HUAWEI MAO-LX9
Geekbench ML Score
42
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 01 2024 01:51 PM |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
20
3.73 IPS |
|
|
Image Classification (F16)
|
100% |
20
3.72 IPS |
|
|
Image Classification (I8)
|
97% |
36
6.72 IPS |
|
|
Image Segmentation (F32)
|
100% |
26
0.44 IPS |
|
|
Image Segmentation (F16)
|
100% |
26
0.44 IPS |
|
|
Image Segmentation (I8)
|
98% |
39
0.66 IPS |
|
|
Pose Estimation (F32)
|
100% |
40
0.05 IPS |
|
|
Pose Estimation (F16)
|
100% |
40
0.05 IPS |
|
|
Pose Estimation (I8)
|
100% |
70
0.09 IPS |
|
|
Object Detection (F32)
|
100% |
22
1.62 IPS |
|
|
Object Detection (F16)
|
100% |
22
1.61 IPS |
|
|
Object Detection (I8)
|
61% |
38
2.85 IPS |
|
|
Face Detection (F32)
|
100% |
50
0.60 IPS |
|
|
Face Detection (F16)
|
100% |
50
0.60 IPS |
|
|
Face Detection (I8)
|
86% |
90
1.08 IPS |
|
|
Depth Estimation (F32)
|
100% |
48
0.37 IPS |
|
|
Depth Estimation (F16)
|
100% |
48
0.37 IPS |
|
|
Depth Estimation (I8)
|
95% |
85
0.66 IPS |
|
|
Style Transfer (F32)
|
100% |
87
0.12 IPS |
|
|
Style Transfer (F16)
|
100% |
87
0.11 IPS |
|
|
Style Transfer (I8)
|
98% |
165
0.22 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
26
0.92 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
26
0.92 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
46
1.65 IPS |
|
|
Text Classification (F32)
|
100% |
26
38.0 IPS |
|
|
Text Classification (F16)
|
100% |
27
38.4 IPS |
|
|
Text Classification (I8)
|
92% |
39
55.3 IPS |
|
|
Machine Translation (F32)
|
100% |
51
0.94 IPS |
|
|
Machine Translation (F16)
|
100% |
51
0.95 IPS |
|
|
Machine Translation (I8)
|
64% |
58
1.06 IPS |
