HONOR DNY-NX9
Geekbench AI Score
575
Single Precision Score
608
Half Precision Score
1124
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 12 2025 09:58 PM |
| Views | 11 |
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% |
726
135.0 IPS |
|
|
Image Classification (HP)
|
100% |
702
130.6 IPS |
|
|
Image Classification (Q)
|
100% |
1949
362.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
689
11.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
690
11.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1988
32.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1896
2.21 IPS |
|
|
Pose Estimation (HP)
|
100% |
1915
2.23 IPS |
|
|
Pose Estimation (Q)
|
84% |
2072
2.46 IPS |
|
|
Object Detection (SP)
|
98% |
274
21.8 IPS |
|
|
Object Detection (HP)
|
98% |
370
29.5 IPS |
|
|
Object Detection (Q)
|
83% |
561
45.3 IPS |
|
|
Face Detection (SP)
|
100% |
561
6.66 IPS |
|
|
Face Detection (HP)
|
100% |
568
6.75 IPS |
|
|
Face Detection (Q)
|
95% |
1245
14.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
701
5.42 IPS |
|
|
Depth Estimation (HP)
|
99% |
701
5.41 IPS |
|
|
Depth Estimation (Q)
|
64% |
1449
13.3 IPS |
|
|
Style Transfer (SP)
|
89% |
1654
2.15 IPS |
|
|
Style Transfer (HP)
|
89% |
1663
2.16 IPS |
|
|
Style Transfer (Q)
|
98% |
5241
6.76 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
369
13.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
370
13.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1392
51.6 IPS |
|
|
Text Classification (SP)
|
100% |
180
240.8 IPS |
|
|
Text Classification (HP)
|
99% |
182
243.2 IPS |
|
|
Text Classification (Q)
|
88% |
291
392.5 IPS |
|
|
Machine Translation (SP)
|
100% |
352
6.06 IPS |
|
|
Machine Translation (HP)
|
100% |
458
7.88 IPS |
|
|
Machine Translation (Q)
|
50% |
188
6.66 IPS |
