HONOR BRP-NX1M
Geekbench AI Score
52
Single Precision Score
52
Half Precision Score
135
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | mpoloton |
| Upload Date | July 09 2025 04:15 PM |
| Views | 4 |
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% |
30
5.50 IPS |
|
|
Image Classification (HP)
|
100% |
30
5.55 IPS |
|
|
Image Classification (Q)
|
99% |
91
17.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
40
0.65 IPS |
|
|
Image Segmentation (HP)
|
100% |
40
0.65 IPS |
|
|
Image Segmentation (Q)
|
98% |
82
1.34 IPS |
|
|
Pose Estimation (SP)
|
100% |
47
0.05 IPS |
|
|
Pose Estimation (HP)
|
100% |
47
0.05 IPS |
|
|
Pose Estimation (Q)
|
98% |
251
0.29 IPS |
|
|
Object Detection (SP)
|
100% |
31
2.45 IPS |
|
|
Object Detection (HP)
|
100% |
31
2.45 IPS |
|
|
Object Detection (Q)
|
87% |
102
8.14 IPS |
|
|
Face Detection (SP)
|
100% |
72
0.86 IPS |
|
|
Face Detection (HP)
|
100% |
73
0.87 IPS |
|
|
Face Detection (Q)
|
97% |
191
2.28 IPS |
|
|
Depth Estimation (SP)
|
100% |
65
0.50 IPS |
|
|
Depth Estimation (HP)
|
99% |
65
0.50 IPS |
|
|
Depth Estimation (Q)
|
64% |
173
1.57 IPS |
|
|
Style Transfer (SP)
|
100% |
128
0.16 IPS |
|
|
Style Transfer (HP)
|
100% |
128
0.16 IPS |
|
|
Style Transfer (Q)
|
98% |
359
0.46 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
38
1.39 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
37
1.38 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
138
5.13 IPS |
|
|
Text Classification (SP)
|
100% |
47
62.8 IPS |
|
|
Text Classification (HP)
|
100% |
47
63.2 IPS |
|
|
Text Classification (Q)
|
91% |
92
123.2 IPS |
|
|
Machine Translation (SP)
|
100% |
82
1.42 IPS |
|
|
Machine Translation (HP)
|
100% |
83
1.43 IPS |
|
|
Machine Translation (Q)
|
57% |
75
1.82 IPS |
