realme RMX5107
Geekbench AI Score
547
Single Precision Score
817
Half Precision Score
648
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | February 02 2026 12:23 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | realme RMX5107 |
| Model ID | realme RMX5107 |
| 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 | 11.19 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
270
50.3 IPS |
|
|
Image Classification (HP)
|
100% |
635
118.1 IPS |
|
|
Image Classification (Q)
|
97% |
326
60.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
628
10.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1059
17.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
983
16.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2514
2.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
4382
5.11 IPS |
|
|
Pose Estimation (Q)
|
95% |
4302
5.04 IPS |
|
|
Object Detection (SP)
|
100% |
261
20.7 IPS |
|
|
Object Detection (HP)
|
99% |
400
31.7 IPS |
|
|
Object Detection (Q)
|
83% |
385
31.1 IPS |
|
|
Face Detection (SP)
|
100% |
1154
13.7 IPS |
|
|
Face Detection (HP)
|
100% |
1761
20.9 IPS |
|
|
Face Detection (Q)
|
96% |
1520
18.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1536
11.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
2469
19.1 IPS |
|
|
Depth Estimation (Q)
|
62% |
1993
18.9 IPS |
|
|
Style Transfer (SP)
|
100% |
4247
5.46 IPS |
|
|
Style Transfer (HP)
|
100% |
7617
9.79 IPS |
|
|
Style Transfer (Q)
|
98% |
7780
10.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
727
26.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1056
39.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1074
39.8 IPS |
|
|
Text Classification (SP)
|
35% |
12
110.9 IPS |
|
|
Text Classification (HP)
|
29% |
8
131.3 IPS |
|
|
Text Classification (Q)
|
32% |
10
132.0 IPS |
|
|
Machine Translation (SP)
|
100% |
334
5.76 IPS |
|
|
Machine Translation (HP)
|
100% |
406
6.99 IPS |
|
|
Machine Translation (Q)
|
43% |
98
5.67 IPS |
