Huawei Mate 40 Pro
Geekbench ML Score
282
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 31 2025 09:09 PM |
| Views | 8 |
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% |
163
30.5 IPS |
|
|
Image Classification (F16)
|
100% |
163
30.5 IPS |
|
|
Image Classification (I8)
|
97% |
420
78.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
161
2.69 IPS |
|
|
Image Segmentation (F16)
|
100% |
159
2.66 IPS |
|
|
Image Segmentation (I8)
|
98% |
318
5.31 IPS |
|
|
Pose Estimation (F32)
|
100% |
198
0.24 IPS |
|
|
Pose Estimation (F16)
|
100% |
196
0.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
809
0.98 IPS |
|
|
Object Detection (F32)
|
100% |
128
9.58 IPS |
|
|
Object Detection (F16)
|
100% |
128
9.54 IPS |
|
|
Object Detection (I8)
|
61% |
358
26.7 IPS |
|
|
Face Detection (F32)
|
100% |
318
3.79 IPS |
|
|
Face Detection (F16)
|
100% |
324
3.85 IPS |
|
|
Face Detection (I8)
|
86% |
693
8.24 IPS |
|
|
Depth Estimation (F32)
|
100% |
260
2.02 IPS |
|
|
Depth Estimation (F16)
|
100% |
261
2.02 IPS |
|
|
Depth Estimation (I8)
|
95% |
741
5.74 IPS |
|
|
Style Transfer (F32)
|
100% |
434
0.57 IPS |
|
|
Style Transfer (F16)
|
100% |
438
0.58 IPS |
|
|
Style Transfer (I8)
|
98% |
1330
1.75 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
139
4.95 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
138
4.92 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
485
17.3 IPS |
|
|
Text Classification (F32)
|
100% |
156
224.2 IPS |
|
|
Text Classification (F16)
|
100% |
160
230.2 IPS |
|
|
Text Classification (I8)
|
92% |
288
414.3 IPS |
|
|
Machine Translation (F32)
|
100% |
305
5.61 IPS |
|
|
Machine Translation (F16)
|
100% |
302
5.56 IPS |
|
|
Machine Translation (I8)
|
64% |
363
6.68 IPS |
