Xiaomi 13
Geekbench ML Score
500
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 07:24 AM |
| Views | 1 |
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% |
228
42.7 IPS |
|
|
Image Classification (I8)
|
97% |
531
99.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
284
4.75 IPS |
|
|
Image Segmentation (F16)
|
100% |
283
4.73 IPS |
|
|
Image Segmentation (I8)
|
98% |
546
9.12 IPS |
|
|
Pose Estimation (F32)
|
100% |
406
0.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
407
0.49 IPS |
|
|
Pose Estimation (I8)
|
100% |
1529
1.85 IPS |
|
|
Object Detection (F32)
|
100% |
240
17.9 IPS |
|
|
Object Detection (F16)
|
100% |
240
17.9 IPS |
|
|
Object Detection (I8)
|
61% |
601
44.8 IPS |
|
|
Face Detection (F32)
|
100% |
569
6.76 IPS |
|
|
Face Detection (F16)
|
100% |
570
6.77 IPS |
|
|
Face Detection (I8)
|
86% |
1174
14.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
501
3.89 IPS |
|
|
Depth Estimation (F16)
|
100% |
504
3.91 IPS |
|
|
Depth Estimation (I8)
|
95% |
1344
10.4 IPS |
|
|
Style Transfer (F32)
|
100% |
822
1.08 IPS |
|
|
Style Transfer (F16)
|
100% |
809
1.06 IPS |
|
|
Style Transfer (I8)
|
98% |
2131
2.80 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
278
9.94 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
274
9.79 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
954
34.1 IPS |
|
|
Text Classification (F32)
|
100% |
311
447.4 IPS |
|
|
Text Classification (F16)
|
100% |
310
445.6 IPS |
|
|
Text Classification (I8)
|
92% |
452
649.2 IPS |
|
|
Machine Translation (F32)
|
100% |
534
9.82 IPS |
|
|
Machine Translation (F16)
|
100% |
540
9.93 IPS |
|
|
Machine Translation (I8)
|
64% |
532
9.79 IPS |
