HONOR DNP-NX9
Geekbench AI Score
1705
Single Precision Score
2015
Half Precision Score
2683
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | September 17 2025 12:12 PM |
| Views | 3 |
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% |
1644
305.7 IPS |
|
|
Image Classification (HP)
|
100% |
2078
386.4 IPS |
|
|
Image Classification (Q)
|
100% |
2624
488.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2082
33.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2053
33.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
3156
51.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2488
2.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
3714
4.33 IPS |
|
|
Pose Estimation (Q)
|
84% |
7363
8.73 IPS |
|
|
Object Detection (SP)
|
98% |
1422
113.1 IPS |
|
|
Object Detection (HP)
|
98% |
1411
112.3 IPS |
|
|
Object Detection (Q)
|
83% |
2130
172.0 IPS |
|
|
Face Detection (SP)
|
100% |
1319
15.7 IPS |
|
|
Face Detection (HP)
|
100% |
1270
15.1 IPS |
|
|
Face Detection (Q)
|
95% |
2658
31.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
3205
24.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
3293
25.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
3046
27.9 IPS |
|
|
Style Transfer (SP)
|
89% |
7997
10.4 IPS |
|
|
Style Transfer (HP)
|
89% |
7609
9.88 IPS |
|
|
Style Transfer (Q)
|
98% |
6660
8.59 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1543
57.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1489
55.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3750
138.9 IPS |
|
|
Text Classification (SP)
|
100% |
381
508.6 IPS |
|
|
Text Classification (HP)
|
99% |
709
946.5 IPS |
|
|
Text Classification (Q)
|
88% |
1081
1.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
866
14.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1475
25.4 IPS |
|
|
Machine Translation (Q)
|
50% |
682
24.2 IPS |
