realme RMX5010
Geekbench ML Score
1598
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 20 2024 03:13 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | realme RMX5010 |
| Model ID | realme RMX5010 |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
959
179.4 IPS |
|
|
Image Classification (F16)
|
100% |
1031
192.9 IPS |
|
|
Image Classification (I8)
|
97% |
1234
230.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1279
21.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1315
22.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1185
19.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1839
2.23 IPS |
|
|
Pose Estimation (F16)
|
100% |
1834
2.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
8488
10.3 IPS |
|
|
Object Detection (F32)
|
100% |
1085
81.0 IPS |
|
|
Object Detection (F16)
|
100% |
1087
81.2 IPS |
|
|
Object Detection (I8)
|
61% |
2052
153.2 IPS |
|
|
Face Detection (F32)
|
100% |
1987
23.6 IPS |
|
|
Face Detection (F16)
|
100% |
1935
23.0 IPS |
|
|
Face Detection (I8)
|
86% |
3733
44.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1950
15.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
1946
15.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
4454
34.5 IPS |
|
|
Style Transfer (F32)
|
100% |
3108
4.09 IPS |
|
|
Style Transfer (F16)
|
100% |
3094
4.07 IPS |
|
|
Style Transfer (I8)
|
98% |
7935
10.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1217
43.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1211
43.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
3180
113.6 IPS |
|
|
Text Classification (F32)
|
100% |
495
710.7 IPS |
|
|
Text Classification (F16)
|
100% |
481
691.5 IPS |
|
|
Text Classification (I8)
|
92% |
643
924.1 IPS |
|
|
Machine Translation (F32)
|
100% |
903
16.6 IPS |
|
|
Machine Translation (F16)
|
100% |
848
15.6 IPS |
|
|
Machine Translation (I8)
|
64% |
754
13.9 IPS |
