Samsung Galaxy A71
Geekbench ML Score
260
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 27 2024 06:00 AM |
| Views | 2 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
187
34.9 IPS |
|
|
Image Classification (F16)
|
99% |
269
50.4 IPS |
|
|
Image Classification (I8)
|
97% |
543
101.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
208
3.47 IPS |
|
|
Image Segmentation (F16)
|
100% |
251
4.19 IPS |
|
|
Image Segmentation (I8)
|
98% |
670
11.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
459
0.56 IPS |
|
|
Pose Estimation (F16)
|
100% |
1071
1.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
3896
4.72 IPS |
|
|
Object Detection (F32)
|
100% |
139
10.4 IPS |
|
|
Object Detection (F16)
|
100% |
174
13.0 IPS |
|
|
Object Detection (I8)
|
59% |
297
22.2 IPS |
|
|
Face Detection (F32)
|
100% |
411
4.89 IPS |
|
|
Face Detection (F16)
|
97% |
497
5.91 IPS |
|
|
Face Detection (I8)
|
88% |
1412
16.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
264
2.05 IPS |
|
|
Depth Estimation (F16)
|
100% |
315
2.44 IPS |
|
|
Depth Estimation (I8)
|
82% |
2862
22.2 IPS |
|
|
Style Transfer (F32)
|
100% |
413
0.54 IPS |
|
|
Style Transfer (F16)
|
100% |
450
0.59 IPS |
|
|
Style Transfer (I8)
|
98% |
1743
2.29 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
299
10.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
583
20.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1894
67.6 IPS |
|
|
Text Classification (F32)
|
64% |
5
7.29 IPS |
|
|
Text Classification (F16)
|
64% |
5
7.70 IPS |
|
|
Text Classification (I8)
|
92% |
40
57.9 IPS |
|
|
Machine Translation (F32)
|
100% |
155
2.85 IPS |
|
|
Machine Translation (F16)
|
100% |
202
3.72 IPS |
|
|
Machine Translation (I8)
|
0
|
