HONOR MTN-NX1M
Geekbench AI Score
216
Single Precision Score
217
Half Precision Score
504
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 09 2026 07:43 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
127
23.7 IPS |
|
|
Image Classification (HP)
|
100% |
127
23.7 IPS |
|
|
Image Classification (Q)
|
99% |
321
60.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
173
2.80 IPS |
|
|
Image Segmentation (HP)
|
100% |
174
2.82 IPS |
|
|
Image Segmentation (Q)
|
98% |
364
5.92 IPS |
|
|
Pose Estimation (SP)
|
100% |
228
0.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
228
0.27 IPS |
|
|
Pose Estimation (Q)
|
98% |
868
1.02 IPS |
|
|
Object Detection (SP)
|
100% |
126
10.0 IPS |
|
|
Object Detection (HP)
|
100% |
126
10.0 IPS |
|
|
Object Detection (Q)
|
87% |
346
27.7 IPS |
|
|
Face Detection (SP)
|
100% |
344
4.09 IPS |
|
|
Face Detection (HP)
|
100% |
348
4.14 IPS |
|
|
Face Detection (Q)
|
97% |
763
9.10 IPS |
|
|
Depth Estimation (SP)
|
100% |
284
2.19 IPS |
|
|
Depth Estimation (HP)
|
99% |
285
2.20 IPS |
|
|
Depth Estimation (Q)
|
64% |
678
6.15 IPS |
|
|
Style Transfer (SP)
|
100% |
500
0.64 IPS |
|
|
Style Transfer (HP)
|
100% |
500
0.64 IPS |
|
|
Style Transfer (Q)
|
98% |
1484
1.91 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
139
5.13 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
139
5.14 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
502
18.6 IPS |
|
|
Text Classification (SP)
|
100% |
179
238.4 IPS |
|
|
Text Classification (HP)
|
100% |
180
240.1 IPS |
|
|
Text Classification (Q)
|
91% |
314
422.3 IPS |
|
|
Machine Translation (SP)
|
100% |
301
5.19 IPS |
|
|
Machine Translation (HP)
|
100% |
302
5.20 IPS |
|
|
Machine Translation (Q)
|
57% |
253
6.18 IPS |
