Xiaomi 13
Geekbench ML Score
785
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 03:15 AM |
| Views | 2 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
499
93.4 IPS |
|
|
Image Classification (F16)
|
100% |
721
135.0 IPS |
|
|
Image Classification (I8)
|
99% |
575
107.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
775
12.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
941
15.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
873
14.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
642
0.78 IPS |
|
|
Pose Estimation (F16)
|
100% |
921
1.12 IPS |
|
|
Pose Estimation (I8)
|
100% |
1100
1.33 IPS |
|
|
Object Detection (F32)
|
100% |
231
17.3 IPS |
|
|
Object Detection (F16)
|
100% |
332
24.8 IPS |
|
|
Object Detection (I8)
|
62% |
408
30.5 IPS |
|
|
Face Detection (F32)
|
100% |
1736
20.6 IPS |
|
|
Face Detection (F16)
|
97% |
1569
18.6 IPS |
|
|
Face Detection (I8)
|
86% |
1598
19.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1121
8.69 IPS |
|
|
Depth Estimation (F16)
|
100% |
2138
16.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
2150
16.7 IPS |
|
|
Style Transfer (F32)
|
100% |
2809
3.69 IPS |
|
|
Style Transfer (F16)
|
100% |
6495
8.54 IPS |
|
|
Style Transfer (I8)
|
98% |
6463
8.50 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
284
10.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
226
8.07 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
230
8.23 IPS |
|
|
Text Classification (F32)
|
100% |
310
445.6 IPS |
|
|
Text Classification (F16)
|
100% |
311
446.5 IPS |
|
|
Text Classification (I8)
|
92% |
450
647.0 IPS |
|
|
Machine Translation (F32)
|
100% |
542
9.98 IPS |
|
|
Machine Translation (F16)
|
100% |
541
9.96 IPS |
|
|
Machine Translation (I8)
|
64% |
532
9.79 IPS |
