Xiaomi Redmi Note 11T Pro
Geekbench ML Score
507
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 16 2024 08:01 AM |
| Views | 2 |
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% |
221
41.3 IPS |
|
|
Image Classification (F16)
|
100% |
243
45.5 IPS |
|
|
Image Classification (I8)
|
97% |
426
79.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
298
4.97 IPS |
|
|
Image Segmentation (F16)
|
100% |
290
4.85 IPS |
|
|
Image Segmentation (I8)
|
98% |
427
7.12 IPS |
|
|
Pose Estimation (F32)
|
100% |
625
0.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
614
0.74 IPS |
|
|
Pose Estimation (I8)
|
100% |
2289
2.77 IPS |
|
|
Object Detection (F32)
|
100% |
250
18.7 IPS |
|
|
Object Detection (F16)
|
100% |
234
17.5 IPS |
|
|
Object Detection (I8)
|
61% |
577
43.1 IPS |
|
|
Face Detection (F32)
|
100% |
564
6.71 IPS |
|
|
Face Detection (F16)
|
100% |
575
6.84 IPS |
|
|
Face Detection (I8)
|
86% |
1096
13.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
533
4.14 IPS |
|
|
Depth Estimation (F16)
|
100% |
528
4.10 IPS |
|
|
Depth Estimation (I8)
|
95% |
1203
9.33 IPS |
|
|
Style Transfer (F32)
|
100% |
1168
1.54 IPS |
|
|
Style Transfer (F16)
|
100% |
1169
1.54 IPS |
|
|
Style Transfer (I8)
|
98% |
2275
2.99 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
281
10.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
338
12.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
955
34.1 IPS |
|
|
Text Classification (F32)
|
100% |
334
479.9 IPS |
|
|
Text Classification (F16)
|
100% |
318
456.8 IPS |
|
|
Text Classification (I8)
|
92% |
271
389.9 IPS |
|
|
Machine Translation (F32)
|
100% |
467
8.60 IPS |
|
|
Machine Translation (F16)
|
100% |
506
9.30 IPS |
|
|
Machine Translation (I8)
|
64% |
259
4.76 IPS |
