HONOR ELI-NX9
Geekbench AI Score
608
Single Precision Score
639
Half Precision Score
1252
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 22 2024 12:29 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR ELI-NX9 |
| Model ID | HONOR ELI-NX9 |
| Motherboard | crow |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.63 GHz |
| Memory Information | |
|---|---|
| Size | 11.07 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
773
143.8 IPS |
|
|
Image Classification (HP)
|
100% |
828
154.0 IPS |
|
|
Image Classification (Q)
|
100% |
1989
369.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
856
13.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
861
14.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2075
33.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2089
2.44 IPS |
|
|
Pose Estimation (HP)
|
100% |
1240
1.45 IPS |
|
|
Pose Estimation (Q)
|
84% |
2728
3.24 IPS |
|
|
Object Detection (SP)
|
98% |
378
30.1 IPS |
|
|
Object Detection (HP)
|
98% |
278
22.1 IPS |
|
|
Object Detection (Q)
|
83% |
806
65.1 IPS |
|
|
Face Detection (SP)
|
100% |
555
6.59 IPS |
|
|
Face Detection (HP)
|
100% |
702
8.34 IPS |
|
|
Face Detection (Q)
|
95% |
1233
14.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
722
5.58 IPS |
|
|
Depth Estimation (HP)
|
99% |
848
6.56 IPS |
|
|
Depth Estimation (Q)
|
64% |
2044
18.7 IPS |
|
|
Style Transfer (SP)
|
89% |
1633
2.12 IPS |
|
|
Style Transfer (HP)
|
89% |
2260
2.93 IPS |
|
|
Style Transfer (Q)
|
98% |
5236
6.75 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
371
13.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
481
17.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1353
50.1 IPS |
|
|
Text Classification (SP)
|
100% |
163
218.2 IPS |
|
|
Text Classification (HP)
|
99% |
165
220.1 IPS |
|
|
Text Classification (Q)
|
88% |
260
351.1 IPS |
|
|
Machine Translation (SP)
|
100% |
337
5.80 IPS |
|
|
Machine Translation (HP)
|
100% |
434
7.47 IPS |
|
|
Machine Translation (Q)
|
50% |
226
8.01 IPS |
