realme RMX3571
Geekbench ML Score
403
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 07:43 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3571 |
| Model ID | realme RMX3571 |
| Motherboard | RM6833 |
| CPU Information | |
|---|---|
| Name | ARM MT6833V/PNZA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 3.52 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
222
41.5 IPS |
|
|
Image Classification (F16)
|
100% |
182
34.1 IPS |
|
|
Image Classification (I8)
|
97% |
470
87.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
288
4.81 IPS |
|
|
Image Segmentation (F16)
|
100% |
292
4.88 IPS |
|
|
Image Segmentation (I8)
|
98% |
405
6.77 IPS |
|
|
Pose Estimation (F32)
|
100% |
371
0.45 IPS |
|
|
Pose Estimation (F16)
|
100% |
395
0.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
1646
1.99 IPS |
|
|
Object Detection (F32)
|
100% |
154
11.5 IPS |
|
|
Object Detection (F16)
|
100% |
236
17.6 IPS |
|
|
Object Detection (I8)
|
61% |
467
34.9 IPS |
|
|
Face Detection (F32)
|
100% |
456
5.42 IPS |
|
|
Face Detection (F16)
|
100% |
442
5.26 IPS |
|
|
Face Detection (I8)
|
86% |
1030
12.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
386
2.99 IPS |
|
|
Depth Estimation (F16)
|
100% |
443
3.43 IPS |
|
|
Depth Estimation (I8)
|
95% |
1023
7.94 IPS |
|
|
Style Transfer (F32)
|
100% |
482
0.63 IPS |
|
|
Style Transfer (F16)
|
100% |
302
0.40 IPS |
|
|
Style Transfer (I8)
|
98% |
2022
2.66 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
174
6.22 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
268
9.58 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
900
32.1 IPS |
|
|
Text Classification (F32)
|
100% |
329
472.7 IPS |
|
|
Text Classification (F16)
|
100% |
291
418.4 IPS |
|
|
Text Classification (I8)
|
92% |
283
407.4 IPS |
|
|
Machine Translation (F32)
|
100% |
387
7.13 IPS |
|
|
Machine Translation (F16)
|
100% |
412
7.58 IPS |
|
|
Machine Translation (I8)
|
64% |
290
5.34 IPS |
