HONOR DNP-NX9
Geekbench AI Score
1048
Single Precision Score
1479
Half Precision Score
1424
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 21 2025 10:24 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
749
139.3 IPS |
|
|
Image Classification (HP)
|
100% |
693
128.9 IPS |
|
|
Image Classification (Q)
|
96% |
662
123.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1179
19.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1160
18.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1113
18.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1022
1.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
2157
2.52 IPS |
|
|
Pose Estimation (Q)
|
96% |
2148
2.52 IPS |
|
|
Object Detection (SP)
|
100% |
584
46.4 IPS |
|
|
Object Detection (HP)
|
100% |
941
74.6 IPS |
|
|
Object Detection (Q)
|
87% |
914
73.4 IPS |
|
|
Face Detection (SP)
|
100% |
2431
28.9 IPS |
|
|
Face Detection (HP)
|
100% |
2370
28.2 IPS |
|
|
Face Detection (Q)
|
97% |
1720
20.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
1564
12.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3276
25.3 IPS |
|
|
Depth Estimation (Q)
|
63% |
2721
25.2 IPS |
|
|
Style Transfer (SP)
|
100% |
5740
7.38 IPS |
|
|
Style Transfer (HP)
|
100% |
9320
12.0 IPS |
|
|
Style Transfer (Q)
|
98% |
9181
11.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
430
15.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1317
48.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1291
47.8 IPS |
|
|
Text Classification (SP)
|
100% |
457
610.0 IPS |
|
|
Text Classification (HP)
|
100% |
457
610.4 IPS |
|
|
Text Classification (Q)
|
91% |
717
963.4 IPS |
|
|
Machine Translation (SP)
|
100% |
712
12.3 IPS |
|
|
Machine Translation (HP)
|
100% |
705
12.1 IPS |
|
|
Machine Translation (Q)
|
57% |
596
14.6 IPS |
