HONOR DNP-NX9
Geekbench AI Score
2563
Single Precision Score
2536
Half Precision Score
3717
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 01 2025 03:25 PM |
| Views | 6 |
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% |
2020
375.7 IPS |
|
|
Image Classification (HP)
|
100% |
1825
339.4 IPS |
|
|
Image Classification (Q)
|
100% |
2797
520.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2084
33.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2092
33.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
3144
51.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
3886
4.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
3833
4.47 IPS |
|
|
Pose Estimation (Q)
|
84% |
8552
10.1 IPS |
|
|
Object Detection (SP)
|
98% |
1936
154.1 IPS |
|
|
Object Detection (HP)
|
98% |
1951
155.2 IPS |
|
|
Object Detection (Q)
|
83% |
2458
198.5 IPS |
|
|
Face Detection (SP)
|
100% |
3823
45.4 IPS |
|
|
Face Detection (HP)
|
100% |
3801
45.2 IPS |
|
|
Face Detection (Q)
|
95% |
6004
71.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
3884
30.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3894
30.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
6010
55.0 IPS |
|
|
Style Transfer (SP)
|
89% |
9194
11.9 IPS |
|
|
Style Transfer (HP)
|
89% |
9183
11.9 IPS |
|
|
Style Transfer (Q)
|
98% |
17604
22.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2046
75.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1996
73.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4480
166.0 IPS |
|
|
Text Classification (SP)
|
100% |
827
1.10 KIPS |
|
|
Text Classification (HP)
|
99% |
833
1.11 KIPS |
|
|
Text Classification (Q)
|
88% |
1156
1.56 KIPS |
|
|
Machine Translation (SP)
|
100% |
1675
28.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1706
29.4 IPS |
|
|
Machine Translation (Q)
|
50% |
829
29.4 IPS |
