HONOR ELP-NX9
Geekbench AI Score
1408
Single Precision Score
1235
Half Precision Score
1893
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 24 2024 09:43 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR ELP-NX9 |
| Model ID | HONOR ELP-NX9 |
| Motherboard | ELP |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.01 GHz |
| Memory Information | |
|---|---|
| Size | 11.04 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1526
283.8 IPS |
|
|
Image Classification (HP)
|
100% |
573
106.6 IPS |
|
|
Image Classification (Q)
|
100% |
971
180.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
640
10.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
645
10.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
1055
17.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2953
3.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
2877
3.36 IPS |
|
|
Pose Estimation (Q)
|
84% |
5908
7.01 IPS |
|
|
Object Detection (SP)
|
98% |
1381
109.9 IPS |
|
|
Object Detection (HP)
|
98% |
1368
108.8 IPS |
|
|
Object Detection (Q)
|
83% |
1035
83.6 IPS |
|
|
Face Detection (SP)
|
100% |
2306
27.4 IPS |
|
|
Face Detection (HP)
|
100% |
2790
33.2 IPS |
|
|
Face Detection (Q)
|
95% |
5080
60.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
1476
11.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
1504
11.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
2184
20.0 IPS |
|
|
Style Transfer (SP)
|
89% |
7074
9.18 IPS |
|
|
Style Transfer (HP)
|
89% |
3215
4.17 IPS |
|
|
Style Transfer (Q)
|
98% |
12739
16.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1380
51.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1512
55.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1456
54.0 IPS |
|
|
Text Classification (SP)
|
100% |
323
431.7 IPS |
|
|
Text Classification (HP)
|
99% |
259
345.4 IPS |
|
|
Text Classification (Q)
|
88% |
669
901.9 IPS |
|
|
Machine Translation (SP)
|
100% |
719
12.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1079
18.6 IPS |
|
|
Machine Translation (Q)
|
50% |
688
24.4 IPS |
