Xiaomi Redmi K40
Geekbench ML Score
834
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | LiBoHanse |
| Upload Date | July 26 2024 01:32 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Xiaomi Redmi K40 |
| Model ID | Xiaomi M2012K11AC |
| Motherboard | alioth |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 11.23 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
460
86.1 IPS |
|
|
Image Classification (F16)
|
100% |
756
141.5 IPS |
|
|
Image Classification (I8)
|
97% |
1411
264.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
636
10.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
850
14.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
1217
20.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
1537
1.86 IPS |
|
|
Pose Estimation (F16)
|
100% |
5799
7.02 IPS |
|
|
Pose Estimation (I8)
|
100% |
11057
13.4 IPS |
|
|
Object Detection (F32)
|
100% |
462
34.5 IPS |
|
|
Object Detection (F16)
|
99% |
701
52.4 IPS |
|
|
Object Detection (I8)
|
59% |
1457
108.8 IPS |
|
|
Face Detection (F32)
|
100% |
1270
15.1 IPS |
|
|
Face Detection (F16)
|
97% |
1746
20.8 IPS |
|
|
Face Detection (I8)
|
88% |
3548
42.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
506
3.93 IPS |
|
|
Depth Estimation (F16)
|
100% |
574
4.45 IPS |
|
|
Depth Estimation (I8)
|
82% |
7604
59.0 IPS |
|
|
Style Transfer (F32)
|
100% |
745
0.98 IPS |
|
|
Style Transfer (F16)
|
100% |
785
1.03 IPS |
|
|
Style Transfer (I8)
|
98% |
3793
4.99 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
842
30.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2371
84.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
5794
206.9 IPS |
|
|
Text Classification (F32)
|
64% |
11
16.0 IPS |
|
|
Text Classification (F16)
|
64% |
11
15.8 IPS |
|
|
Text Classification (I8)
|
92% |
150
215.9 IPS |
|
|
Machine Translation (F32)
|
100% |
281
5.18 IPS |
|
|
Machine Translation (F16)
|
100% |
341
6.27 IPS |
|
|
Machine Translation (I8)
|
58% |
377
6.94 IPS |
