HUAWEI ADY-AL10
Geekbench ML Score
293
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 26 2025 07:57 AM |
| Views | 14 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
181
33.9 IPS |
|
|
Image Classification (F16)
|
100% |
188
35.2 IPS |
|
|
Image Classification (I8)
|
97% |
451
84.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
227
3.79 IPS |
|
|
Image Segmentation (F16)
|
100% |
157
2.62 IPS |
|
|
Image Segmentation (I8)
|
98% |
329
5.49 IPS |
|
|
Pose Estimation (F32)
|
100% |
206
0.25 IPS |
|
|
Pose Estimation (F16)
|
100% |
205
0.25 IPS |
|
|
Pose Estimation (I8)
|
100% |
763
0.92 IPS |
|
|
Object Detection (F32)
|
100% |
125
9.34 IPS |
|
|
Object Detection (F16)
|
100% |
125
9.33 IPS |
|
|
Object Detection (I8)
|
61% |
361
27.0 IPS |
|
|
Face Detection (F32)
|
100% |
337
4.01 IPS |
|
|
Face Detection (F16)
|
100% |
336
3.99 IPS |
|
|
Face Detection (I8)
|
86% |
752
8.94 IPS |
|
|
Depth Estimation (F32)
|
100% |
272
2.11 IPS |
|
|
Depth Estimation (F16)
|
100% |
272
2.11 IPS |
|
|
Depth Estimation (I8)
|
95% |
782
6.06 IPS |
|
|
Style Transfer (F32)
|
100% |
481
0.63 IPS |
|
|
Style Transfer (F16)
|
100% |
481
0.63 IPS |
|
|
Style Transfer (I8)
|
98% |
1290
1.70 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
136
4.84 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
136
4.85 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
481
17.2 IPS |
|
|
Text Classification (F32)
|
100% |
162
233.5 IPS |
|
|
Text Classification (F16)
|
100% |
163
233.8 IPS |
|
|
Text Classification (I8)
|
92% |
286
410.5 IPS |
|
|
Machine Translation (F32)
|
100% |
302
5.56 IPS |
|
|
Machine Translation (F16)
|
100% |
303
5.58 IPS |
|
|
Machine Translation (I8)
|
64% |
360
6.63 IPS |
