HONOR DNY-NX9
Geekbench AI Score
612
Single Precision Score
851
Half Precision Score
1189
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | kasid |
| Upload Date | February 16 2026 04:26 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | HONOR DNY-NX9 |
| Model ID | HONOR DNY-NX9 |
| Motherboard | crow |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.63 GHz |
| Memory Information | |
|---|---|
| Size | 11.12 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
707
131.5 IPS |
|
|
Image Classification (HP)
|
100% |
590
109.8 IPS |
|
|
Image Classification (Q)
|
99% |
812
151.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
376
6.09 IPS |
|
|
Image Segmentation (HP)
|
100% |
489
7.93 IPS |
|
|
Image Segmentation (Q)
|
98% |
807
13.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1190
1.39 IPS |
|
|
Pose Estimation (HP)
|
91% |
2195
2.58 IPS |
|
|
Pose Estimation (Q)
|
96% |
2590
3.03 IPS |
|
|
Object Detection (SP)
|
98% |
357
28.4 IPS |
|
|
Object Detection (HP)
|
97% |
515
41.0 IPS |
|
|
Object Detection (Q)
|
85% |
796
64.1 IPS |
|
|
Face Detection (SP)
|
100% |
649
7.71 IPS |
|
|
Face Detection (HP)
|
100% |
949
11.3 IPS |
|
|
Face Detection (Q)
|
97% |
1737
20.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
842
6.51 IPS |
|
|
Depth Estimation (HP)
|
98% |
1552
12.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
2096
19.3 IPS |
|
|
Style Transfer (SP)
|
89% |
2226
2.89 IPS |
|
|
Style Transfer (HP)
|
88% |
2613
3.39 IPS |
|
|
Style Transfer (Q)
|
98% |
5313
6.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
463
17.1 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
901
33.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1434
53.1 IPS |
|
|
Text Classification (SP)
|
100% |
258
344.0 IPS |
|
|
Text Classification (HP)
|
99% |
375
500.7 IPS |
|
|
Text Classification (Q)
|
93% |
434
583.3 IPS |
|
|
Machine Translation (SP)
|
100% |
451
7.78 IPS |
|
|
Machine Translation (HP)
|
100% |
472
8.13 IPS |
|
|
Machine Translation (Q)
|
55% |
350
9.40 IPS |
