Samsung Galaxy A71
Geekbench ML Score
283
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 02 2024 07:21 AM |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
193
36.0 IPS |
|
|
Image Classification (F16)
|
99% |
275
51.4 IPS |
|
|
Image Classification (I8)
|
97% |
601
112.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
218
3.65 IPS |
|
|
Image Segmentation (F16)
|
100% |
280
4.67 IPS |
|
|
Image Segmentation (I8)
|
98% |
680
11.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
454
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
1071
1.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
3900
4.72 IPS |
|
|
Object Detection (F32)
|
100% |
156
11.6 IPS |
|
|
Object Detection (F16)
|
100% |
208
15.5 IPS |
|
|
Object Detection (I8)
|
59% |
299
22.3 IPS |
|
|
Face Detection (F32)
|
100% |
422
5.02 IPS |
|
|
Face Detection (F16)
|
97% |
510
6.06 IPS |
|
|
Face Detection (I8)
|
88% |
1470
17.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
306
2.37 IPS |
|
|
Depth Estimation (F16)
|
100% |
356
2.76 IPS |
|
|
Depth Estimation (I8)
|
82% |
3106
24.1 IPS |
|
|
Style Transfer (F32)
|
100% |
500
0.66 IPS |
|
|
Style Transfer (F16)
|
100% |
541
0.71 IPS |
|
|
Style Transfer (I8)
|
98% |
1914
2.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
300
10.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
588
21.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1902
67.9 IPS |
|
|
Text Classification (F32)
|
64% |
6
8.05 IPS |
|
|
Text Classification (F16)
|
64% |
6
7.92 IPS |
|
|
Text Classification (I8)
|
92% |
44
63.7 IPS |
|
|
Machine Translation (F32)
|
100% |
207
3.81 IPS |
|
|
Machine Translation (F16)
|
100% |
261
4.81 IPS |
|
|
Machine Translation (I8)
|
0
|
