HONOR JDY-LX2
Geekbench AI Score
220
Single Precision Score
220
Half Precision Score
284
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 02 2025 12:42 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6769V/CZ |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR JDY-LX2 |
| Model ID | HONOR JDY-LX2 |
| Motherboard | JDYL |
| CPU Information | |
|---|---|
| Name | ARM MT6769V/CZ |
| 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 | 5.63 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
104
19.3 IPS |
|
|
Image Classification (HP)
|
100% |
105
19.6 IPS |
|
|
Image Classification (Q)
|
100% |
218
40.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
133
2.15 IPS |
|
|
Image Segmentation (HP)
|
100% |
132
2.14 IPS |
|
|
Image Segmentation (Q)
|
98% |
272
4.43 IPS |
|
|
Pose Estimation (SP)
|
100% |
523
0.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
526
0.61 IPS |
|
|
Pose Estimation (Q)
|
84% |
418
0.50 IPS |
|
|
Object Detection (SP)
|
100% |
105
8.35 IPS |
|
|
Object Detection (HP)
|
100% |
105
8.32 IPS |
|
|
Object Detection (Q)
|
83% |
212
17.1 IPS |
|
|
Face Detection (SP)
|
100% |
341
4.05 IPS |
|
|
Face Detection (HP)
|
100% |
340
4.04 IPS |
|
|
Face Detection (Q)
|
95% |
603
7.19 IPS |
|
|
Depth Estimation (SP)
|
100% |
375
2.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
375
2.89 IPS |
|
|
Depth Estimation (Q)
|
64% |
362
3.32 IPS |
|
|
Style Transfer (SP)
|
89% |
717
0.93 IPS |
|
|
Style Transfer (HP)
|
89% |
717
0.93 IPS |
|
|
Style Transfer (Q)
|
98% |
827
1.07 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
202
7.46 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
202
7.45 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
199
7.39 IPS |
|
|
Text Classification (SP)
|
100% |
100
133.9 IPS |
|
|
Text Classification (HP)
|
100% |
100
133.5 IPS |
|
|
Text Classification (Q)
|
88% |
154
207.6 IPS |
|
|
Machine Translation (SP)
|
100% |
190
3.27 IPS |
|
|
Machine Translation (HP)
|
100% |
188
3.24 IPS |
|
|
Machine Translation (Q)
|
50% |
120
4.28 IPS |
