HUAWEI ALN-AL10
Geekbench ML Score
525
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 20 2024 01:46 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | HUAWEI ALN-AL10 |
| Model ID | HUAWEI ALN-AL10 |
| Motherboard | ALN |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 72 architecture 8 variant 2 part 3330 revision 2 |
| Base Frequency | 1.53 GHz |
| Cluster 1 | 4 Cores @ 1.53 GHz |
| Cluster 2 | 3 Cores @ 2.15 GHz |
| Cluster 3 | 1 Core @ 2.62 GHz |
| Memory Information | |
|---|---|
| Size | 15.24 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
238
44.5 IPS |
|
|
Image Classification (F16)
|
100% |
240
44.9 IPS |
|
|
Image Classification (I8)
|
97% |
609
114.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
301
5.02 IPS |
|
|
Image Segmentation (F16)
|
100% |
300
5.01 IPS |
|
|
Image Segmentation (I8)
|
98% |
578
9.65 IPS |
|
|
Pose Estimation (F32)
|
100% |
416
0.50 IPS |
|
|
Pose Estimation (F16)
|
100% |
410
0.50 IPS |
|
|
Pose Estimation (I8)
|
100% |
1647
1.99 IPS |
|
|
Object Detection (F32)
|
100% |
247
18.4 IPS |
|
|
Object Detection (F16)
|
100% |
247
18.5 IPS |
|
|
Object Detection (I8)
|
61% |
700
52.3 IPS |
|
|
Face Detection (F32)
|
100% |
556
6.61 IPS |
|
|
Face Detection (F16)
|
100% |
555
6.60 IPS |
|
|
Face Detection (I8)
|
86% |
1260
15.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
500
3.87 IPS |
|
|
Depth Estimation (F16)
|
100% |
501
3.88 IPS |
|
|
Depth Estimation (I8)
|
95% |
1410
10.9 IPS |
|
|
Style Transfer (F32)
|
100% |
863
1.13 IPS |
|
|
Style Transfer (F16)
|
100% |
857
1.13 IPS |
|
|
Style Transfer (I8)
|
98% |
2167
2.85 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
273
9.76 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
266
9.51 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1030
36.8 IPS |
|
|
Text Classification (F32)
|
100% |
350
503.4 IPS |
|
|
Text Classification (F16)
|
100% |
351
504.5 IPS |
|
|
Text Classification (I8)
|
92% |
491
705.7 IPS |
|
|
Machine Translation (F32)
|
100% |
589
10.8 IPS |
|
|
Machine Translation (F16)
|
100% |
570
10.5 IPS |
|
|
Machine Translation (I8)
|
64% |
561
10.3 IPS |
