HONOR DNP-NX9
Geekbench AI Score
1413
Single Precision Score
1012
Half Precision Score
2242
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | September 16 2025 01:19 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR DNP-NX9 |
| Model ID | HONOR DNP-NX9 |
| Motherboard | DNP |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.04 GHz |
| Cluster 1 | 2 Cores @ 2.04 GHz |
| Cluster 2 | 5 Cores @ 2.96 GHz |
| Cluster 3 | 1 Core @ 3.05 GHz |
| Memory Information | |
|---|---|
| Size | 11.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
869
161.6 IPS |
|
|
Image Classification (HP)
|
100% |
425
79.1 IPS |
|
|
Image Classification (Q)
|
100% |
1090
202.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
795
12.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
719
11.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
2162
35.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2063
2.41 IPS |
|
|
Pose Estimation (HP)
|
100% |
2032
2.37 IPS |
|
|
Pose Estimation (Q)
|
84% |
6204
7.36 IPS |
|
|
Object Detection (SP)
|
98% |
1362
108.4 IPS |
|
|
Object Detection (HP)
|
98% |
740
58.9 IPS |
|
|
Object Detection (Q)
|
83% |
1355
109.4 IPS |
|
|
Face Detection (SP)
|
100% |
2298
27.3 IPS |
|
|
Face Detection (HP)
|
100% |
889
10.6 IPS |
|
|
Face Detection (Q)
|
95% |
1818
21.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
2395
18.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
1730
13.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
2897
26.5 IPS |
|
|
Style Transfer (SP)
|
89% |
5107
6.63 IPS |
|
|
Style Transfer (HP)
|
89% |
4315
5.60 IPS |
|
|
Style Transfer (Q)
|
98% |
12168
15.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1077
39.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1025
37.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3698
137.0 IPS |
|
|
Text Classification (SP)
|
100% |
594
793.4 IPS |
|
|
Text Classification (HP)
|
99% |
436
582.3 IPS |
|
|
Text Classification (Q)
|
88% |
1058
1.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
914
15.7 IPS |
|
|
Machine Translation (HP)
|
100% |
827
14.2 IPS |
|
|
Machine Translation (Q)
|
50% |
647
23.0 IPS |
