HUAWEI ADY-AL10
Geekbench ML Score
708
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 26 2025 08:03 AM |
| Views | 23 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | HUAWEI ADY-AL10 |
| Model ID | HUAWEI ADY-AL10 |
| Motherboard | ADY |
| CPU Information | |
|---|---|
| Name | vendor |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 72 architecture 8 variant 2 part 3331 revision 0 |
| Base Frequency | 1.55 GHz |
| Cluster 1 | 4 Cores @ 1.55 GHz |
| Cluster 2 | 3 Cores @ 2.18 GHz |
| Cluster 3 | 1 Core @ 2.19 GHz |
| Memory Information | |
|---|---|
| Size | 11.31 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
368
68.8 IPS |
|
|
Image Classification (F16)
|
100% |
379
71.0 IPS |
|
|
Image Classification (I8)
|
97% |
641
119.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
455
7.60 IPS |
|
|
Image Segmentation (F16)
|
100% |
451
7.54 IPS |
|
|
Image Segmentation (I8)
|
98% |
602
10.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
601
0.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
662
0.80 IPS |
|
|
Pose Estimation (I8)
|
100% |
2420
2.93 IPS |
|
|
Object Detection (F32)
|
100% |
398
29.7 IPS |
|
|
Object Detection (F16)
|
100% |
380
28.4 IPS |
|
|
Object Detection (I8)
|
61% |
756
56.5 IPS |
|
|
Face Detection (F32)
|
100% |
877
10.4 IPS |
|
|
Face Detection (F16)
|
100% |
831
9.88 IPS |
|
|
Face Detection (I8)
|
86% |
1506
17.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
770
5.97 IPS |
|
|
Depth Estimation (F16)
|
100% |
760
5.90 IPS |
|
|
Depth Estimation (I8)
|
95% |
1585
12.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1248
1.64 IPS |
|
|
Style Transfer (F16)
|
100% |
1227
1.61 IPS |
|
|
Style Transfer (I8)
|
98% |
3000
3.95 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
411
14.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
442
15.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1411
50.4 IPS |
|
|
Text Classification (F32)
|
100% |
500
718.6 IPS |
|
|
Text Classification (F16)
|
100% |
521
748.8 IPS |
|
|
Text Classification (I8)
|
92% |
356
512.0 IPS |
|
|
Machine Translation (F32)
|
100% |
790
14.5 IPS |
|
|
Machine Translation (F16)
|
100% |
731
13.4 IPS |
|
|
Machine Translation (I8)
|
64% |
419
7.71 IPS |
