realme RMX3741
Geekbench ML Score
409
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 03:13 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3741 |
| Model ID | realme RMX3741 |
| Motherboard | RM6877 |
| CPU Information | |
|---|---|
| Name | ARM MT6877V/TTZA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.60 GHz |
| Memory Information | |
|---|---|
| Size | 11.28 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
189
35.4 IPS |
|
|
Image Classification (F16)
|
100% |
180
33.6 IPS |
|
|
Image Classification (I8)
|
97% |
218
40.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
277
4.62 IPS |
|
|
Image Segmentation (F16)
|
100% |
273
4.56 IPS |
|
|
Image Segmentation (I8)
|
98% |
471
7.87 IPS |
|
|
Pose Estimation (F32)
|
100% |
396
0.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
391
0.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
1775
2.15 IPS |
|
|
Object Detection (F32)
|
100% |
207
15.5 IPS |
|
|
Object Detection (F16)
|
100% |
204
15.2 IPS |
|
|
Object Detection (I8)
|
61% |
438
32.7 IPS |
|
|
Face Detection (F32)
|
100% |
446
5.30 IPS |
|
|
Face Detection (F16)
|
100% |
455
5.41 IPS |
|
|
Face Detection (I8)
|
86% |
951
11.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
461
3.58 IPS |
|
|
Depth Estimation (F16)
|
100% |
437
3.39 IPS |
|
|
Depth Estimation (I8)
|
95% |
1016
7.88 IPS |
|
|
Style Transfer (F32)
|
100% |
768
1.01 IPS |
|
|
Style Transfer (F16)
|
100% |
761
1.00 IPS |
|
|
Style Transfer (I8)
|
98% |
2018
2.65 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
252
9.01 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
249
8.88 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
662
23.6 IPS |
|
|
Text Classification (F32)
|
100% |
247
355.0 IPS |
|
|
Text Classification (F16)
|
100% |
251
361.3 IPS |
|
|
Text Classification (I8)
|
92% |
214
307.7 IPS |
|
|
Machine Translation (F32)
|
100% |
468
8.61 IPS |
|
|
Machine Translation (F16)
|
100% |
458
8.43 IPS |
|
|
Machine Translation (I8)
|
64% |
306
5.64 IPS |
