realme RMX5061
Geekbench ML Score
890
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 26 2025 08:37 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | realme RMX5061 |
| Model ID | realme RMX5061 |
| Motherboard | k6989v2_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 11.08 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
596
111.5 IPS |
|
|
Image Classification (F16)
|
100% |
465
87.0 IPS |
|
|
Image Classification (I8)
|
97% |
692
129.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
672
11.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
718
12.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
656
10.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1096
1.33 IPS |
|
|
Pose Estimation (F16)
|
100% |
1103
1.34 IPS |
|
|
Pose Estimation (I8)
|
100% |
3993
4.84 IPS |
|
|
Object Detection (F32)
|
100% |
467
34.9 IPS |
|
|
Object Detection (F16)
|
100% |
439
32.8 IPS |
|
|
Object Detection (I8)
|
61% |
699
52.2 IPS |
|
|
Face Detection (F32)
|
100% |
1089
13.0 IPS |
|
|
Face Detection (F16)
|
100% |
1080
12.8 IPS |
|
|
Face Detection (I8)
|
86% |
1680
20.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1139
8.83 IPS |
|
|
Depth Estimation (F16)
|
100% |
1154
8.95 IPS |
|
|
Depth Estimation (I8)
|
95% |
1976
15.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1919
2.52 IPS |
|
|
Style Transfer (F16)
|
100% |
1694
2.23 IPS |
|
|
Style Transfer (I8)
|
98% |
3438
4.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
489
17.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
738
26.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1585
56.6 IPS |
|
|
Text Classification (F32)
|
100% |
428
614.6 IPS |
|
|
Text Classification (F16)
|
100% |
406
583.4 IPS |
|
|
Text Classification (I8)
|
92% |
351
504.1 IPS |
|
|
Machine Translation (F32)
|
100% |
992
18.3 IPS |
|
|
Machine Translation (F16)
|
100% |
979
18.0 IPS |
|
|
Machine Translation (I8)
|
64% |
383
7.04 IPS |
