HONOR ELP-NX9
Geekbench AI Score
727
Single Precision Score
975
Half Precision Score
927
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 12 2025 12:41 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
550
102.3 IPS |
|
|
Image Classification (HP)
|
100% |
510
94.8 IPS |
|
|
Image Classification (Q)
|
96% |
482
90.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
739
12.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1110
18.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
781
12.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
801
0.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
1375
1.60 IPS |
|
|
Pose Estimation (Q)
|
96% |
1366
1.60 IPS |
|
|
Object Detection (SP)
|
100% |
450
35.7 IPS |
|
|
Object Detection (HP)
|
100% |
684
54.2 IPS |
|
|
Object Detection (Q)
|
87% |
728
58.5 IPS |
|
|
Face Detection (SP)
|
100% |
1490
17.7 IPS |
|
|
Face Detection (HP)
|
100% |
1605
19.1 IPS |
|
|
Face Detection (Q)
|
97% |
1410
16.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1191
9.18 IPS |
|
|
Depth Estimation (HP)
|
99% |
2089
16.1 IPS |
|
|
Depth Estimation (Q)
|
63% |
1717
15.9 IPS |
|
|
Style Transfer (SP)
|
100% |
3896
5.01 IPS |
|
|
Style Transfer (HP)
|
100% |
6116
7.86 IPS |
|
|
Style Transfer (Q)
|
98% |
5904
7.61 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
402
14.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
637
23.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
619
22.9 IPS |
|
|
Text Classification (SP)
|
100% |
249
332.4 IPS |
|
|
Text Classification (HP)
|
100% |
265
354.0 IPS |
|
|
Text Classification (Q)
|
91% |
437
587.0 IPS |
|
|
Machine Translation (SP)
|
100% |
409
7.05 IPS |
|
|
Machine Translation (HP)
|
100% |
425
7.32 IPS |
|
|
Machine Translation (Q)
|
57% |
327
8.00 IPS |
