Huawei Mate 40 Pro
Geekbench ML Score
525
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 31 2025 09:02 PM |
| Views | 7 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
339
63.4 IPS |
|
|
Image Classification (F16)
|
100% |
491
92.0 IPS |
|
|
Image Classification (I8)
|
97% |
439
82.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
456
7.62 IPS |
|
|
Image Segmentation (F16)
|
100% |
676
11.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
602
10.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
270
0.33 IPS |
|
|
Pose Estimation (F16)
|
100% |
378
0.46 IPS |
|
|
Pose Estimation (I8)
|
100% |
381
0.46 IPS |
|
|
Object Detection (F32)
|
100% |
222
16.6 IPS |
|
|
Object Detection (F16)
|
100% |
296
22.1 IPS |
|
|
Object Detection (I8)
|
62% |
318
23.8 IPS |
|
|
Face Detection (F32)
|
100% |
878
10.4 IPS |
|
|
Face Detection (F16)
|
98% |
1114
13.2 IPS |
|
|
Face Detection (I8)
|
86% |
1013
12.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
619
4.80 IPS |
|
|
Depth Estimation (F16)
|
100% |
732
5.67 IPS |
|
|
Depth Estimation (I8)
|
95% |
761
5.90 IPS |
|
|
Style Transfer (F32)
|
100% |
1311
1.72 IPS |
|
|
Style Transfer (F16)
|
100% |
2370
3.12 IPS |
|
|
Style Transfer (I8)
|
98% |
2381
3.13 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
388
13.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
622
22.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
594
21.2 IPS |
|
|
Text Classification (F32)
|
100% |
220
316.2 IPS |
|
|
Text Classification (F16)
|
100% |
223
319.8 IPS |
|
|
Text Classification (I8)
|
92% |
395
568.4 IPS |
|
|
Machine Translation (F32)
|
100% |
387
7.12 IPS |
|
|
Machine Translation (F16)
|
100% |
392
7.22 IPS |
|
|
Machine Translation (I8)
|
64% |
362
6.67 IPS |
