HONOR DNP-NX9
Geekbench AI Score
2472
Single Precision Score
2460
Half Precision Score
3667
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 13 2025 05:31 AM |
| Views | 2 |
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% |
2255
419.4 IPS |
|
|
Image Classification (HP)
|
100% |
1950
362.7 IPS |
|
|
Image Classification (Q)
|
100% |
2717
505.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2073
33.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2042
33.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
3063
49.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
3796
4.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
3774
4.40 IPS |
|
|
Pose Estimation (Q)
|
84% |
8453
10.0 IPS |
|
|
Object Detection (SP)
|
98% |
1519
120.9 IPS |
|
|
Object Detection (HP)
|
98% |
1909
151.9 IPS |
|
|
Object Detection (Q)
|
83% |
2549
205.9 IPS |
|
|
Face Detection (SP)
|
100% |
3695
43.9 IPS |
|
|
Face Detection (HP)
|
100% |
3693
43.9 IPS |
|
|
Face Detection (Q)
|
95% |
5806
69.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
3760
29.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
3707
28.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
5807
53.2 IPS |
|
|
Style Transfer (SP)
|
89% |
8961
11.6 IPS |
|
|
Style Transfer (HP)
|
89% |
9045
11.7 IPS |
|
|
Style Transfer (Q)
|
98% |
17319
22.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1928
71.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1902
70.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4341
160.9 IPS |
|
|
Text Classification (SP)
|
100% |
807
1.08 KIPS |
|
|
Text Classification (HP)
|
99% |
763
1.02 KIPS |
|
|
Text Classification (Q)
|
88% |
1229
1.66 KIPS |
|
|
Machine Translation (SP)
|
100% |
1632
28.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1580
27.2 IPS |
|
|
Machine Translation (Q)
|
50% |
788
28.0 IPS |
