realme RMX5079
Geekbench ML Score
552
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 27 2025 11:47 AM |
| Views | 1 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
299
56.0 IPS |
|
|
Image Classification (F16)
|
100% |
301
56.2 IPS |
|
|
Image Classification (I8)
|
97% |
544
101.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
383
6.40 IPS |
|
|
Image Segmentation (F16)
|
100% |
374
6.24 IPS |
|
|
Image Segmentation (I8)
|
98% |
382
6.38 IPS |
|
|
Pose Estimation (F32)
|
100% |
596
0.72 IPS |
|
|
Pose Estimation (F16)
|
100% |
582
0.71 IPS |
|
|
Pose Estimation (I8)
|
100% |
2673
3.24 IPS |
|
|
Object Detection (F32)
|
100% |
331
24.7 IPS |
|
|
Object Detection (F16)
|
100% |
331
24.7 IPS |
|
|
Object Detection (I8)
|
61% |
643
48.0 IPS |
|
|
Face Detection (F32)
|
100% |
577
6.86 IPS |
|
|
Face Detection (F16)
|
100% |
605
7.20 IPS |
|
|
Face Detection (I8)
|
86% |
799
9.50 IPS |
|
|
Depth Estimation (F32)
|
100% |
625
4.85 IPS |
|
|
Depth Estimation (F16)
|
100% |
624
4.84 IPS |
|
|
Depth Estimation (I8)
|
95% |
1158
8.98 IPS |
|
|
Style Transfer (F32)
|
100% |
1009
1.33 IPS |
|
|
Style Transfer (F16)
|
100% |
994
1.31 IPS |
|
|
Style Transfer (I8)
|
98% |
2438
3.21 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
367
13.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
376
13.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1238
44.2 IPS |
|
|
Text Classification (F32)
|
100% |
401
576.8 IPS |
|
|
Text Classification (F16)
|
100% |
398
571.4 IPS |
|
|
Text Classification (I8)
|
92% |
267
383.2 IPS |
|
|
Machine Translation (F32)
|
100% |
576
10.6 IPS |
|
|
Machine Translation (F16)
|
100% |
598
11.0 IPS |
|
|
Machine Translation (I8)
|
64% |
141
2.60 IPS |
