HONOR LGE-NX9
Geekbench AI Score
1061
Single Precision Score
1058
Half Precision Score
2419
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | slavatsarev |
| Upload Date | November 11 2025 02:56 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
553
102.9 IPS |
|
|
Image Classification (HP)
|
100% |
543
101.0 IPS |
|
|
Image Classification (Q)
|
100% |
1980
368.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
620
10.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
628
10.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2180
35.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2195
2.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
2167
2.53 IPS |
|
|
Pose Estimation (Q)
|
84% |
4693
5.57 IPS |
|
|
Object Detection (SP)
|
100% |
433
34.4 IPS |
|
|
Object Detection (HP)
|
100% |
452
35.8 IPS |
|
|
Object Detection (Q)
|
83% |
1616
130.5 IPS |
|
|
Face Detection (SP)
|
100% |
1544
18.3 IPS |
|
|
Face Detection (HP)
|
100% |
1543
18.3 IPS |
|
|
Face Detection (Q)
|
95% |
3891
46.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
2020
15.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2021
15.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
3932
36.0 IPS |
|
|
Style Transfer (SP)
|
89% |
3599
4.67 IPS |
|
|
Style Transfer (HP)
|
89% |
3614
4.69 IPS |
|
|
Style Transfer (Q)
|
98% |
9799
12.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1164
43.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1184
43.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2566
95.1 IPS |
|
|
Text Classification (SP)
|
100% |
563
750.8 IPS |
|
|
Text Classification (HP)
|
100% |
542
723.6 IPS |
|
|
Text Classification (Q)
|
88% |
1046
1.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
759
13.1 IPS |
|
|
Machine Translation (HP)
|
100% |
730
12.6 IPS |
|
|
Machine Translation (Q)
|
50% |
521
18.5 IPS |
