Xiaomi 13
Geekbench ML Score
501
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 07:30 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Xiaomi 13 |
| Model ID | Xiaomi 2211133C |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 10.90 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
226
42.3 IPS |
|
|
Image Classification (F16)
|
100% |
227
42.5 IPS |
|
|
Image Classification (I8)
|
97% |
535
100.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
283
4.73 IPS |
|
|
Image Segmentation (F16)
|
100% |
283
4.73 IPS |
|
|
Image Segmentation (I8)
|
98% |
595
9.93 IPS |
|
|
Pose Estimation (F32)
|
100% |
406
0.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
406
0.49 IPS |
|
|
Pose Estimation (I8)
|
100% |
1516
1.84 IPS |
|
|
Object Detection (F32)
|
100% |
247
18.4 IPS |
|
|
Object Detection (F16)
|
100% |
239
17.9 IPS |
|
|
Object Detection (I8)
|
61% |
605
45.2 IPS |
|
|
Face Detection (F32)
|
100% |
569
6.76 IPS |
|
|
Face Detection (F16)
|
100% |
571
6.79 IPS |
|
|
Face Detection (I8)
|
86% |
1157
13.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
503
3.90 IPS |
|
|
Depth Estimation (F16)
|
100% |
501
3.88 IPS |
|
|
Depth Estimation (I8)
|
95% |
1349
10.5 IPS |
|
|
Style Transfer (F32)
|
100% |
811
1.07 IPS |
|
|
Style Transfer (F16)
|
100% |
814
1.07 IPS |
|
|
Style Transfer (I8)
|
98% |
2180
2.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
273
9.76 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
275
9.83 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
954
34.1 IPS |
|
|
Text Classification (F32)
|
100% |
310
445.4 IPS |
|
|
Text Classification (F16)
|
100% |
310
446.0 IPS |
|
|
Text Classification (I8)
|
92% |
451
647.8 IPS |
|
|
Machine Translation (F32)
|
100% |
534
9.83 IPS |
|
|
Machine Translation (F16)
|
100% |
537
9.89 IPS |
|
|
Machine Translation (I8)
|
64% |
531
9.78 IPS |
