realme RMX3890
Geekbench AI Score
48
Single Precision Score
91
Half Precision Score
89
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | March 19 2025 05:17 PM |
| Views | 14 |
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
6.38 IPS |
|
|
Image Classification (HP)
|
100% |
69
12.8 IPS |
|
|
Image Classification (Q)
|
97% |
70
13.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
31
0.50 IPS |
|
|
Image Segmentation (HP)
|
100% |
95
1.53 IPS |
|
|
Image Segmentation (Q)
|
98% |
86
1.39 IPS |
|
|
Pose Estimation (SP)
|
100% |
58
0.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
107
0.12 IPS |
|
|
Pose Estimation (Q)
|
95% |
104
0.12 IPS |
|
|
Object Detection (SP)
|
100% |
35
2.75 IPS |
|
|
Object Detection (HP)
|
100% |
58
4.58 IPS |
|
|
Object Detection (Q)
|
89% |
56
4.45 IPS |
|
|
Face Detection (SP)
|
100% |
85
1.01 IPS |
|
|
Face Detection (HP)
|
100% |
215
2.56 IPS |
|
|
Face Detection (Q)
|
97% |
219
2.61 IPS |
|
|
Depth Estimation (SP)
|
100% |
80
0.62 IPS |
|
|
Depth Estimation (HP)
|
99% |
165
1.28 IPS |
|
|
Depth Estimation (Q)
|
63% |
134
1.26 IPS |
|
|
Style Transfer (SP)
|
100% |
154
0.20 IPS |
|
|
Style Transfer (HP)
|
100% |
307
0.39 IPS |
|
|
Style Transfer (Q)
|
98% |
306
0.39 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39
1.44 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
81
2.98 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
80
2.96 IPS |
|
|
Text Classification (SP)
|
100% |
23
30.9 IPS |
|
|
Text Classification (HP)
|
100% |
23
31.3 IPS |
|
|
Text Classification (Q)
|
91% |
32
43.3 IPS |
|
|
Machine Translation (SP)
|
100% |
33
0.57 IPS |
|
|
Machine Translation (HP)
|
100% |
49
0.84 IPS |
|
|
Machine Translation (Q)
|
57% |
39
0.96 IPS |
