Xiaomi Mi 11
Geekbench ML Score
592
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 19 2024 09:14 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi Mi 11 |
| Model ID | Xiaomi M2011K2C |
| Motherboard | venus |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Venus |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 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 @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 7.08 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
252
47.2 IPS |
|
|
Image Classification (F16)
|
100% |
253
47.4 IPS |
|
|
Image Classification (I8)
|
97% |
610
114.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
357
5.96 IPS |
|
|
Image Segmentation (F16)
|
100% |
353
5.90 IPS |
|
|
Image Segmentation (I8)
|
98% |
522
8.71 IPS |
|
|
Pose Estimation (F32)
|
100% |
535
0.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
492
0.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
2678
3.24 IPS |
|
|
Object Detection (F32)
|
100% |
293
21.9 IPS |
|
|
Object Detection (F16)
|
100% |
285
21.2 IPS |
|
|
Object Detection (I8)
|
61% |
863
64.5 IPS |
|
|
Face Detection (F32)
|
100% |
639
7.60 IPS |
|
|
Face Detection (F16)
|
100% |
629
7.48 IPS |
|
|
Face Detection (I8)
|
86% |
1527
18.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
603
4.67 IPS |
|
|
Depth Estimation (F16)
|
100% |
569
4.41 IPS |
|
|
Depth Estimation (I8)
|
95% |
1576
12.2 IPS |
|
|
Style Transfer (F32)
|
100% |
1021
1.34 IPS |
|
|
Style Transfer (F16)
|
100% |
1039
1.37 IPS |
|
|
Style Transfer (I8)
|
98% |
2824
3.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
432
15.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
410
14.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1531
54.7 IPS |
|
|
Text Classification (F32)
|
100% |
389
558.9 IPS |
|
|
Text Classification (F16)
|
100% |
328
471.1 IPS |
|
|
Text Classification (I8)
|
92% |
280
402.7 IPS |
|
|
Machine Translation (F32)
|
100% |
648
11.9 IPS |
|
|
Machine Translation (F16)
|
100% |
635
11.7 IPS |
|
|
Machine Translation (I8)
|
64% |
294
5.40 IPS |
