Xiaomi Redmi Note 11T Pro
Geekbench ML Score
618
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 18 2024 03:48 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi Redmi Note 11T Pro |
| Model ID | Xiaomi 22041216C |
| Motherboard | xaga |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.85 GHz |
| Memory Information | |
|---|---|
| Size | 7.30 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
299
55.9 IPS |
|
|
Image Classification (F16)
|
100% |
292
54.7 IPS |
|
|
Image Classification (I8)
|
97% |
513
96.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
382
6.37 IPS |
|
|
Image Segmentation (F16)
|
100% |
366
6.10 IPS |
|
|
Image Segmentation (I8)
|
98% |
534
8.92 IPS |
|
|
Pose Estimation (F32)
|
100% |
679
0.82 IPS |
|
|
Pose Estimation (F16)
|
100% |
685
0.83 IPS |
|
|
Pose Estimation (I8)
|
100% |
2596
3.14 IPS |
|
|
Object Detection (F32)
|
100% |
328
24.5 IPS |
|
|
Object Detection (F16)
|
100% |
327
24.4 IPS |
|
|
Object Detection (I8)
|
61% |
672
50.2 IPS |
|
|
Face Detection (F32)
|
100% |
715
8.50 IPS |
|
|
Face Detection (F16)
|
100% |
691
8.21 IPS |
|
|
Face Detection (I8)
|
86% |
1252
14.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
673
5.22 IPS |
|
|
Depth Estimation (F16)
|
100% |
653
5.07 IPS |
|
|
Depth Estimation (I8)
|
95% |
1340
10.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1248
1.64 IPS |
|
|
Style Transfer (F16)
|
100% |
1243
1.64 IPS |
|
|
Style Transfer (I8)
|
98% |
2675
3.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
362
12.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
373
13.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1124
40.2 IPS |
|
|
Text Classification (F32)
|
100% |
392
563.6 IPS |
|
|
Text Classification (F16)
|
100% |
413
593.3 IPS |
|
|
Text Classification (I8)
|
92% |
363
522.3 IPS |
|
|
Machine Translation (F32)
|
100% |
603
11.1 IPS |
|
|
Machine Translation (F16)
|
100% |
622
11.4 IPS |
|
|
Machine Translation (I8)
|
64% |
372
6.85 IPS |
