Xiaomi Mi 11
Geekbench ML Score
614
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 19 2024 02:36 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% |
236
44.2 IPS |
|
|
Image Classification (F16)
|
100% |
255
47.6 IPS |
|
|
Image Classification (I8)
|
97% |
650
121.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
376
6.27 IPS |
|
|
Image Segmentation (F16)
|
100% |
362
6.04 IPS |
|
|
Image Segmentation (I8)
|
98% |
552
9.21 IPS |
|
|
Pose Estimation (F32)
|
100% |
581
0.70 IPS |
|
|
Pose Estimation (F16)
|
100% |
555
0.67 IPS |
|
|
Pose Estimation (I8)
|
100% |
2955
3.58 IPS |
|
|
Object Detection (F32)
|
100% |
306
22.9 IPS |
|
|
Object Detection (F16)
|
100% |
312
23.3 IPS |
|
|
Object Detection (I8)
|
61% |
905
67.6 IPS |
|
|
Face Detection (F32)
|
100% |
663
7.89 IPS |
|
|
Face Detection (F16)
|
100% |
671
7.97 IPS |
|
|
Face Detection (I8)
|
86% |
1599
19.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
608
4.71 IPS |
|
|
Depth Estimation (F16)
|
100% |
585
4.54 IPS |
|
|
Depth Estimation (I8)
|
95% |
1648
12.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1118
1.47 IPS |
|
|
Style Transfer (F16)
|
100% |
1165
1.53 IPS |
|
|
Style Transfer (I8)
|
98% |
2896
3.81 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
403
14.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
390
13.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1326
47.3 IPS |
|
|
Text Classification (F32)
|
100% |
373
535.9 IPS |
|
|
Text Classification (F16)
|
100% |
381
547.3 IPS |
|
|
Text Classification (I8)
|
92% |
279
400.4 IPS |
|
|
Machine Translation (F32)
|
100% |
660
12.1 IPS |
|
|
Machine Translation (F16)
|
100% |
707
13.0 IPS |
|
|
Machine Translation (I8)
|
64% |
315
5.80 IPS |
