HONOR DNP-NX9
Geekbench AI Score
2219
Single Precision Score
2222
Half Precision Score
3226
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 15 2025 12:01 PM |
| Views | 7 |
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% |
2040
379.4 IPS |
|
|
Image Classification (HP)
|
100% |
1837
341.7 IPS |
|
|
Image Classification (Q)
|
100% |
2819
524.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2094
33.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2051
33.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2699
43.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
3308
3.86 IPS |
|
|
Pose Estimation (HP)
|
100% |
3325
3.88 IPS |
|
|
Pose Estimation (Q)
|
84% |
7448
8.83 IPS |
|
|
Object Detection (SP)
|
98% |
1452
115.6 IPS |
|
|
Object Detection (HP)
|
98% |
1624
129.2 IPS |
|
|
Object Detection (Q)
|
83% |
2144
173.2 IPS |
|
|
Face Detection (SP)
|
100% |
3156
37.5 IPS |
|
|
Face Detection (HP)
|
100% |
3316
39.4 IPS |
|
|
Face Detection (Q)
|
95% |
5050
60.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
3228
24.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
3163
24.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
5213
47.7 IPS |
|
|
Style Transfer (SP)
|
89% |
7976
10.4 IPS |
|
|
Style Transfer (HP)
|
89% |
9093
11.8 IPS |
|
|
Style Transfer (Q)
|
98% |
14664
18.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1667
61.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1530
56.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3743
138.7 IPS |
|
|
Text Classification (SP)
|
100% |
713
951.9 IPS |
|
|
Text Classification (HP)
|
99% |
663
885.0 IPS |
|
|
Text Classification (Q)
|
88% |
990
1.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
1461
25.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1491
25.7 IPS |
|
|
Machine Translation (Q)
|
50% |
703
25.0 IPS |
