realme RMX5030
Geekbench AI Score
961
Single Precision Score
1298
Half Precision Score
915
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 24 2025 12:21 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | realme RMX5030 |
| Model ID | realme RMX5030 |
| Motherboard | k6897v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 0 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores @ 2.20 GHz |
| Cluster 2 | 3 Cores @ 3.20 GHz |
| Cluster 3 | 1 Core @ 3.35 GHz |
| Memory Information | |
|---|---|
| Size | 11.22 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
463
86.2 IPS |
|
|
Image Classification (HP)
|
100% |
503
93.6 IPS |
|
|
Image Classification (Q)
|
97% |
387
72.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1251
20.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1718
27.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1543
25.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6370
7.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
9821
11.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
9979
11.7 IPS |
|
|
Object Detection (SP)
|
100% |
669
53.1 IPS |
|
|
Object Detection (HP)
|
99% |
733
58.1 IPS |
|
|
Object Detection (Q)
|
83% |
1112
89.8 IPS |
|
|
Face Detection (SP)
|
100% |
2510
29.8 IPS |
|
|
Face Detection (HP)
|
100% |
2531
30.1 IPS |
|
|
Face Detection (Q)
|
96% |
2079
24.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2492
19.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
3381
26.1 IPS |
|
|
Depth Estimation (Q)
|
62% |
2712
25.8 IPS |
|
|
Style Transfer (SP)
|
100% |
9298
12.0 IPS |
|
|
Style Transfer (HP)
|
100% |
16299
21.0 IPS |
|
|
Style Transfer (Q)
|
98% |
14322
18.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1031
38.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1429
52.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1295
48.0 IPS |
|
|
Text Classification (SP)
|
35% |
17
156.5 IPS |
|
|
Text Classification (HP)
|
35% |
36
327.7 IPS |
|
|
Text Classification (Q)
|
29% |
8
137.2 IPS |
|
|
Machine Translation (SP)
|
100% |
269
4.64 IPS |
|
|
Machine Translation (HP)
|
100% |
306
5.26 IPS |
|
|
Machine Translation (Q)
|
43% |
75
4.33 IPS |
