realme RMX5085
Geekbench AI Score
1593
Single Precision Score
1629
Half Precision Score
2372
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 29 2025 08:33 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | realme RMX5085 |
| Model ID | realme RMX5085 |
| Motherboard | k6899v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3463 revision 1 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 4 Cores @ 2.10 GHz |
| Cluster 2 | 3 Cores @ 3.00 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 11.19 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1056
196.4 IPS |
|
|
Image Classification (HP)
|
100% |
1332
247.7 IPS |
|
|
Image Classification (Q)
|
100% |
1807
336.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1343
21.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1388
22.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
1923
31.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2402
2.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
2404
2.80 IPS |
|
|
Pose Estimation (Q)
|
84% |
5392
6.39 IPS |
|
|
Object Detection (SP)
|
98% |
1246
99.2 IPS |
|
|
Object Detection (HP)
|
98% |
1235
98.3 IPS |
|
|
Object Detection (Q)
|
83% |
1670
134.9 IPS |
|
|
Face Detection (SP)
|
100% |
2555
30.4 IPS |
|
|
Face Detection (HP)
|
100% |
2655
31.6 IPS |
|
|
Face Detection (Q)
|
95% |
3765
44.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
2503
19.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2403
18.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
4066
37.2 IPS |
|
|
Style Transfer (SP)
|
89% |
5853
7.60 IPS |
|
|
Style Transfer (HP)
|
89% |
6026
7.82 IPS |
|
|
Style Transfer (Q)
|
98% |
11622
15.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1160
42.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1164
43.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2789
103.4 IPS |
|
|
Text Classification (SP)
|
100% |
511
681.5 IPS |
|
|
Text Classification (HP)
|
99% |
488
651.2 IPS |
|
|
Text Classification (Q)
|
88% |
797
1.08 KIPS |
|
|
Machine Translation (SP)
|
100% |
1124
19.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1098
18.9 IPS |
|
|
Machine Translation (Q)
|
50% |
456
16.2 IPS |
