HONOR DNY-NX9
Geekbench AI Score
837
Single Precision Score
836
Half Precision Score
1894
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 16 2025 09:40 PM |
| Views | 1 |
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% |
619
115.1 IPS |
|
|
Image Classification (HP)
|
100% |
639
118.9 IPS |
|
|
Image Classification (Q)
|
100% |
1475
274.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
719
11.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
722
11.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
1986
32.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1619
1.89 IPS |
|
|
Pose Estimation (HP)
|
100% |
1888
2.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
5162
6.12 IPS |
|
|
Object Detection (SP)
|
98% |
686
54.6 IPS |
|
|
Object Detection (HP)
|
98% |
589
46.9 IPS |
|
|
Object Detection (Q)
|
83% |
1537
124.2 IPS |
|
|
Face Detection (SP)
|
100% |
957
11.4 IPS |
|
|
Face Detection (HP)
|
100% |
980
11.6 IPS |
|
|
Face Detection (Q)
|
95% |
3669
43.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
1429
11.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
1422
11.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
3925
36.0 IPS |
|
|
Style Transfer (SP)
|
89% |
4323
5.61 IPS |
|
|
Style Transfer (HP)
|
89% |
4255
5.52 IPS |
|
|
Style Transfer (Q)
|
98% |
12179
15.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
482
17.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
487
18.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1393
51.6 IPS |
|
|
Text Classification (SP)
|
100% |
258
345.0 IPS |
|
|
Text Classification (HP)
|
99% |
256
342.2 IPS |
|
|
Text Classification (Q)
|
88% |
429
578.8 IPS |
|
|
Machine Translation (SP)
|
100% |
468
8.05 IPS |
|
|
Machine Translation (HP)
|
100% |
444
7.65 IPS |
|
|
Machine Translation (Q)
|
50% |
244
8.66 IPS |
