HUAWEI MAO-LX9
Geekbench ML Score
83
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 04 2024 10:13 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
32
5.91 IPS |
|
|
Image Classification (F16)
|
100% |
64
12.0 IPS |
|
|
Image Classification (I8)
|
97% |
65
12.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
30
0.50 IPS |
|
|
Image Segmentation (F16)
|
100% |
102
1.71 IPS |
|
|
Image Segmentation (I8)
|
98% |
100
1.67 IPS |
|
|
Pose Estimation (F32)
|
100% |
54
0.07 IPS |
|
|
Pose Estimation (F16)
|
100% |
110
0.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
110
0.13 IPS |
|
|
Object Detection (F32)
|
100% |
32
2.39 IPS |
|
|
Object Detection (F16)
|
100% |
52
3.88 IPS |
|
|
Object Detection (I8)
|
62% |
52
3.85 IPS |
|
|
Face Detection (F32)
|
100% |
80
0.95 IPS |
|
|
Face Detection (F16)
|
97% |
195
2.32 IPS |
|
|
Face Detection (I8)
|
87% |
203
2.42 IPS |
|
|
Depth Estimation (F32)
|
100% |
76
0.59 IPS |
|
|
Depth Estimation (F16)
|
100% |
157
1.21 IPS |
|
|
Depth Estimation (I8)
|
95% |
157
1.22 IPS |
|
|
Style Transfer (F32)
|
100% |
146
0.19 IPS |
|
|
Style Transfer (F16)
|
100% |
289
0.38 IPS |
|
|
Style Transfer (I8)
|
98% |
287
0.38 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
37
1.33 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
76
2.70 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
76
2.70 IPS |
|
|
Text Classification (F32)
|
100% |
66
95.1 IPS |
|
|
Text Classification (F16)
|
100% |
66
95.1 IPS |
|
|
Text Classification (I8)
|
92% |
86
123.4 IPS |
|
|
Machine Translation (F32)
|
100% |
126
2.31 IPS |
|
|
Machine Translation (F16)
|
100% |
51
0.95 IPS |
|
|
Machine Translation (I8)
|
64% |
58
1.06 IPS |
