HONOR MTN-NX1
Geekbench AI Score
1033
Single Precision Score
780
Half Precision Score
1282
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 26 2026 09:21 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR MTN-NX1 |
| Model ID | HONOR MTN-NX1 |
| Motherboard | volcano |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3457 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.21 GHz |
| Cluster 3 | 1 Core @ 2.30 GHz |
| Memory Information | |
|---|---|
| Size | 11.18 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
885
164.5 IPS |
|
|
Image Classification (HP)
|
100% |
870
161.8 IPS |
|
|
Image Classification (Q)
|
100% |
945
175.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
787
12.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
404
6.55 IPS |
|
|
Image Segmentation (Q)
|
98% |
1044
17.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1934
2.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
1919
2.24 IPS |
|
|
Pose Estimation (Q)
|
84% |
2958
3.51 IPS |
|
|
Object Detection (SP)
|
98% |
847
67.4 IPS |
|
|
Object Detection (HP)
|
98% |
424
33.7 IPS |
|
|
Object Detection (Q)
|
83% |
887
71.6 IPS |
|
|
Face Detection (SP)
|
100% |
1210
14.4 IPS |
|
|
Face Detection (HP)
|
100% |
717
8.52 IPS |
|
|
Face Detection (Q)
|
95% |
1776
21.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
919
7.10 IPS |
|
|
Depth Estimation (HP)
|
99% |
1452
11.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
2128
19.5 IPS |
|
|
Style Transfer (SP)
|
89% |
4485
5.82 IPS |
|
|
Style Transfer (HP)
|
89% |
2306
2.99 IPS |
|
|
Style Transfer (Q)
|
98% |
5097
6.57 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
509
18.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
500
18.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1210
44.9 IPS |
|
|
Text Classification (SP)
|
100% |
546
729.0 IPS |
|
|
Text Classification (HP)
|
99% |
274
365.9 IPS |
|
|
Text Classification (Q)
|
88% |
595
802.8 IPS |
|
|
Machine Translation (SP)
|
100% |
880
15.2 IPS |
|
|
Machine Translation (HP)
|
100% |
894
15.4 IPS |
|
|
Machine Translation (Q)
|
50% |
335
11.9 IPS |
