Huawei Mate 40 Pro
Geekbench ML Score
476
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 22 2025 02:35 PM |
| Views | 5 |
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% |
457
85.5 IPS |
|
|
Image Classification (F16)
|
100% |
673
126.0 IPS |
|
|
Image Classification (I8)
|
97% |
464
86.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
440
7.34 IPS |
|
|
Image Segmentation (F16)
|
100% |
597
9.97 IPS |
|
|
Image Segmentation (I8)
|
98% |
595
9.93 IPS |
|
|
Pose Estimation (F32)
|
100% |
267
0.32 IPS |
|
|
Pose Estimation (F16)
|
100% |
380
0.46 IPS |
|
|
Pose Estimation (I8)
|
100% |
381
0.46 IPS |
|
|
Object Detection (F32)
|
100% |
251
18.7 IPS |
|
|
Object Detection (F16)
|
100% |
361
26.9 IPS |
|
|
Object Detection (I8)
|
62% |
227
17.0 IPS |
|
|
Face Detection (F32)
|
100% |
739
8.78 IPS |
|
|
Face Detection (F16)
|
98% |
1479
17.6 IPS |
|
|
Face Detection (I8)
|
86% |
739
8.78 IPS |
|
|
Depth Estimation (F32)
|
100% |
367
2.85 IPS |
|
|
Depth Estimation (F16)
|
100% |
558
4.33 IPS |
|
|
Depth Estimation (I8)
|
95% |
530
4.11 IPS |
|
|
Style Transfer (F32)
|
100% |
1147
1.51 IPS |
|
|
Style Transfer (F16)
|
100% |
2232
2.94 IPS |
|
|
Style Transfer (I8)
|
98% |
1621
2.13 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
288
10.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
482
17.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
422
15.1 IPS |
|
|
Text Classification (F32)
|
100% |
190
272.7 IPS |
|
|
Text Classification (F16)
|
100% |
193
277.3 IPS |
|
|
Text Classification (I8)
|
92% |
342
492.1 IPS |
|
|
Machine Translation (F32)
|
100% |
361
6.64 IPS |
|
|
Machine Translation (F16)
|
100% |
360
6.63 IPS |
|
|
Machine Translation (I8)
|
64% |
359
6.61 IPS |
