HUAWEI MAO-LX9
Geekbench ML Score
73
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 05 2024 10:28 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | HUAWEI MAO-LX9 |
| Model ID | HUAWEI MAO-LX9 |
| Motherboard | MAO |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
153
28.7 IPS |
|
|
Image Classification (F16)
|
100% |
157
29.4 IPS |
|
|
Image Classification (I8)
|
97% |
234
43.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
211
3.53 IPS |
|
|
Image Segmentation (F16)
|
100% |
205
3.42 IPS |
|
|
Image Segmentation (I8)
|
98% |
80
1.34 IPS |
|
|
Pose Estimation (F32)
|
100% |
123
0.15 IPS |
|
|
Pose Estimation (F16)
|
100% |
122
0.15 IPS |
|
|
Pose Estimation (I8)
|
100% |
242
0.29 IPS |
|
|
Object Detection (F32)
|
100% |
35
2.62 IPS |
|
|
Object Detection (F16)
|
100% |
36
2.65 IPS |
|
|
Object Detection (I8)
|
61% |
47
3.49 IPS |
|
|
Face Detection (F32)
|
100% |
103
1.22 IPS |
|
|
Face Detection (F16)
|
100% |
103
1.23 IPS |
|
|
Face Detection (I8)
|
86% |
147
1.75 IPS |
|
|
Depth Estimation (F32)
|
100% |
97
0.75 IPS |
|
|
Depth Estimation (F16)
|
100% |
97
0.75 IPS |
|
|
Depth Estimation (I8)
|
95% |
142
1.10 IPS |
|
|
Style Transfer (F32)
|
100% |
227
0.30 IPS |
|
|
Style Transfer (F16)
|
100% |
227
0.30 IPS |
|
|
Style Transfer (I8)
|
98% |
474
0.62 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
56
2.01 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
57
2.03 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
90
3.22 IPS |
|
|
Text Classification (F32)
|
100% |
7
9.42 IPS |
|
|
Text Classification (F16)
|
100% |
7
9.40 IPS |
|
|
Text Classification (I8)
|
92% |
8
10.9 IPS |
|
|
Machine Translation (F32)
|
100% |
16
0.30 IPS |
|
|
Machine Translation (F16)
|
100% |
16
0.30 IPS |
|
|
Machine Translation (I8)
|
64% |
18
0.34 IPS |
