realme RMX3890
Geekbench AI Score
50
Single Precision Score
93
Half Precision Score
92
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 22 2024 11:05 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3890 |
| Model ID | realme RMX3890 |
| Motherboard | bengal |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.40 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
34
6.41 IPS |
|
|
Image Classification (HP)
|
100% |
69
12.8 IPS |
|
|
Image Classification (Q)
|
97% |
70
13.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
31
0.51 IPS |
|
|
Image Segmentation (HP)
|
100% |
94
1.53 IPS |
|
|
Image Segmentation (Q)
|
98% |
89
1.44 IPS |
|
|
Pose Estimation (SP)
|
100% |
58
0.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
116
0.13 IPS |
|
|
Pose Estimation (Q)
|
95% |
115
0.13 IPS |
|
|
Object Detection (SP)
|
100% |
35
2.77 IPS |
|
|
Object Detection (HP)
|
100% |
58
4.58 IPS |
|
|
Object Detection (Q)
|
89% |
57
4.56 IPS |
|
|
Face Detection (SP)
|
100% |
86
1.02 IPS |
|
|
Face Detection (HP)
|
100% |
218
2.59 IPS |
|
|
Face Detection (Q)
|
97% |
221
2.64 IPS |
|
|
Depth Estimation (SP)
|
100% |
80
0.62 IPS |
|
|
Depth Estimation (HP)
|
99% |
163
1.26 IPS |
|
|
Depth Estimation (Q)
|
63% |
135
1.27 IPS |
|
|
Style Transfer (SP)
|
100% |
156
0.20 IPS |
|
|
Style Transfer (HP)
|
100% |
308
0.40 IPS |
|
|
Style Transfer (Q)
|
98% |
307
0.40 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39
1.46 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
82
3.01 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
80
2.98 IPS |
|
|
Text Classification (SP)
|
100% |
27
35.9 IPS |
|
|
Text Classification (HP)
|
100% |
27
36.5 IPS |
|
|
Text Classification (Q)
|
91% |
39
52.2 IPS |
|
|
Machine Translation (SP)
|
100% |
49
0.85 IPS |
|
|
Machine Translation (HP)
|
100% |
49
0.84 IPS |
|
|
Machine Translation (Q)
|
57% |
39
0.95 IPS |
