HONOR ELN-W09
Geekbench AI Score
425
Single Precision Score
420
Half Precision Score
532
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | maquiz |
| Upload Date | April 12 2025 10:54 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM SM6225 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | HONOR ELN-W09 |
| Model ID | HONOR ELN-W09 |
| Motherboard | ELN |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM SM6225 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 3.68 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
201
37.4 IPS |
|
|
Image Classification (HP)
|
100% |
201
37.4 IPS |
|
|
Image Classification (Q)
|
100% |
369
68.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
244
3.96 IPS |
|
|
Image Segmentation (HP)
|
100% |
245
3.97 IPS |
|
|
Image Segmentation (Q)
|
98% |
462
7.52 IPS |
|
|
Pose Estimation (SP)
|
100% |
940
1.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
913
1.06 IPS |
|
|
Pose Estimation (Q)
|
84% |
644
0.76 IPS |
|
|
Object Detection (SP)
|
100% |
190
15.0 IPS |
|
|
Object Detection (HP)
|
100% |
189
15.0 IPS |
|
|
Object Detection (Q)
|
83% |
357
28.9 IPS |
|
|
Face Detection (SP)
|
100% |
532
6.32 IPS |
|
|
Face Detection (HP)
|
100% |
532
6.32 IPS |
|
|
Face Detection (Q)
|
95% |
835
9.96 IPS |
|
|
Depth Estimation (SP)
|
100% |
754
5.81 IPS |
|
|
Depth Estimation (HP)
|
99% |
736
5.67 IPS |
|
|
Depth Estimation (Q)
|
64% |
822
7.53 IPS |
|
|
Style Transfer (SP)
|
89% |
1630
2.12 IPS |
|
|
Style Transfer (HP)
|
89% |
1624
2.11 IPS |
|
|
Style Transfer (Q)
|
98% |
2006
2.59 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
406
15.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
399
14.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
475
17.6 IPS |
|
|
Text Classification (SP)
|
100% |
230
306.5 IPS |
|
|
Text Classification (HP)
|
100% |
225
300.9 IPS |
|
|
Text Classification (Q)
|
88% |
351
473.3 IPS |
|
|
Machine Translation (SP)
|
100% |
367
6.33 IPS |
|
|
Machine Translation (HP)
|
100% |
355
6.11 IPS |
|
|
Machine Translation (Q)
|
50% |
203
7.22 IPS |
