realme RMX3868
Geekbench ML Score
442
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 09:27 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3868 |
| Model ID | realme RMX3868 |
| Motherboard | RM6877 |
| CPU Information | |
|---|---|
| Name | ARM MT6877V/TTZA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.60 GHz |
| Memory Information | |
|---|---|
| Size | 7.36 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
203
37.9 IPS |
|
|
Image Classification (F16)
|
100% |
204
38.2 IPS |
|
|
Image Classification (I8)
|
97% |
409
76.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
295
4.93 IPS |
|
|
Image Segmentation (F16)
|
100% |
310
5.17 IPS |
|
|
Image Segmentation (I8)
|
98% |
401
6.69 IPS |
|
|
Pose Estimation (F32)
|
100% |
447
0.54 IPS |
|
|
Pose Estimation (F16)
|
100% |
455
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1932
2.34 IPS |
|
|
Object Detection (F32)
|
100% |
222
16.6 IPS |
|
|
Object Detection (F16)
|
100% |
205
15.3 IPS |
|
|
Object Detection (I8)
|
61% |
521
38.9 IPS |
|
|
Face Detection (F32)
|
100% |
474
5.64 IPS |
|
|
Face Detection (F16)
|
100% |
449
5.33 IPS |
|
|
Face Detection (I8)
|
86% |
1071
12.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
474
3.68 IPS |
|
|
Depth Estimation (F16)
|
100% |
478
3.71 IPS |
|
|
Depth Estimation (I8)
|
95% |
1100
8.53 IPS |
|
|
Style Transfer (F32)
|
100% |
813
1.07 IPS |
|
|
Style Transfer (F16)
|
100% |
823
1.08 IPS |
|
|
Style Transfer (I8)
|
98% |
2187
2.88 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
267
9.55 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
265
9.47 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
760
27.1 IPS |
|
|
Text Classification (F32)
|
100% |
287
411.8 IPS |
|
|
Text Classification (F16)
|
100% |
255
366.8 IPS |
|
|
Text Classification (I8)
|
92% |
146
209.8 IPS |
|
|
Machine Translation (F32)
|
100% |
496
9.14 IPS |
|
|
Machine Translation (F16)
|
100% |
514
9.45 IPS |
|
|
Machine Translation (I8)
|
64% |
348
6.40 IPS |
