realme RMX5010
Geekbench AI Score
2326
Single Precision Score
2331
Half Precision Score
3021
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 27 2024 11:36 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | realme RMX5010 |
| Model ID | realme RMX5010 |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1394
259.3 IPS |
|
|
Image Classification (HP)
|
100% |
1460
271.5 IPS |
|
|
Image Classification (Q)
|
100% |
2730
507.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2001
32.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1910
31.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
3473
56.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
4381
5.11 IPS |
|
|
Pose Estimation (HP)
|
100% |
4305
5.02 IPS |
|
|
Pose Estimation (Q)
|
84% |
10849
12.9 IPS |
|
|
Object Detection (SP)
|
98% |
1310
104.3 IPS |
|
|
Object Detection (HP)
|
98% |
1297
103.2 IPS |
|
|
Object Detection (Q)
|
83% |
2081
168.1 IPS |
|
|
Face Detection (SP)
|
100% |
3503
41.6 IPS |
|
|
Face Detection (HP)
|
100% |
3552
42.2 IPS |
|
|
Face Detection (Q)
|
95% |
5948
71.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
4058
31.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
4079
31.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
5839
53.5 IPS |
|
|
Style Transfer (SP)
|
89% |
10075
13.1 IPS |
|
|
Style Transfer (HP)
|
89% |
10012
13.0 IPS |
|
|
Style Transfer (Q)
|
98% |
20182
26.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1747
64.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1777
65.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3319
123.0 IPS |
|
|
Text Classification (SP)
|
100% |
913
1.22 KIPS |
|
|
Text Classification (HP)
|
99% |
965
1.29 KIPS |
|
|
Text Classification (Q)
|
88% |
497
670.2 IPS |
|
|
Machine Translation (SP)
|
100% |
1270
21.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1225
21.1 IPS |
|
|
Machine Translation (Q)
|
50% |
256
9.10 IPS |
