realme RMX3888
Geekbench AI Score
204
Single Precision Score
200
Half Precision Score
440
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | hass |
| Upload Date | September 12 2024 03:18 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3888 |
| Model ID | realme RMX3888 |
| Motherboard | pineapple |
| Governor | uag |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 10.99 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
118
21.9 IPS |
|
|
Image Classification (HP)
|
100% |
115
21.3 IPS |
|
|
Image Classification (Q)
|
99% |
283
52.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
154
2.49 IPS |
|
|
Image Segmentation (HP)
|
100% |
154
2.49 IPS |
|
|
Image Segmentation (Q)
|
98% |
304
4.94 IPS |
|
|
Pose Estimation (SP)
|
100% |
197
0.23 IPS |
|
|
Pose Estimation (HP)
|
100% |
199
0.23 IPS |
|
|
Pose Estimation (Q)
|
98% |
738
0.86 IPS |
|
|
Object Detection (SP)
|
100% |
116
9.20 IPS |
|
|
Object Detection (HP)
|
100% |
114
9.00 IPS |
|
|
Object Detection (Q)
|
87% |
321
25.8 IPS |
|
|
Face Detection (SP)
|
100% |
342
4.07 IPS |
|
|
Face Detection (HP)
|
100% |
343
4.08 IPS |
|
|
Face Detection (Q)
|
97% |
652
7.78 IPS |
|
|
Depth Estimation (SP)
|
100% |
270
2.08 IPS |
|
|
Depth Estimation (HP)
|
99% |
270
2.08 IPS |
|
|
Depth Estimation (Q)
|
64% |
604
5.48 IPS |
|
|
Style Transfer (SP)
|
100% |
487
0.63 IPS |
|
|
Style Transfer (HP)
|
100% |
487
0.63 IPS |
|
|
Style Transfer (Q)
|
98% |
1339
1.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
128
4.72 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
128
4.74 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
435
16.1 IPS |
|
|
Text Classification (SP)
|
100% |
188
250.5 IPS |
|
|
Text Classification (HP)
|
100% |
157
210.1 IPS |
|
|
Text Classification (Q)
|
91% |
255
343.2 IPS |
|
|
Machine Translation (SP)
|
100% |
283
4.88 IPS |
|
|
Machine Translation (HP)
|
100% |
284
4.89 IPS |
|
|
Machine Translation (Q)
|
57% |
233
5.70 IPS |
