HONOR LGE-NX9
Geekbench AI Score
233
Single Precision Score
11006
Half Precision Score
28248
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | slavatsarev |
| Upload Date | January 03 2025 05:59 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| 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% |
137
25.5 IPS |
|
|
Image Classification (HP)
|
100% |
8094
1.51 KIPS |
|
|
Image Classification (Q)
|
99% |
22625
4.22 KIPS |
|
|
Image Segmentation (SP)
|
100% |
178
2.88 IPS |
|
|
Image Segmentation (HP)
|
100% |
6461
104.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
18458
300.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
247
0.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
38028
44.4 IPS |
|
|
Pose Estimation (Q)
|
94% |
224546
263.3 IPS |
|
|
Object Detection (SP)
|
100% |
136
10.8 IPS |
|
|
Object Detection (HP)
|
100% |
7641
606.1 IPS |
|
|
Object Detection (Q)
|
88% |
11547
925.0 IPS |
|
|
Face Detection (SP)
|
100% |
357
4.24 IPS |
|
|
Face Detection (HP)
|
100% |
17601
209.1 IPS |
|
|
Face Detection (Q)
|
97% |
66129
788.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
309
2.38 IPS |
|
|
Depth Estimation (HP)
|
99% |
27950
215.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
63125
581.1 IPS |
|
|
Style Transfer (SP)
|
100% |
540
0.69 IPS |
|
|
Style Transfer (HP)
|
98% |
40617
52.4 IPS |
|
|
Style Transfer (Q)
|
98% |
219874
283.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
153
5.67 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
21364
788.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
61823
2.29 KIPS |
|
|
Text Classification (SP)
|
100% |
198
264.8 IPS |
|
|
Text Classification (HP)
|
100% |
1885
2.52 KIPS |
|
|
Text Classification (Q)
|
94% |
4441
5.96 KIPS |
|
|
Machine Translation (SP)
|
100% |
329
5.67 IPS |
|
|
Machine Translation (HP)
|
100% |
2133
36.7 IPS |
|
|
Machine Translation (Q)
|
50% |
1186
41.1 IPS |
