HONOR BRP-NX1M
Geekbench AI Score
51
Single Precision Score
51
Half Precision Score
133
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 02 2025 10:00 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR BRP-NX1M |
| Model ID | HONOR BRP-NX1M |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 7.29 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
29
5.48 IPS |
|
|
Image Classification (HP)
|
100% |
30
5.55 IPS |
|
|
Image Classification (Q)
|
99% |
91
16.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
39
0.64 IPS |
|
|
Image Segmentation (HP)
|
100% |
40
0.65 IPS |
|
|
Image Segmentation (Q)
|
98% |
82
1.33 IPS |
|
|
Pose Estimation (SP)
|
100% |
47
0.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
47
0.06 IPS |
|
|
Pose Estimation (Q)
|
98% |
242
0.28 IPS |
|
|
Object Detection (SP)
|
100% |
30
2.42 IPS |
|
|
Object Detection (HP)
|
100% |
31
2.42 IPS |
|
|
Object Detection (Q)
|
87% |
100
8.04 IPS |
|
|
Face Detection (SP)
|
100% |
72
0.85 IPS |
|
|
Face Detection (HP)
|
100% |
72
0.86 IPS |
|
|
Face Detection (Q)
|
97% |
190
2.27 IPS |
|
|
Depth Estimation (SP)
|
100% |
64
0.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
64
0.50 IPS |
|
|
Depth Estimation (Q)
|
64% |
169
1.54 IPS |
|
|
Style Transfer (SP)
|
100% |
126
0.16 IPS |
|
|
Style Transfer (HP)
|
100% |
125
0.16 IPS |
|
|
Style Transfer (Q)
|
98% |
351
0.45 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
37
1.37 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
37
1.38 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
134
4.98 IPS |
|
|
Text Classification (SP)
|
100% |
47
62.1 IPS |
|
|
Text Classification (HP)
|
100% |
47
63.0 IPS |
|
|
Text Classification (Q)
|
91% |
90
120.8 IPS |
|
|
Machine Translation (SP)
|
100% |
82
1.41 IPS |
|
|
Machine Translation (HP)
|
100% |
82
1.42 IPS |
|
|
Machine Translation (Q)
|
57% |
73
1.79 IPS |
