HONOR MTN-NX1M
Geekbench AI Score
468
Single Precision Score
813
Half Precision Score
650
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 26 2026 08:58 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR MTN-NX1M |
| Model ID | HONOR MTN-NX1M |
| 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 | 7.29 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
354
65.9 IPS |
|
|
Image Classification (HP)
|
100% |
620
115.3 IPS |
|
|
Image Classification (Q)
|
100% |
536
99.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
562
9.10 IPS |
|
|
Image Segmentation (HP)
|
100% |
974
15.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
767
12.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1815
2.12 IPS |
|
|
Pose Estimation (HP)
|
99% |
3402
3.97 IPS |
|
|
Pose Estimation (Q)
|
95% |
3333
3.91 IPS |
|
|
Object Detection (SP)
|
100% |
288
22.9 IPS |
|
|
Object Detection (HP)
|
99% |
481
38.2 IPS |
|
|
Object Detection (Q)
|
85% |
446
35.9 IPS |
|
|
Face Detection (SP)
|
100% |
926
11.0 IPS |
|
|
Face Detection (HP)
|
100% |
1625
19.3 IPS |
|
|
Face Detection (Q)
|
97% |
1297
15.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
1134
8.73 IPS |
|
|
Depth Estimation (HP)
|
98% |
2346
18.1 IPS |
|
|
Depth Estimation (Q)
|
61% |
1787
17.4 IPS |
|
|
Style Transfer (SP)
|
100% |
2245
2.89 IPS |
|
|
Style Transfer (HP)
|
100% |
5242
6.74 IPS |
|
|
Style Transfer (Q)
|
98% |
5134
6.62 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
494
18.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
900
33.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
866
32.1 IPS |
|
|
Text Classification (SP)
|
35% |
18
175.5 IPS |
|
|
Text Classification (HP)
|
35% |
29
260.2 IPS |
|
|
Text Classification (Q)
|
33% |
23
258.4 IPS |
|
|
Machine Translation (SP)
|
100% |
235
4.04 IPS |
|
|
Machine Translation (HP)
|
100% |
247
4.26 IPS |
|
|
Machine Translation (Q)
|
48% |
94
3.60 IPS |
