realme RMX3660
Geekbench ML Score
429
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 07 2024 11:10 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3660 |
| Model ID | realme RMX3660 |
| Motherboard | holi |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 7.24 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
193
36.2 IPS |
|
|
Image Classification (F16)
|
100% |
195
36.4 IPS |
|
|
Image Classification (I8)
|
97% |
514
96.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
264
4.41 IPS |
|
|
Image Segmentation (F16)
|
100% |
276
4.61 IPS |
|
|
Image Segmentation (I8)
|
98% |
418
6.98 IPS |
|
|
Pose Estimation (F32)
|
100% |
375
0.45 IPS |
|
|
Pose Estimation (F16)
|
100% |
381
0.46 IPS |
|
|
Pose Estimation (I8)
|
100% |
1982
2.40 IPS |
|
|
Object Detection (F32)
|
100% |
206
15.4 IPS |
|
|
Object Detection (F16)
|
100% |
216
16.1 IPS |
|
|
Object Detection (I8)
|
61% |
602
44.9 IPS |
|
|
Face Detection (F32)
|
100% |
441
5.25 IPS |
|
|
Face Detection (F16)
|
100% |
435
5.17 IPS |
|
|
Face Detection (I8)
|
86% |
1127
13.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
427
3.31 IPS |
|
|
Depth Estimation (F16)
|
100% |
440
3.41 IPS |
|
|
Depth Estimation (I8)
|
95% |
1153
8.94 IPS |
|
|
Style Transfer (F32)
|
100% |
722
0.95 IPS |
|
|
Style Transfer (F16)
|
100% |
724
0.95 IPS |
|
|
Style Transfer (I8)
|
98% |
1987
2.61 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
264
9.43 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
270
9.63 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
818
29.2 IPS |
|
|
Text Classification (F32)
|
100% |
247
354.6 IPS |
|
|
Text Classification (F16)
|
100% |
236
339.8 IPS |
|
|
Text Classification (I8)
|
92% |
209
300.3 IPS |
|
|
Machine Translation (F32)
|
100% |
486
8.94 IPS |
|
|
Machine Translation (F16)
|
100% |
500
9.20 IPS |
|
|
Machine Translation (I8)
|
64% |
256
4.70 IPS |
