HONOR DNP-NX9
Geekbench AI Score
2245
Single Precision Score
2205
Half Precision Score
3195
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 13 2025 05:18 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% |
2076
386.0 IPS |
|
|
Image Classification (HP)
|
100% |
1951
362.7 IPS |
|
|
Image Classification (Q)
|
100% |
1946
361.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1738
28.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1769
28.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
3248
52.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
3903
4.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
3315
3.87 IPS |
|
|
Pose Estimation (Q)
|
84% |
7478
8.87 IPS |
|
|
Object Detection (SP)
|
98% |
1669
132.9 IPS |
|
|
Object Detection (HP)
|
98% |
1659
132.0 IPS |
|
|
Object Detection (Q)
|
83% |
2339
188.9 IPS |
|
|
Face Detection (SP)
|
100% |
3287
39.1 IPS |
|
|
Face Detection (HP)
|
100% |
3250
38.6 IPS |
|
|
Face Detection (Q)
|
95% |
5203
62.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
3076
23.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
3292
25.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
5321
48.7 IPS |
|
|
Style Transfer (SP)
|
89% |
8147
10.6 IPS |
|
|
Style Transfer (HP)
|
89% |
8207
10.7 IPS |
|
|
Style Transfer (Q)
|
98% |
15417
19.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1611
59.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1614
59.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3819
141.5 IPS |
|
|
Text Classification (SP)
|
100% |
682
910.7 IPS |
|
|
Text Classification (HP)
|
99% |
713
952.0 IPS |
|
|
Text Classification (Q)
|
88% |
999
1.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
1532
26.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1421
24.5 IPS |
|
|
Machine Translation (Q)
|
50% |
616
21.9 IPS |
