HONOR ELI-NX9
Geekbench AI Score
676
Single Precision Score
654
Half Precision Score
1280
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | March 20 2025 07:00 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
684
127.3 IPS |
|
|
Image Classification (HP)
|
100% |
724
134.7 IPS |
|
|
Image Classification (Q)
|
100% |
1715
319.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
798
12.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
823
13.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
1885
30.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1961
2.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
1962
2.29 IPS |
|
|
Pose Estimation (Q)
|
84% |
5233
6.21 IPS |
|
|
Object Detection (SP)
|
98% |
775
61.7 IPS |
|
|
Object Detection (HP)
|
98% |
715
56.9 IPS |
|
|
Object Detection (Q)
|
83% |
1799
145.3 IPS |
|
|
Face Detection (SP)
|
100% |
585
6.95 IPS |
|
|
Face Detection (HP)
|
100% |
573
6.80 IPS |
|
|
Face Detection (Q)
|
95% |
1220
14.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
714
5.52 IPS |
|
|
Depth Estimation (HP)
|
99% |
717
5.54 IPS |
|
|
Depth Estimation (Q)
|
64% |
1484
13.6 IPS |
|
|
Style Transfer (SP)
|
89% |
1735
2.25 IPS |
|
|
Style Transfer (HP)
|
89% |
1691
2.20 IPS |
|
|
Style Transfer (Q)
|
98% |
3855
4.97 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
523
19.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
397
14.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
985
36.5 IPS |
|
|
Text Classification (SP)
|
100% |
180
240.3 IPS |
|
|
Text Classification (HP)
|
99% |
180
240.6 IPS |
|
|
Text Classification (Q)
|
88% |
297
401.0 IPS |
|
|
Machine Translation (SP)
|
100% |
356
6.13 IPS |
|
|
Machine Translation (HP)
|
100% |
349
6.01 IPS |
|
|
Machine Translation (Q)
|
50% |
190
6.75 IPS |
