realme RMX3709
Geekbench AI Score
280
Single Precision Score
280
Half Precision Score
682
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | March 30 2025 11:01 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | realme RMX3709 |
| Model ID | realme RMX3709 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 10.95 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
158
29.5 IPS |
|
|
Image Classification (HP)
|
100% |
160
29.7 IPS |
|
|
Image Classification (Q)
|
99% |
462
86.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
212
3.44 IPS |
|
|
Image Segmentation (HP)
|
100% |
212
3.43 IPS |
|
|
Image Segmentation (Q)
|
98% |
489
7.95 IPS |
|
|
Pose Estimation (SP)
|
100% |
287
0.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
286
0.33 IPS |
|
|
Pose Estimation (Q)
|
98% |
1127
1.32 IPS |
|
|
Object Detection (SP)
|
100% |
161
12.7 IPS |
|
|
Object Detection (HP)
|
100% |
160
12.7 IPS |
|
|
Object Detection (Q)
|
87% |
485
38.9 IPS |
|
|
Face Detection (SP)
|
100% |
450
5.34 IPS |
|
|
Face Detection (HP)
|
100% |
453
5.38 IPS |
|
|
Face Detection (Q)
|
97% |
1068
12.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
374
2.88 IPS |
|
|
Depth Estimation (HP)
|
99% |
377
2.90 IPS |
|
|
Depth Estimation (Q)
|
64% |
925
8.39 IPS |
|
|
Style Transfer (SP)
|
100% |
649
0.83 IPS |
|
|
Style Transfer (HP)
|
100% |
649
0.83 IPS |
|
|
Style Transfer (Q)
|
98% |
1658
2.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
183
6.76 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
182
6.74 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
664
24.6 IPS |
|
|
Text Classification (SP)
|
100% |
241
321.6 IPS |
|
|
Text Classification (HP)
|
100% |
233
310.9 IPS |
|
|
Text Classification (Q)
|
91% |
468
628.9 IPS |
|
|
Machine Translation (SP)
|
100% |
405
6.97 IPS |
|
|
Machine Translation (HP)
|
100% |
408
7.03 IPS |
|
|
Machine Translation (Q)
|
57% |
350
8.55 IPS |
