Xiaomi 24030PN60G
Geekbench ML Score
1096
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 23 2024 09:08 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi 24030PN60G |
| Model ID | Xiaomi 24030PN60G |
| Motherboard | aurora |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.86 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
563
105.3 IPS |
|
|
Image Classification (F16)
|
100% |
571
106.8 IPS |
|
|
Image Classification (I8)
|
97% |
888
166.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
730
12.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
737
12.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
704
11.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1345
1.63 IPS |
|
|
Pose Estimation (F16)
|
100% |
1366
1.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
4943
5.99 IPS |
|
|
Object Detection (F32)
|
100% |
559
41.8 IPS |
|
|
Object Detection (F16)
|
100% |
569
42.5 IPS |
|
|
Object Detection (I8)
|
61% |
1111
83.0 IPS |
|
|
Face Detection (F32)
|
100% |
1300
15.5 IPS |
|
|
Face Detection (F16)
|
100% |
1294
15.4 IPS |
|
|
Face Detection (I8)
|
86% |
1925
22.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1264
9.81 IPS |
|
|
Depth Estimation (F16)
|
100% |
1270
9.85 IPS |
|
|
Depth Estimation (I8)
|
95% |
2017
15.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2409
3.17 IPS |
|
|
Style Transfer (F16)
|
100% |
2449
3.22 IPS |
|
|
Style Transfer (I8)
|
98% |
4907
6.45 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
836
29.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
832
29.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2149
76.7 IPS |
|
|
Text Classification (F32)
|
100% |
608
873.1 IPS |
|
|
Text Classification (F16)
|
100% |
619
889.9 IPS |
|
|
Text Classification (I8)
|
92% |
380
546.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1300
23.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1336
24.6 IPS |
|
|
Machine Translation (I8)
|
64% |
403
7.41 IPS |
