realme RMX3709
Geekbench AI Score
280
Single Precision Score
281
Half Precision Score
685
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 13 2025 05:56 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
29.4 IPS |
|
|
Image Classification (HP)
|
100% |
158
29.4 IPS |
|
|
Image Classification (Q)
|
99% |
446
83.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
210
3.40 IPS |
|
|
Image Segmentation (HP)
|
100% |
210
3.41 IPS |
|
|
Image Segmentation (Q)
|
98% |
590
9.59 IPS |
|
|
Pose Estimation (SP)
|
100% |
295
0.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
293
0.34 IPS |
|
|
Pose Estimation (Q)
|
98% |
1134
1.33 IPS |
|
|
Object Detection (SP)
|
100% |
163
12.9 IPS |
|
|
Object Detection (HP)
|
100% |
163
12.9 IPS |
|
|
Object Detection (Q)
|
87% |
476
38.2 IPS |
|
|
Face Detection (SP)
|
100% |
448
5.32 IPS |
|
|
Face Detection (HP)
|
100% |
451
5.35 IPS |
|
|
Face Detection (Q)
|
97% |
1056
12.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
375
2.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
379
2.92 IPS |
|
|
Depth Estimation (Q)
|
64% |
912
8.28 IPS |
|
|
Style Transfer (SP)
|
100% |
652
0.84 IPS |
|
|
Style Transfer (HP)
|
100% |
653
0.84 IPS |
|
|
Style Transfer (Q)
|
98% |
1625
2.10 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
183
6.74 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
183
6.75 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
647
24.0 IPS |
|
|
Text Classification (SP)
|
100% |
237
316.1 IPS |
|
|
Text Classification (HP)
|
100% |
238
317.3 IPS |
|
|
Text Classification (Q)
|
91% |
456
613.4 IPS |
|
|
Machine Translation (SP)
|
100% |
400
6.89 IPS |
|
|
Machine Translation (HP)
|
100% |
406
6.99 IPS |
|
|
Machine Translation (Q)
|
57% |
350
8.54 IPS |
