HONOR CRT-NX1
Geekbench AI Score
144
Single Precision Score
198
Half Precision Score
192
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 27 2024 01:59 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM MT6833 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR CRT-NX1 |
| Model ID | HONOR CRT-NX1 |
| Motherboard | CRTN |
| CPU Information | |
|---|---|
| Name | ARM MT6833 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 7.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
91
17.0 IPS |
|
|
Image Classification (HP)
|
100% |
166
30.8 IPS |
|
|
Image Classification (Q)
|
99% |
153
28.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
130
2.10 IPS |
|
|
Image Segmentation (HP)
|
100% |
223
3.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
215
3.49 IPS |
|
|
Pose Estimation (SP)
|
100% |
88
0.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
102
0.12 IPS |
|
|
Pose Estimation (Q)
|
96% |
102
0.12 IPS |
|
|
Object Detection (SP)
|
100% |
72
5.69 IPS |
|
|
Object Detection (HP)
|
100% |
119
9.41 IPS |
|
|
Object Detection (Q)
|
83% |
112
9.02 IPS |
|
|
Face Detection (SP)
|
100% |
279
3.32 IPS |
|
|
Face Detection (HP)
|
100% |
410
4.88 IPS |
|
|
Face Detection (Q)
|
97% |
383
4.56 IPS |
|
|
Depth Estimation (SP)
|
100% |
166
1.28 IPS |
|
|
Depth Estimation (HP)
|
99% |
216
1.67 IPS |
|
|
Depth Estimation (Q)
|
62% |
175
1.66 IPS |
|
|
Style Transfer (SP)
|
100% |
334
0.43 IPS |
|
|
Style Transfer (HP)
|
100% |
460
0.59 IPS |
|
|
Style Transfer (Q)
|
98% |
458
0.59 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
86
3.17 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
131
4.85 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
130
4.80 IPS |
|
|
Text Classification (SP)
|
100% |
153
204.6 IPS |
|
|
Text Classification (HP)
|
100% |
155
206.9 IPS |
|
|
Text Classification (Q)
|
91% |
252
339.2 IPS |
|
|
Machine Translation (SP)
|
100% |
257
4.43 IPS |
|
|
Machine Translation (HP)
|
100% |
257
4.42 IPS |
|
|
Machine Translation (Q)
|
57% |
184
4.50 IPS |
