Xiaomi Mi 11
Geekbench ML Score
620
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 19 2024 03:09 PM |
| Views | 3 |
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% |
279
52.3 IPS |
|
|
Image Classification (F16)
|
100% |
272
50.8 IPS |
|
|
Image Classification (I8)
|
97% |
684
128.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
367
6.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
377
6.30 IPS |
|
|
Image Segmentation (I8)
|
98% |
546
9.12 IPS |
|
|
Pose Estimation (F32)
|
100% |
556
0.67 IPS |
|
|
Pose Estimation (F16)
|
100% |
520
0.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
2951
3.57 IPS |
|
|
Object Detection (F32)
|
100% |
302
22.6 IPS |
|
|
Object Detection (F16)
|
100% |
310
23.2 IPS |
|
|
Object Detection (I8)
|
61% |
889
66.4 IPS |
|
|
Face Detection (F32)
|
100% |
671
7.97 IPS |
|
|
Face Detection (F16)
|
100% |
656
7.80 IPS |
|
|
Face Detection (I8)
|
86% |
1586
18.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
643
4.99 IPS |
|
|
Depth Estimation (F16)
|
100% |
638
4.95 IPS |
|
|
Depth Estimation (I8)
|
95% |
1680
13.0 IPS |
|
|
Style Transfer (F32)
|
100% |
1080
1.42 IPS |
|
|
Style Transfer (F16)
|
100% |
1121
1.47 IPS |
|
|
Style Transfer (I8)
|
98% |
2922
3.84 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
387
13.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
377
13.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1355
48.4 IPS |
|
|
Text Classification (F32)
|
100% |
389
559.4 IPS |
|
|
Text Classification (F16)
|
100% |
370
531.8 IPS |
|
|
Text Classification (I8)
|
92% |
321
461.1 IPS |
|
|
Machine Translation (F32)
|
100% |
685
12.6 IPS |
|
|
Machine Translation (F16)
|
100% |
641
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
326
6.00 IPS |
