HONOR ELP-NX9
Geekbench AI Score
1575
Single Precision Score
1508
Half Precision Score
2434
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 15 2025 03:50 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1325
246.4 IPS |
|
|
Image Classification (HP)
|
100% |
1270
236.3 IPS |
|
|
Image Classification (Q)
|
100% |
2291
426.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1539
25.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1364
22.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
2409
39.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2373
2.77 IPS |
|
|
Pose Estimation (HP)
|
100% |
2232
2.60 IPS |
|
|
Pose Estimation (Q)
|
84% |
5055
6.00 IPS |
|
|
Object Detection (SP)
|
98% |
1186
94.4 IPS |
|
|
Object Detection (HP)
|
98% |
1071
85.2 IPS |
|
|
Object Detection (Q)
|
83% |
1547
125.0 IPS |
|
|
Face Detection (SP)
|
100% |
2182
25.9 IPS |
|
|
Face Detection (HP)
|
100% |
2124
25.2 IPS |
|
|
Face Detection (Q)
|
95% |
4464
53.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
2288
17.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
1944
15.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
3861
35.4 IPS |
|
|
Style Transfer (SP)
|
89% |
4740
6.15 IPS |
|
|
Style Transfer (HP)
|
89% |
5847
7.59 IPS |
|
|
Style Transfer (Q)
|
98% |
9415
12.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1102
40.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1154
42.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2763
102.4 IPS |
|
|
Text Classification (SP)
|
100% |
666
889.5 IPS |
|
|
Text Classification (HP)
|
99% |
577
769.7 IPS |
|
|
Text Classification (Q)
|
88% |
941
1.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
946
16.3 IPS |
|
|
Machine Translation (HP)
|
100% |
914
15.7 IPS |
|
|
Machine Translation (Q)
|
50% |
402
14.3 IPS |
