HONOR CRT-NX1
Geekbench AI Score
515
Single Precision Score
514
Half Precision Score
951
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 20 2025 12:53 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
223
41.5 IPS |
|
|
Image Classification (HP)
|
100% |
227
42.1 IPS |
|
|
Image Classification (Q)
|
100% |
647
120.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
280
4.53 IPS |
|
|
Image Segmentation (HP)
|
100% |
279
4.52 IPS |
|
|
Image Segmentation (Q)
|
98% |
709
11.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1103
1.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
1108
1.29 IPS |
|
|
Pose Estimation (Q)
|
84% |
1641
1.95 IPS |
|
|
Object Detection (SP)
|
100% |
227
18.0 IPS |
|
|
Object Detection (HP)
|
100% |
227
18.0 IPS |
|
|
Object Detection (Q)
|
83% |
644
52.0 IPS |
|
|
Face Detection (SP)
|
100% |
740
8.80 IPS |
|
|
Face Detection (HP)
|
100% |
727
8.64 IPS |
|
|
Face Detection (Q)
|
95% |
1476
17.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
951
7.33 IPS |
|
|
Depth Estimation (HP)
|
99% |
957
7.37 IPS |
|
|
Depth Estimation (Q)
|
64% |
1507
13.8 IPS |
|
|
Style Transfer (SP)
|
89% |
1866
2.42 IPS |
|
|
Style Transfer (HP)
|
89% |
1865
2.42 IPS |
|
|
Style Transfer (Q)
|
98% |
3760
4.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
503
18.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
502
18.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
911
33.8 IPS |
|
|
Text Classification (SP)
|
100% |
273
364.5 IPS |
|
|
Text Classification (HP)
|
100% |
270
360.7 IPS |
|
|
Text Classification (Q)
|
88% |
496
668.4 IPS |
|
|
Machine Translation (SP)
|
100% |
473
8.16 IPS |
|
|
Machine Translation (HP)
|
100% |
468
8.06 IPS |
|
|
Machine Translation (Q)
|
50% |
332
11.8 IPS |
