HONOR DNP-NX9
Geekbench AI Score
2040
Single Precision Score
2033
Half Precision Score
3090
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 15 2025 12:24 PM |
| Views | 4 |
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% |
1454
270.5 IPS |
|
|
Image Classification (HP)
|
100% |
1294
240.7 IPS |
|
|
Image Classification (Q)
|
100% |
2377
442.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1784
28.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
1779
28.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
2725
44.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
3255
3.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
3372
3.93 IPS |
|
|
Pose Estimation (Q)
|
84% |
7397
8.77 IPS |
|
|
Object Detection (SP)
|
98% |
1443
114.9 IPS |
|
|
Object Detection (HP)
|
98% |
1607
127.9 IPS |
|
|
Object Detection (Q)
|
83% |
2330
188.2 IPS |
|
|
Face Detection (SP)
|
100% |
3273
38.9 IPS |
|
|
Face Detection (HP)
|
100% |
3251
38.6 IPS |
|
|
Face Detection (Q)
|
95% |
5130
61.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
3277
25.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
3320
25.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
5245
48.0 IPS |
|
|
Style Transfer (SP)
|
89% |
8050
10.5 IPS |
|
|
Style Transfer (HP)
|
89% |
8070
10.5 IPS |
|
|
Style Transfer (Q)
|
98% |
15098
19.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1450
53.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1348
49.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3317
122.9 IPS |
|
|
Text Classification (SP)
|
100% |
623
832.1 IPS |
|
|
Text Classification (HP)
|
99% |
622
829.9 IPS |
|
|
Text Classification (Q)
|
88% |
874
1.18 KIPS |
|
|
Machine Translation (SP)
|
100% |
1315
22.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1325
22.8 IPS |
|
|
Machine Translation (Q)
|
50% |
604
21.5 IPS |
