Xiaomi Redmi K40
Geekbench ML Score
625
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | 46fy45 |
| Upload Date | August 23 2024 09:37 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| 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 | 5.48 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
397
74.3 IPS |
|
|
Image Classification (F16)
|
100% |
606
113.4 IPS |
|
|
Image Classification (I8)
|
97% |
654
122.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
537
8.97 IPS |
|
|
Image Segmentation (F16)
|
100% |
698
11.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
772
12.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1539
1.86 IPS |
|
|
Pose Estimation (F16)
|
100% |
5658
6.85 IPS |
|
|
Pose Estimation (I8)
|
100% |
11120
13.5 IPS |
|
|
Object Detection (F32)
|
100% |
402
30.0 IPS |
|
|
Object Detection (F16)
|
99% |
519
38.7 IPS |
|
|
Object Detection (I8)
|
59% |
1194
89.1 IPS |
|
|
Face Detection (F32)
|
100% |
1030
12.2 IPS |
|
|
Face Detection (F16)
|
97% |
1274
15.1 IPS |
|
|
Face Detection (I8)
|
88% |
3378
40.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
405
3.14 IPS |
|
|
Depth Estimation (F16)
|
100% |
457
3.54 IPS |
|
|
Depth Estimation (I8)
|
82% |
7505
58.2 IPS |
|
|
Style Transfer (F32)
|
100% |
598
0.79 IPS |
|
|
Style Transfer (F16)
|
100% |
623
0.82 IPS |
|
|
Style Transfer (I8)
|
98% |
2812
3.70 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
794
28.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1958
69.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
5072
181.1 IPS |
|
|
Text Classification (F32)
|
64% |
3
4.47 IPS |
|
|
Text Classification (F16)
|
64% |
6
7.94 IPS |
|
|
Text Classification (I8)
|
94% |
83
119.1 IPS |
|
|
Machine Translation (F32)
|
100% |
120
2.21 IPS |
|
|
Machine Translation (F16)
|
100% |
312
5.74 IPS |
|
|
Machine Translation (I8)
|
58% |
244
4.49 IPS |
