realme RMX3800
Geekbench ML Score
1009
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 07:48 AM |
| Views | 1 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
522
97.7 IPS |
|
|
Image Classification (F16)
|
100% |
518
96.9 IPS |
|
|
Image Classification (I8)
|
97% |
837
156.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
639
10.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
639
10.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
530
8.86 IPS |
|
|
Pose Estimation (F32)
|
100% |
1313
1.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
1295
1.57 IPS |
|
|
Pose Estimation (I8)
|
100% |
4938
5.98 IPS |
|
|
Object Detection (F32)
|
100% |
528
39.4 IPS |
|
|
Object Detection (F16)
|
100% |
550
41.0 IPS |
|
|
Object Detection (I8)
|
61% |
1095
81.7 IPS |
|
|
Face Detection (F32)
|
100% |
1218
14.5 IPS |
|
|
Face Detection (F16)
|
100% |
1237
14.7 IPS |
|
|
Face Detection (I8)
|
86% |
1707
20.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1252
9.71 IPS |
|
|
Depth Estimation (F16)
|
100% |
1270
9.85 IPS |
|
|
Depth Estimation (I8)
|
95% |
1885
14.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2311
3.04 IPS |
|
|
Style Transfer (F16)
|
100% |
2269
2.98 IPS |
|
|
Style Transfer (I8)
|
98% |
4533
5.96 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
788
28.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
780
27.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1903
68.0 IPS |
|
|
Text Classification (F32)
|
100% |
582
837.1 IPS |
|
|
Text Classification (F16)
|
100% |
592
851.2 IPS |
|
|
Text Classification (I8)
|
92% |
356
512.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1233
22.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1246
22.9 IPS |
|
|
Machine Translation (I8)
|
64% |
253
4.66 IPS |
