realme RMX3301
Geekbench ML Score
526
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 04:22 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3301 |
| Model ID | realme RMX3301 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 7.06 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
255
47.7 IPS |
|
|
Image Classification (F16)
|
100% |
255
47.7 IPS |
|
|
Image Classification (I8)
|
97% |
424
79.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
340
5.69 IPS |
|
|
Image Segmentation (F16)
|
100% |
355
5.92 IPS |
|
|
Image Segmentation (I8)
|
98% |
398
6.64 IPS |
|
|
Pose Estimation (F32)
|
100% |
680
0.82 IPS |
|
|
Pose Estimation (F16)
|
100% |
666
0.81 IPS |
|
|
Pose Estimation (I8)
|
100% |
2383
2.89 IPS |
|
|
Object Detection (F32)
|
100% |
281
21.0 IPS |
|
|
Object Detection (F16)
|
100% |
286
21.3 IPS |
|
|
Object Detection (I8)
|
61% |
543
40.5 IPS |
|
|
Face Detection (F32)
|
100% |
578
6.87 IPS |
|
|
Face Detection (F16)
|
100% |
573
6.82 IPS |
|
|
Face Detection (I8)
|
86% |
1013
12.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
630
4.88 IPS |
|
|
Depth Estimation (F16)
|
100% |
565
4.38 IPS |
|
|
Depth Estimation (I8)
|
95% |
1066
8.27 IPS |
|
|
Style Transfer (F32)
|
100% |
1256
1.65 IPS |
|
|
Style Transfer (F16)
|
100% |
1161
1.53 IPS |
|
|
Style Transfer (I8)
|
98% |
2248
2.96 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
355
12.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
364
13.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
920
32.9 IPS |
|
|
Text Classification (F32)
|
100% |
304
436.6 IPS |
|
|
Text Classification (F16)
|
100% |
340
488.0 IPS |
|
|
Text Classification (I8)
|
92% |
206
296.1 IPS |
|
|
Machine Translation (F32)
|
100% |
529
9.74 IPS |
|
|
Machine Translation (F16)
|
100% |
604
11.1 IPS |
|
|
Machine Translation (I8)
|
64% |
213
3.91 IPS |
