HONOR DNP-NX9
Geekbench AI Score
1956
Single Precision Score
1930
Half Precision Score
2808
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 12 2025 11:41 AM |
| Views | 1 |
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% |
2013
374.4 IPS |
|
|
Image Classification (HP)
|
100% |
1683
312.9 IPS |
|
|
Image Classification (Q)
|
100% |
2203
409.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1256
20.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1206
19.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
1884
30.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
3262
3.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
3258
3.80 IPS |
|
|
Pose Estimation (Q)
|
84% |
6589
7.81 IPS |
|
|
Object Detection (SP)
|
98% |
1304
103.8 IPS |
|
|
Object Detection (HP)
|
98% |
1410
112.2 IPS |
|
|
Object Detection (Q)
|
83% |
2049
165.5 IPS |
|
|
Face Detection (SP)
|
100% |
2882
34.2 IPS |
|
|
Face Detection (HP)
|
100% |
2923
34.7 IPS |
|
|
Face Detection (Q)
|
95% |
4430
52.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
2910
22.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
2897
22.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
4587
42.0 IPS |
|
|
Style Transfer (SP)
|
89% |
7185
9.33 IPS |
|
|
Style Transfer (HP)
|
89% |
7192
9.34 IPS |
|
|
Style Transfer (Q)
|
98% |
13548
17.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1475
54.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1483
54.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3349
124.1 IPS |
|
|
Text Classification (SP)
|
100% |
630
840.7 IPS |
|
|
Text Classification (HP)
|
99% |
627
836.9 IPS |
|
|
Text Classification (Q)
|
88% |
950
1.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
1365
23.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1363
23.5 IPS |
|
|
Machine Translation (Q)
|
50% |
622
22.1 IPS |
