Xiaomi 25042PN24C
Geekbench ML Score
1136
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 23 2025 06:20 AM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Xiaomi 25042PN24C |
| Model ID | Xiaomi 25042PN24C |
| Motherboard | O1_asic |
| Governor | xres |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 2 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 1.89 GHz |
| Cluster 3 | 4 Cores @ 3.40 GHz |
| Cluster 4 | 2 Cores @ 3.90 GHz |
| Memory Information | |
|---|---|
| Size | 15.21 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
759
141.9 IPS |
|
|
Image Classification (F16)
|
100% |
1054
197.3 IPS |
|
|
Image Classification (I8)
|
97% |
751
140.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
601
10.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
962
16.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
892
14.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
819
0.99 IPS |
|
|
Pose Estimation (F16)
|
100% |
1287
1.56 IPS |
|
|
Pose Estimation (I8)
|
100% |
1279
1.55 IPS |
|
|
Object Detection (F32)
|
100% |
547
40.8 IPS |
|
|
Object Detection (F16)
|
100% |
448
33.5 IPS |
|
|
Object Detection (I8)
|
62% |
541
40.4 IPS |
|
|
Face Detection (F32)
|
100% |
2102
25.0 IPS |
|
|
Face Detection (F16)
|
98% |
2806
33.4 IPS |
|
|
Face Detection (I8)
|
86% |
2356
28.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1404
10.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
2312
17.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2178
16.9 IPS |
|
|
Style Transfer (F32)
|
100% |
3810
5.01 IPS |
|
|
Style Transfer (F16)
|
100% |
5699
7.50 IPS |
|
|
Style Transfer (I8)
|
98% |
5460
7.18 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
877
31.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1171
41.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
866
30.9 IPS |
|
|
Text Classification (F32)
|
100% |
448
644.0 IPS |
|
|
Text Classification (F16)
|
100% |
444
638.8 IPS |
|
|
Text Classification (I8)
|
92% |
851
1.22 KIPS |
|
|
Machine Translation (F32)
|
100% |
759
14.0 IPS |
|
|
Machine Translation (F16)
|
100% |
730
13.4 IPS |
|
|
Machine Translation (I8)
|
64% |
863
15.9 IPS |
