realme RMX5108
Geekbench AI Score
538
Single Precision Score
819
Half Precision Score
626
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 28 2025 12:50 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | realme RMX5108 |
| Model ID | realme RMX5108 |
| Motherboard | RM6878 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.60 GHz |
| Memory Information | |
|---|---|
| Size | 7.29 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
269
50.0 IPS |
|
|
Image Classification (HP)
|
100% |
440
81.8 IPS |
|
|
Image Classification (Q)
|
97% |
394
73.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
562
9.11 IPS |
|
|
Image Segmentation (HP)
|
100% |
991
16.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
969
15.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
2511
2.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
4530
5.29 IPS |
|
|
Pose Estimation (Q)
|
95% |
4390
5.15 IPS |
|
|
Object Detection (SP)
|
100% |
257
20.4 IPS |
|
|
Object Detection (HP)
|
99% |
427
33.9 IPS |
|
|
Object Detection (Q)
|
83% |
369
29.8 IPS |
|
|
Face Detection (SP)
|
100% |
1102
13.1 IPS |
|
|
Face Detection (HP)
|
100% |
1632
19.4 IPS |
|
|
Face Detection (Q)
|
96% |
1409
16.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1704
13.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
2423
18.7 IPS |
|
|
Depth Estimation (Q)
|
62% |
2174
20.7 IPS |
|
|
Style Transfer (SP)
|
100% |
4277
5.50 IPS |
|
|
Style Transfer (HP)
|
100% |
7664
9.85 IPS |
|
|
Style Transfer (Q)
|
98% |
7579
9.77 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
716
26.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1056
39.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1060
39.3 IPS |
|
|
Text Classification (SP)
|
35% |
12
106.2 IPS |
|
|
Text Classification (HP)
|
35% |
14
124.0 IPS |
|
|
Text Classification (Q)
|
29% |
7
124.3 IPS |
|
|
Machine Translation (SP)
|
100% |
306
5.26 IPS |
|
|
Machine Translation (HP)
|
100% |
360
6.19 IPS |
|
|
Machine Translation (Q)
|
43% |
88
5.13 IPS |
