Huawei Mate 40 Pro
Geekbench ML Score
364
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 22 2025 02:49 PM |
| Views | 27 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Huawei Mate 40 Pro |
| Model ID | HUAWEI NOH-AN00 |
| Motherboard | NOH |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 2.04 GHz |
| Cluster 1 | 4 Cores @ 2.04 GHz |
| Cluster 2 | 3 Cores @ 2.54 GHz |
| Cluster 3 | 1 Core @ 3.13 GHz |
| Memory Information | |
|---|---|
| Size | 7.31 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
164
30.7 IPS |
|
|
Image Classification (F16)
|
100% |
165
30.8 IPS |
|
|
Image Classification (I8)
|
97% |
432
80.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
214
3.57 IPS |
|
|
Image Segmentation (F16)
|
100% |
213
3.56 IPS |
|
|
Image Segmentation (I8)
|
98% |
438
7.32 IPS |
|
|
Pose Estimation (F32)
|
100% |
259
0.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
261
0.32 IPS |
|
|
Pose Estimation (I8)
|
100% |
1070
1.30 IPS |
|
|
Object Detection (F32)
|
100% |
173
12.9 IPS |
|
|
Object Detection (F16)
|
100% |
173
12.9 IPS |
|
|
Object Detection (I8)
|
61% |
487
36.3 IPS |
|
|
Face Detection (F32)
|
100% |
406
4.83 IPS |
|
|
Face Detection (F16)
|
100% |
406
4.83 IPS |
|
|
Face Detection (I8)
|
86% |
944
11.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
335
2.60 IPS |
|
|
Depth Estimation (F16)
|
100% |
335
2.60 IPS |
|
|
Depth Estimation (I8)
|
95% |
999
7.75 IPS |
|
|
Style Transfer (F32)
|
100% |
538
0.71 IPS |
|
|
Style Transfer (F16)
|
100% |
536
0.70 IPS |
|
|
Style Transfer (I8)
|
98% |
1697
2.23 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
182
6.51 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
182
6.51 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
687
24.5 IPS |
|
|
Text Classification (F32)
|
100% |
226
325.0 IPS |
|
|
Text Classification (F16)
|
100% |
227
326.2 IPS |
|
|
Text Classification (I8)
|
92% |
398
572.4 IPS |
|
|
Machine Translation (F32)
|
100% |
386
7.11 IPS |
|
|
Machine Translation (F16)
|
100% |
391
7.19 IPS |
|
|
Machine Translation (I8)
|
64% |
487
8.97 IPS |
