HONOR LGE-NX9
Geekbench AI Score
835
Single Precision Score
831
Half Precision Score
1761
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 18 2024 01:46 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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% |
424
78.9 IPS |
|
|
Image Classification (HP)
|
100% |
425
79.1 IPS |
|
|
Image Classification (Q)
|
100% |
1538
285.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
556
9.02 IPS |
|
|
Image Segmentation (HP)
|
100% |
561
9.10 IPS |
|
|
Image Segmentation (Q)
|
98% |
1690
27.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2212
2.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
2165
2.53 IPS |
|
|
Pose Estimation (Q)
|
84% |
3577
4.24 IPS |
|
|
Object Detection (SP)
|
100% |
327
25.9 IPS |
|
|
Object Detection (HP)
|
100% |
317
25.1 IPS |
|
|
Object Detection (Q)
|
83% |
1111
89.7 IPS |
|
|
Face Detection (SP)
|
100% |
1172
13.9 IPS |
|
|
Face Detection (HP)
|
100% |
1172
13.9 IPS |
|
|
Face Detection (Q)
|
95% |
2560
30.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1595
12.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
1593
12.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
2815
25.8 IPS |
|
|
Style Transfer (SP)
|
89% |
2718
3.53 IPS |
|
|
Style Transfer (HP)
|
89% |
2718
3.53 IPS |
|
|
Style Transfer (Q)
|
98% |
7290
9.40 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
886
32.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
883
32.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1815
67.3 IPS |
|
|
Text Classification (SP)
|
100% |
359
479.7 IPS |
|
|
Text Classification (HP)
|
100% |
357
476.7 IPS |
|
|
Text Classification (Q)
|
88% |
673
907.4 IPS |
|
|
Machine Translation (SP)
|
100% |
600
10.3 IPS |
|
|
Machine Translation (HP)
|
100% |
604
10.4 IPS |
|
|
Machine Translation (Q)
|
50% |
435
15.4 IPS |
