
|
Style Transfer (F16)
|
100% |
509
0.67 IPS |
|
|
Style Transfer (I8)
|
98% |
1914
2.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
304
10.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
600
21.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1841
65.7 IPS |
|
|
Text Classification (F32)
|
64% |
6
8.26 IPS |
|
|
Text Classification (F16)
|
64% |
6
8.39 IPS |
|
|
Text Classification (I8)
|
92% |
61
88.3 IPS |
|
|
Machine Translation (F32)
|
100% |
164
3.03 IPS |
|
|
Machine Translation (F16)
|
100% |
224
4.12 IPS |
|
|
Machine Translation (I8)
|
0
|
