HONOR JDY-LX3P
Geekbench AI Score
375
Single Precision Score
382
Half Precision Score
744
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 17 2025 11:28 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6769 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR JDY-LX3P |
| Model ID | HONOR JDY-LX3P |
| Motherboard | JDYL |
| CPU Information | |
|---|---|
| Name | ARM MT6769 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 3.67 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
172
32.0 IPS |
|
|
Image Classification (HP)
|
100% |
182
33.8 IPS |
|
|
Image Classification (Q)
|
100% |
522
97.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
222
3.60 IPS |
|
|
Image Segmentation (HP)
|
100% |
223
3.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
633
10.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
846
0.99 IPS |
|
|
Pose Estimation (HP)
|
100% |
849
0.99 IPS |
|
|
Pose Estimation (Q)
|
84% |
1558
1.85 IPS |
|
|
Object Detection (SP)
|
100% |
207
16.5 IPS |
|
|
Object Detection (HP)
|
100% |
206
16.4 IPS |
|
|
Object Detection (Q)
|
83% |
527
42.6 IPS |
|
|
Face Detection (SP)
|
100% |
458
5.44 IPS |
|
|
Face Detection (HP)
|
100% |
460
5.46 IPS |
|
|
Face Detection (Q)
|
95% |
1160
13.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
550
4.24 IPS |
|
|
Depth Estimation (HP)
|
99% |
621
4.79 IPS |
|
|
Depth Estimation (Q)
|
64% |
1377
12.6 IPS |
|
|
Style Transfer (SP)
|
89% |
1762
2.29 IPS |
|
|
Style Transfer (HP)
|
89% |
1763
2.29 IPS |
|
|
Style Transfer (Q)
|
98% |
3415
4.40 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
305
11.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
317
11.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
846
31.3 IPS |
|
|
Text Classification (SP)
|
100% |
200
266.3 IPS |
|
|
Text Classification (HP)
|
100% |
197
263.2 IPS |
|
|
Text Classification (Q)
|
88% |
266
359.4 IPS |
|
|
Machine Translation (SP)
|
100% |
311
5.35 IPS |
|
|
Machine Translation (HP)
|
100% |
298
5.13 IPS |
|
|
Machine Translation (Q)
|
50% |
157
5.56 IPS |
