HONOR DNP-NX9
Geekbench AI Score
1953
Single Precision Score
1545
Half Precision Score
2522
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 19 2025 11:43 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% |
1691
314.4 IPS |
|
|
Image Classification (HP)
|
100% |
1598
297.1 IPS |
|
|
Image Classification (Q)
|
100% |
1265
235.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1756
28.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1771
28.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
2749
44.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
3315
3.87 IPS |
|
|
Pose Estimation (HP)
|
100% |
3313
3.87 IPS |
|
|
Pose Estimation (Q)
|
84% |
7471
8.86 IPS |
|
|
Object Detection (SP)
|
98% |
1470
117.0 IPS |
|
|
Object Detection (HP)
|
98% |
692
55.1 IPS |
|
|
Object Detection (Q)
|
83% |
1351
109.1 IPS |
|
|
Face Detection (SP)
|
100% |
3054
36.3 IPS |
|
|
Face Detection (HP)
|
100% |
1413
16.8 IPS |
|
|
Face Detection (Q)
|
95% |
2683
32.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
3218
24.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
3240
25.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
5245
48.0 IPS |
|
|
Style Transfer (SP)
|
89% |
8059
10.5 IPS |
|
|
Style Transfer (HP)
|
89% |
3808
4.94 IPS |
|
|
Style Transfer (Q)
|
98% |
7418
9.57 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
871
32.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
861
31.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3693
136.9 IPS |
|
|
Text Classification (SP)
|
100% |
526
701.8 IPS |
|
|
Text Classification (HP)
|
99% |
697
930.5 IPS |
|
|
Text Classification (Q)
|
88% |
1082
1.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
1538
26.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1142
19.7 IPS |
|
|
Machine Translation (Q)
|
50% |
712
25.3 IPS |
