HONOR DNY-NX9
Geekbench AI Score
376
Single Precision Score
559
Half Precision Score
510
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 13 2025 01:11 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 7.23 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
321
59.6 IPS |
|
|
Image Classification (HP)
|
100% |
403
75.0 IPS |
|
|
Image Classification (Q)
|
96% |
347
64.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
553
8.96 IPS |
|
|
Image Segmentation (HP)
|
100% |
868
14.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
673
10.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
349
0.41 IPS |
|
|
Pose Estimation (HP)
|
100% |
737
0.86 IPS |
|
|
Pose Estimation (Q)
|
96% |
734
0.86 IPS |
|
|
Object Detection (SP)
|
100% |
247
19.6 IPS |
|
|
Object Detection (HP)
|
100% |
360
28.6 IPS |
|
|
Object Detection (Q)
|
87% |
362
29.0 IPS |
|
|
Face Detection (SP)
|
100% |
1005
11.9 IPS |
|
|
Face Detection (HP)
|
100% |
1452
17.3 IPS |
|
|
Face Detection (Q)
|
97% |
1238
14.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
675
5.20 IPS |
|
|
Depth Estimation (HP)
|
99% |
1295
10.0 IPS |
|
|
Depth Estimation (Q)
|
63% |
1067
9.89 IPS |
|
|
Style Transfer (SP)
|
100% |
1678
2.16 IPS |
|
|
Style Transfer (HP)
|
100% |
3685
4.74 IPS |
|
|
Style Transfer (Q)
|
98% |
3627
4.68 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
209
7.73 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
299
11.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
293
10.9 IPS |
|
|
Text Classification (SP)
|
100% |
95
126.2 IPS |
|
|
Text Classification (HP)
|
100% |
94
126.0 IPS |
|
|
Text Classification (Q)
|
91% |
132
177.5 IPS |
|
|
Machine Translation (SP)
|
100% |
165
2.85 IPS |
|
|
Machine Translation (HP)
|
100% |
167
2.87 IPS |
|
|
Machine Translation (Q)
|
57% |
105
2.57 IPS |
