realme RMX3800
Geekbench ML Score
290
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 07:44 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3800 |
| Model ID | realme RMX3800 |
| Motherboard | pineapple |
| Governor | uag |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 10.99 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
227
42.5 IPS |
|
|
Image Classification (F16)
|
100% |
226
42.3 IPS |
|
|
Image Classification (I8)
|
97% |
619
115.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
288
4.82 IPS |
|
|
Image Segmentation (F16)
|
100% |
167
2.79 IPS |
|
|
Image Segmentation (I8)
|
98% |
308
5.14 IPS |
|
|
Pose Estimation (F32)
|
100% |
201
0.24 IPS |
|
|
Pose Estimation (F16)
|
100% |
191
0.23 IPS |
|
|
Pose Estimation (I8)
|
100% |
719
0.87 IPS |
|
|
Object Detection (F32)
|
100% |
119
8.90 IPS |
|
|
Object Detection (F16)
|
100% |
119
8.88 IPS |
|
|
Object Detection (I8)
|
61% |
321
23.9 IPS |
|
|
Face Detection (F32)
|
100% |
341
4.06 IPS |
|
|
Face Detection (F16)
|
100% |
371
4.41 IPS |
|
|
Face Detection (I8)
|
86% |
654
7.77 IPS |
|
|
Depth Estimation (F32)
|
100% |
272
2.11 IPS |
|
|
Depth Estimation (F16)
|
100% |
268
2.08 IPS |
|
|
Depth Estimation (I8)
|
95% |
715
5.54 IPS |
|
|
Style Transfer (F32)
|
100% |
474
0.62 IPS |
|
|
Style Transfer (F16)
|
100% |
473
0.62 IPS |
|
|
Style Transfer (I8)
|
98% |
1306
1.72 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
132
4.73 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
132
4.72 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
457
16.3 IPS |
|
|
Text Classification (F32)
|
100% |
146
210.0 IPS |
|
|
Text Classification (F16)
|
100% |
146
209.6 IPS |
|
|
Text Classification (I8)
|
92% |
238
342.1 IPS |
|
|
Machine Translation (F32)
|
100% |
282
5.19 IPS |
|
|
Machine Translation (F16)
|
100% |
282
5.18 IPS |
|
|
Machine Translation (I8)
|
64% |
338
6.23 IPS |
