HONOR ELP-NX9
Geekbench AI Score
396
Single Precision Score
397
Half Precision Score
913
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 21 2024 11:57 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR ELP-NX9 |
| Model ID | HONOR ELP-NX9 |
| Motherboard | ELP |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.01 GHz |
| Memory Information | |
|---|---|
| Size | 11.04 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
247
45.9 IPS |
|
|
Image Classification (HP)
|
100% |
243
45.2 IPS |
|
|
Image Classification (Q)
|
99% |
626
116.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
303
4.91 IPS |
|
|
Image Segmentation (HP)
|
100% |
307
4.98 IPS |
|
|
Image Segmentation (Q)
|
98% |
631
10.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
408
0.48 IPS |
|
|
Pose Estimation (HP)
|
100% |
411
0.48 IPS |
|
|
Pose Estimation (Q)
|
98% |
1618
1.89 IPS |
|
|
Object Detection (SP)
|
100% |
234
18.6 IPS |
|
|
Object Detection (HP)
|
100% |
236
18.7 IPS |
|
|
Object Detection (Q)
|
87% |
675
54.1 IPS |
|
|
Face Detection (SP)
|
100% |
571
6.78 IPS |
|
|
Face Detection (HP)
|
100% |
576
6.85 IPS |
|
|
Face Detection (Q)
|
97% |
1343
16.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
496
3.82 IPS |
|
|
Depth Estimation (HP)
|
99% |
501
3.86 IPS |
|
|
Depth Estimation (Q)
|
64% |
1153
10.5 IPS |
|
|
Style Transfer (SP)
|
100% |
846
1.09 IPS |
|
|
Style Transfer (HP)
|
100% |
844
1.08 IPS |
|
|
Style Transfer (Q)
|
98% |
2106
2.72 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
260
9.60 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
260
9.60 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
931
34.5 IPS |
|
|
Text Classification (SP)
|
100% |
376
502.1 IPS |
|
|
Text Classification (HP)
|
100% |
377
502.9 IPS |
|
|
Text Classification (Q)
|
91% |
648
870.7 IPS |
|
|
Machine Translation (SP)
|
100% |
568
9.79 IPS |
|
|
Machine Translation (HP)
|
100% |
563
9.71 IPS |
|
|
Machine Translation (Q)
|
57% |
475
11.6 IPS |
