realme RMX5079
Geekbench ML Score
279
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 27 2025 11:42 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | realme RMX5079 |
| Model ID | realme RMX5079 |
| Motherboard | volcano |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3457 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.21 GHz |
| Cluster 3 | 1 Core @ 2.30 GHz |
| Memory Information | |
|---|---|
| Size | 7.24 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
155
29.1 IPS |
|
|
Image Classification (F16)
|
100% |
236
44.2 IPS |
|
|
Image Classification (I8)
|
100% |
221
41.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
260
4.35 IPS |
|
|
Image Segmentation (F16)
|
100% |
345
5.76 IPS |
|
|
Image Segmentation (I8)
|
98% |
333
5.56 IPS |
|
|
Pose Estimation (F32)
|
100% |
184
0.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
232
0.28 IPS |
|
|
Pose Estimation (I8)
|
100% |
242
0.29 IPS |
|
|
Object Detection (F32)
|
100% |
112
8.33 IPS |
|
|
Object Detection (F16)
|
100% |
149
11.2 IPS |
|
|
Object Detection (I8)
|
59% |
151
11.3 IPS |
|
|
Face Detection (F32)
|
100% |
460
5.47 IPS |
|
|
Face Detection (F16)
|
97% |
650
7.73 IPS |
|
|
Face Detection (I8)
|
86% |
600
7.13 IPS |
|
|
Depth Estimation (F32)
|
100% |
282
2.19 IPS |
|
|
Depth Estimation (F16)
|
100% |
463
3.59 IPS |
|
|
Depth Estimation (I8)
|
94% |
466
3.61 IPS |
|
|
Style Transfer (F32)
|
100% |
602
0.79 IPS |
|
|
Style Transfer (F16)
|
100% |
1123
1.48 IPS |
|
|
Style Transfer (I8)
|
98% |
1227
1.61 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
131
4.67 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
166
5.92 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
166
5.91 IPS |
|
|
Text Classification (F32)
|
100% |
166
238.1 IPS |
|
|
Text Classification (F16)
|
100% |
166
238.4 IPS |
|
|
Text Classification (I8)
|
92% |
294
422.9 IPS |
|
|
Machine Translation (F32)
|
100% |
302
5.56 IPS |
|
|
Machine Translation (F16)
|
100% |
213
3.91 IPS |
|
|
Machine Translation (I8)
|
64% |
236
4.34 IPS |
