HONOR ELI-NX9
Geekbench AI Score
685
Single Precision Score
690
Half Precision Score
1265
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 13 2024 10:20 AM |
| Views | 4 |
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 | 7.17 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
722
134.3 IPS |
|
|
Image Classification (HP)
|
100% |
747
138.9 IPS |
|
|
Image Classification (Q)
|
100% |
970
180.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
687
11.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
687
11.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1896
30.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1906
2.22 IPS |
|
|
Pose Estimation (HP)
|
100% |
1917
2.24 IPS |
|
|
Pose Estimation (Q)
|
84% |
2669
3.17 IPS |
|
|
Object Detection (SP)
|
98% |
359
28.6 IPS |
|
|
Object Detection (HP)
|
98% |
364
28.9 IPS |
|
|
Object Detection (Q)
|
83% |
804
64.9 IPS |
|
|
Face Detection (SP)
|
100% |
662
7.87 IPS |
|
|
Face Detection (HP)
|
100% |
657
7.80 IPS |
|
|
Face Detection (Q)
|
95% |
1684
20.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
859
6.63 IPS |
|
|
Depth Estimation (HP)
|
99% |
837
6.47 IPS |
|
|
Depth Estimation (Q)
|
64% |
2045
18.7 IPS |
|
|
Style Transfer (SP)
|
89% |
2229
2.89 IPS |
|
|
Style Transfer (HP)
|
89% |
2238
2.91 IPS |
|
|
Style Transfer (Q)
|
98% |
5346
6.89 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
455
16.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
482
17.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1394
51.7 IPS |
|
|
Text Classification (SP)
|
100% |
258
344.4 IPS |
|
|
Text Classification (HP)
|
99% |
257
342.7 IPS |
|
|
Text Classification (Q)
|
88% |
427
575.3 IPS |
|
|
Machine Translation (SP)
|
100% |
454
7.82 IPS |
|
|
Machine Translation (HP)
|
100% |
453
7.80 IPS |
|
|
Machine Translation (Q)
|
50% |
243
8.63 IPS |
