HONOR LGE-NX9
Geekbench AI Score
1018
Single Precision Score
1026
Half Precision Score
2343
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 05 2025 06:53 PM |
| Views | 2 |
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% |
462
85.8 IPS |
|
|
Image Classification (HP)
|
100% |
496
92.2 IPS |
|
|
Image Classification (Q)
|
100% |
1872
348.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
584
9.47 IPS |
|
|
Image Segmentation (HP)
|
100% |
580
9.40 IPS |
|
|
Image Segmentation (Q)
|
98% |
1992
32.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2193
2.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
2198
2.57 IPS |
|
|
Pose Estimation (Q)
|
84% |
4673
5.54 IPS |
|
|
Object Detection (SP)
|
100% |
429
34.0 IPS |
|
|
Object Detection (HP)
|
100% |
425
33.7 IPS |
|
|
Object Detection (Q)
|
83% |
1552
125.4 IPS |
|
|
Face Detection (SP)
|
100% |
1488
17.7 IPS |
|
|
Face Detection (HP)
|
100% |
1523
18.1 IPS |
|
|
Face Detection (Q)
|
95% |
3765
44.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
2050
15.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
2033
15.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
3831
35.1 IPS |
|
|
Style Transfer (SP)
|
89% |
3549
4.61 IPS |
|
|
Style Transfer (HP)
|
89% |
3513
4.56 IPS |
|
|
Style Transfer (Q)
|
98% |
9803
12.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1134
41.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1142
42.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2446
90.6 IPS |
|
|
Text Classification (SP)
|
100% |
526
701.5 IPS |
|
|
Text Classification (HP)
|
100% |
553
737.9 IPS |
|
|
Text Classification (Q)
|
88% |
1078
1.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
731
12.6 IPS |
|
|
Machine Translation (HP)
|
100% |
706
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
495
17.6 IPS |
