HONOR LGE-NX9
Geekbench AI Score
646
Single Precision Score
900
Half Precision Score
894
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | slavatsarev |
| Upload Date | January 03 2025 05:34 PM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
452
84.1 IPS |
|
|
Image Classification (HP)
|
100% |
488
90.7 IPS |
|
|
Image Classification (Q)
|
97% |
374
69.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
975
15.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1238
20.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1085
17.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
713
0.83 IPS |
|
|
Pose Estimation (HP)
|
100% |
1276
1.49 IPS |
|
|
Pose Estimation (Q)
|
95% |
1284
1.50 IPS |
|
|
Object Detection (SP)
|
100% |
389
30.8 IPS |
|
|
Object Detection (HP)
|
100% |
655
52.0 IPS |
|
|
Object Detection (Q)
|
89% |
659
52.7 IPS |
|
|
Face Detection (SP)
|
100% |
1440
17.1 IPS |
|
|
Face Detection (HP)
|
100% |
1488
17.7 IPS |
|
|
Face Detection (Q)
|
97% |
1606
19.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1102
8.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
2411
18.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
1983
18.6 IPS |
|
|
Style Transfer (SP)
|
100% |
2729
3.51 IPS |
|
|
Style Transfer (HP)
|
100% |
6038
7.76 IPS |
|
|
Style Transfer (Q)
|
98% |
6072
7.83 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
371
13.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
491
18.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
480
17.8 IPS |
|
|
Text Classification (SP)
|
100% |
199
265.7 IPS |
|
|
Text Classification (HP)
|
100% |
199
266.1 IPS |
|
|
Text Classification (Q)
|
91% |
354
475.9 IPS |
|
|
Machine Translation (SP)
|
100% |
327
5.64 IPS |
|
|
Machine Translation (HP)
|
100% |
329
5.67 IPS |
|
|
Machine Translation (Q)
|
57% |
290
7.08 IPS |
