HONOR DNP-NX9
Geekbench AI Score
2288
Single Precision Score
2178
Half Precision Score
3322
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 01 2025 03:57 PM |
| Views | 3 |
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% |
2010
373.9 IPS |
|
|
Image Classification (HP)
|
100% |
1808
336.2 IPS |
|
|
Image Classification (Q)
|
100% |
2824
525.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2096
34.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2139
34.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
3180
51.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
3884
4.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
3328
3.88 IPS |
|
|
Pose Estimation (Q)
|
84% |
7471
8.86 IPS |
|
|
Object Detection (SP)
|
98% |
1669
132.9 IPS |
|
|
Object Detection (HP)
|
98% |
1499
119.2 IPS |
|
|
Object Detection (Q)
|
83% |
2368
191.3 IPS |
|
|
Face Detection (SP)
|
100% |
3156
37.5 IPS |
|
|
Face Detection (HP)
|
100% |
3270
38.9 IPS |
|
|
Face Detection (Q)
|
95% |
5142
61.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
3231
25.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3333
25.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
5169
47.3 IPS |
|
|
Style Transfer (SP)
|
89% |
7999
10.4 IPS |
|
|
Style Transfer (HP)
|
89% |
8119
10.5 IPS |
|
|
Style Transfer (Q)
|
98% |
15067
19.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1681
62.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1612
59.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3799
140.8 IPS |
|
|
Text Classification (SP)
|
100% |
707
943.4 IPS |
|
|
Text Classification (HP)
|
99% |
704
940.0 IPS |
|
|
Text Classification (Q)
|
88% |
993
1.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
1488
25.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1242
21.4 IPS |
|
|
Machine Translation (Q)
|
50% |
683
24.2 IPS |
