HONOR DNP-NX9
Geekbench AI Score
1020
Single Precision Score
1495
Half Precision Score
1460
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 21 2025 10:47 AM |
| Views | 4 |
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% |
695
129.2 IPS |
|
|
Image Classification (HP)
|
100% |
686
127.5 IPS |
|
|
Image Classification (Q)
|
96% |
671
125.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1112
18.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1182
19.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1071
17.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
998
1.17 IPS |
|
|
Pose Estimation (HP)
|
100% |
2163
2.52 IPS |
|
|
Pose Estimation (Q)
|
96% |
2152
2.52 IPS |
|
|
Object Detection (SP)
|
100% |
616
48.9 IPS |
|
|
Object Detection (HP)
|
100% |
921
73.0 IPS |
|
|
Object Detection (Q)
|
87% |
721
57.9 IPS |
|
|
Face Detection (SP)
|
100% |
2340
27.8 IPS |
|
|
Face Detection (HP)
|
100% |
3149
37.4 IPS |
|
|
Face Detection (Q)
|
97% |
3234
38.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1590
12.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3208
24.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
2673
24.8 IPS |
|
|
Style Transfer (SP)
|
100% |
5735
7.37 IPS |
|
|
Style Transfer (HP)
|
100% |
9332
12.0 IPS |
|
|
Style Transfer (Q)
|
98% |
9172
11.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
429
15.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1308
48.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1271
47.1 IPS |
|
|
Text Classification (SP)
|
100% |
431
575.2 IPS |
|
|
Text Classification (HP)
|
100% |
434
578.8 IPS |
|
|
Text Classification (Q)
|
91% |
715
960.5 IPS |
|
|
Machine Translation (SP)
|
100% |
653
11.2 IPS |
|
|
Machine Translation (HP)
|
100% |
649
11.2 IPS |
|
|
Machine Translation (Q)
|
57% |
551
13.5 IPS |
