HUAWEI MAO-LX9
Geekbench ML Score
74
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 01 2024 01:15 PM |
| Views | 2 |
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
5.92 IPS |
|
|
Image Classification (F16)
|
100% |
64
12.0 IPS |
|
|
Image Classification (I8)
|
97% |
66
12.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
29
0.49 IPS |
|
|
Image Segmentation (F16)
|
100% |
89
1.49 IPS |
|
|
Image Segmentation (I8)
|
98% |
85
1.42 IPS |
|
|
Pose Estimation (F32)
|
100% |
55
0.07 IPS |
|
|
Pose Estimation (F16)
|
100% |
110
0.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
110
0.13 IPS |
|
|
Object Detection (F32)
|
100% |
32
2.40 IPS |
|
|
Object Detection (F16)
|
100% |
52
3.88 IPS |
|
|
Object Detection (I8)
|
62% |
52
3.85 IPS |
|
|
Face Detection (F32)
|
100% |
80
0.96 IPS |
|
|
Face Detection (F16)
|
97% |
196
2.33 IPS |
|
|
Face Detection (I8)
|
87% |
205
2.43 IPS |
|
|
Depth Estimation (F32)
|
100% |
76
0.59 IPS |
|
|
Depth Estimation (F16)
|
100% |
157
1.22 IPS |
|
|
Depth Estimation (I8)
|
95% |
157
1.22 IPS |
|
|
Style Transfer (F32)
|
100% |
148
0.19 IPS |
|
|
Style Transfer (F16)
|
100% |
292
0.38 IPS |
|
|
Style Transfer (I8)
|
98% |
290
0.38 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
39
1.38 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
81
2.89 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
77
2.77 IPS |
|
|
Text Classification (F32)
|
100% |
26
37.8 IPS |
|
|
Text Classification (F16)
|
100% |
26
38.0 IPS |
|
|
Text Classification (I8)
|
92% |
38
55.3 IPS |
|
|
Machine Translation (F32)
|
100% |
51
0.93 IPS |
|
|
Machine Translation (F16)
|
100% |
52
0.95 IPS |
|
|
Machine Translation (I8)
|
64% |
57
1.04 IPS |
