HONOR DNY-NX9
Geekbench AI Score
643
Single Precision Score
653
Half Precision Score
1267
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 31 2025 08:10 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR DNY-NX9 |
| Model ID | HONOR DNY-NX9 |
| Motherboard | crow |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.63 GHz |
| Memory Information | |
|---|---|
| Size | 7.23 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
744
138.4 IPS |
|
|
Image Classification (HP)
|
100% |
722
134.3 IPS |
|
|
Image Classification (Q)
|
100% |
1742
323.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
673
10.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
677
11.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
1816
29.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1900
2.22 IPS |
|
|
Pose Estimation (HP)
|
100% |
1850
2.16 IPS |
|
|
Pose Estimation (Q)
|
84% |
5343
6.34 IPS |
|
|
Object Detection (SP)
|
98% |
683
54.3 IPS |
|
|
Object Detection (HP)
|
98% |
668
53.2 IPS |
|
|
Object Detection (Q)
|
83% |
1673
135.1 IPS |
|
|
Face Detection (SP)
|
100% |
546
6.49 IPS |
|
|
Face Detection (HP)
|
100% |
678
8.05 IPS |
|
|
Face Detection (Q)
|
95% |
1255
15.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
694
5.36 IPS |
|
|
Depth Estimation (HP)
|
99% |
704
5.44 IPS |
|
|
Depth Estimation (Q)
|
64% |
1489
13.6 IPS |
|
|
Style Transfer (SP)
|
89% |
1645
2.14 IPS |
|
|
Style Transfer (HP)
|
89% |
1644
2.13 IPS |
|
|
Style Transfer (Q)
|
98% |
3747
4.83 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
464
17.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
370
13.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
974
36.1 IPS |
|
|
Text Classification (SP)
|
100% |
183
243.7 IPS |
|
|
Text Classification (HP)
|
99% |
179
239.5 IPS |
|
|
Text Classification (Q)
|
88% |
296
399.1 IPS |
|
|
Machine Translation (SP)
|
100% |
354
6.09 IPS |
|
|
Machine Translation (HP)
|
100% |
451
7.77 IPS |
|
|
Machine Translation (Q)
|
50% |
188
6.69 IPS |
