HONOR CRT-NX1
Geekbench AI Score
511
Single Precision Score
513
Half Precision Score
955
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 28 2024 04:48 AM |
| 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% |
230
42.7 IPS |
|
|
Image Classification (HP)
|
100% |
229
42.6 IPS |
|
|
Image Classification (Q)
|
100% |
652
121.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
283
4.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
283
4.58 IPS |
|
|
Image Segmentation (Q)
|
98% |
716
11.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1094
1.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
1099
1.28 IPS |
|
|
Pose Estimation (Q)
|
84% |
1641
1.95 IPS |
|
|
Object Detection (SP)
|
100% |
229
18.2 IPS |
|
|
Object Detection (HP)
|
100% |
229
18.2 IPS |
|
|
Object Detection (Q)
|
83% |
650
52.5 IPS |
|
|
Face Detection (SP)
|
100% |
734
8.73 IPS |
|
|
Face Detection (HP)
|
100% |
737
8.75 IPS |
|
|
Face Detection (Q)
|
95% |
1482
17.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
836
6.44 IPS |
|
|
Depth Estimation (HP)
|
99% |
867
6.68 IPS |
|
|
Depth Estimation (Q)
|
64% |
1511
13.8 IPS |
|
|
Style Transfer (SP)
|
89% |
1856
2.41 IPS |
|
|
Style Transfer (HP)
|
89% |
1865
2.42 IPS |
|
|
Style Transfer (Q)
|
98% |
3774
4.87 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
501
18.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
505
18.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
913
33.8 IPS |
|
|
Text Classification (SP)
|
100% |
275
366.6 IPS |
|
|
Text Classification (HP)
|
100% |
272
363.4 IPS |
|
|
Text Classification (Q)
|
88% |
491
662.8 IPS |
|
|
Machine Translation (SP)
|
100% |
475
8.19 IPS |
|
|
Machine Translation (HP)
|
100% |
473
8.15 IPS |
|
|
Machine Translation (Q)
|
50% |
336
11.9 IPS |
