HONOR LGE-NX9
Geekbench AI Score
286
Single Precision Score
11275
Half Precision Score
29487
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | slavatsarev |
| Upload Date | November 11 2025 03:39 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR LGE-NX9 |
| Model ID | HONOR LGE-NX9 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 7.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
190
35.4 IPS |
|
|
Image Classification (HP)
|
100% |
8391
1.56 KIPS |
|
|
Image Classification (Q)
|
99% |
24350
4.54 KIPS |
|
|
Image Segmentation (SP)
|
100% |
223
3.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
6706
108.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
19426
315.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
265
0.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
37821
44.1 IPS |
|
|
Pose Estimation (Q)
|
94% |
226914
266.0 IPS |
|
|
Object Detection (SP)
|
100% |
172
13.6 IPS |
|
|
Object Detection (HP)
|
100% |
7945
630.2 IPS |
|
|
Object Detection (Q)
|
88% |
12120
970.9 IPS |
|
|
Face Detection (SP)
|
100% |
465
5.52 IPS |
|
|
Face Detection (HP)
|
100% |
18403
218.7 IPS |
|
|
Face Detection (Q)
|
97% |
73584
877.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
370
2.85 IPS |
|
|
Depth Estimation (HP)
|
99% |
28469
220.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
65008
598.5 IPS |
|
|
Style Transfer (SP)
|
100% |
654
0.84 IPS |
|
|
Style Transfer (HP)
|
98% |
40878
52.7 IPS |
|
|
Style Transfer (Q)
|
98% |
220213
284.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
165
6.11 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
21766
803.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
64517
2.39 KIPS |
|
|
Text Classification (SP)
|
100% |
275
367.3 IPS |
|
|
Text Classification (HP)
|
100% |
1895
2.53 KIPS |
|
|
Text Classification (Q)
|
94% |
4465
5.99 KIPS |
|
|
Machine Translation (SP)
|
100% |
384
6.61 IPS |
|
|
Machine Translation (HP)
|
100% |
2223
38.3 IPS |
|
|
Machine Translation (Q)
|
50% |
1259
43.6 IPS |
