HONOR ABR-NX1
Geekbench AI Score
465
Single Precision Score
456
Half Precision Score
904
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 23 2025 01:23 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR ABR-NX1 |
| Model ID | HONOR ABR-NX1 |
| Motherboard | ABRN |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.50 GHz |
| Memory Information | |
|---|---|
| Size | 7.38 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
222
41.2 IPS |
|
|
Image Classification (HP)
|
100% |
196
36.4 IPS |
|
|
Image Classification (Q)
|
100% |
632
117.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
266
4.31 IPS |
|
|
Image Segmentation (HP)
|
100% |
267
4.33 IPS |
|
|
Image Segmentation (Q)
|
98% |
721
11.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1049
1.22 IPS |
|
|
Pose Estimation (HP)
|
100% |
1046
1.22 IPS |
|
|
Pose Estimation (Q)
|
84% |
1676
1.99 IPS |
|
|
Object Detection (SP)
|
100% |
195
15.5 IPS |
|
|
Object Detection (HP)
|
100% |
196
15.6 IPS |
|
|
Object Detection (Q)
|
83% |
598
48.3 IPS |
|
|
Face Detection (SP)
|
100% |
699
8.30 IPS |
|
|
Face Detection (HP)
|
100% |
695
8.25 IPS |
|
|
Face Detection (Q)
|
95% |
1549
18.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
868
6.69 IPS |
|
|
Depth Estimation (HP)
|
99% |
818
6.30 IPS |
|
|
Depth Estimation (Q)
|
64% |
1354
12.4 IPS |
|
|
Style Transfer (SP)
|
89% |
1751
2.27 IPS |
|
|
Style Transfer (HP)
|
89% |
1749
2.27 IPS |
|
|
Style Transfer (Q)
|
98% |
3550
4.58 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
466
17.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
467
17.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
819
30.4 IPS |
|
|
Text Classification (SP)
|
100% |
212
282.9 IPS |
|
|
Text Classification (HP)
|
100% |
210
279.8 IPS |
|
|
Text Classification (Q)
|
88% |
456
615.0 IPS |
|
|
Machine Translation (SP)
|
100% |
376
6.47 IPS |
|
|
Machine Translation (HP)
|
100% |
374
6.44 IPS |
|
|
Machine Translation (Q)
|
50% |
290
10.3 IPS |
