realme RMX3301
Geekbench ML Score
667
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 27 2024 07:48 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| 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% |
327
61.1 IPS |
|
|
Image Classification (F16)
|
100% |
334
62.6 IPS |
|
|
Image Classification (I8)
|
97% |
526
98.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
421
7.04 IPS |
|
|
Image Segmentation (F16)
|
100% |
419
6.99 IPS |
|
|
Image Segmentation (I8)
|
98% |
479
7.99 IPS |
|
|
Pose Estimation (F32)
|
100% |
795
0.96 IPS |
|
|
Pose Estimation (F16)
|
100% |
760
0.92 IPS |
|
|
Pose Estimation (I8)
|
100% |
2854
3.46 IPS |
|
|
Object Detection (F32)
|
100% |
319
23.8 IPS |
|
|
Object Detection (F16)
|
100% |
337
25.2 IPS |
|
|
Object Detection (I8)
|
61% |
662
49.4 IPS |
|
|
Face Detection (F32)
|
100% |
730
8.69 IPS |
|
|
Face Detection (F16)
|
100% |
729
8.67 IPS |
|
|
Face Detection (I8)
|
86% |
1265
15.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
827
6.41 IPS |
|
|
Depth Estimation (F16)
|
100% |
800
6.20 IPS |
|
|
Depth Estimation (I8)
|
95% |
1460
11.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1508
1.98 IPS |
|
|
Style Transfer (F16)
|
100% |
1484
1.95 IPS |
|
|
Style Transfer (I8)
|
98% |
3139
4.13 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
466
16.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
478
17.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1340
47.9 IPS |
|
|
Text Classification (F32)
|
100% |
371
532.6 IPS |
|
|
Text Classification (F16)
|
100% |
372
534.2 IPS |
|
|
Text Classification (I8)
|
92% |
262
376.4 IPS |
|
|
Machine Translation (F32)
|
100% |
751
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
745
13.7 IPS |
|
|
Machine Translation (I8)
|
64% |
329
6.05 IPS |
