Samsung Galaxy A71
Geekbench ML Score
394
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 07 2024 05:14 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy A71 |
| Model ID | samsung SM-A715F |
| Motherboard | sm6150 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 13 part 2052 revision 14 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 7.34 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
198
37.1 IPS |
|
|
Image Classification (F16)
|
100% |
214
40.0 IPS |
|
|
Image Classification (I8)
|
97% |
440
82.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
264
4.41 IPS |
|
|
Image Segmentation (F16)
|
100% |
268
4.47 IPS |
|
|
Image Segmentation (I8)
|
98% |
355
5.93 IPS |
|
|
Pose Estimation (F32)
|
100% |
382
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
385
0.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
1892
2.29 IPS |
|
|
Object Detection (F32)
|
100% |
220
16.4 IPS |
|
|
Object Detection (F16)
|
100% |
211
15.8 IPS |
|
|
Object Detection (I8)
|
61% |
530
39.6 IPS |
|
|
Face Detection (F32)
|
100% |
413
4.91 IPS |
|
|
Face Detection (F16)
|
100% |
413
4.91 IPS |
|
|
Face Detection (I8)
|
86% |
915
10.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
410
3.18 IPS |
|
|
Depth Estimation (F16)
|
100% |
409
3.17 IPS |
|
|
Depth Estimation (I8)
|
95% |
997
7.74 IPS |
|
|
Style Transfer (F32)
|
100% |
619
0.81 IPS |
|
|
Style Transfer (F16)
|
100% |
620
0.82 IPS |
|
|
Style Transfer (I8)
|
98% |
1663
2.19 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
204
7.29 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
210
7.50 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
739
26.4 IPS |
|
|
Text Classification (F32)
|
100% |
246
353.4 IPS |
|
|
Text Classification (F16)
|
100% |
232
332.8 IPS |
|
|
Text Classification (I8)
|
92% |
197
282.8 IPS |
|
|
Machine Translation (F32)
|
100% |
454
8.36 IPS |
|
|
Machine Translation (F16)
|
100% |
471
8.67 IPS |
|
|
Machine Translation (I8)
|
64% |
185
3.40 IPS |
