HONOR ELN-W09
Geekbench AI Score
419
Single Precision Score
412
Half Precision Score
515
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | kot-ubitsa |
| Upload Date | October 28 2025 06:26 PM |
| Views | 6 |
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% |
200
37.3 IPS |
|
|
Image Classification (HP)
|
100% |
201
37.4 IPS |
|
|
Image Classification (Q)
|
100% |
363
67.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
247
4.01 IPS |
|
|
Image Segmentation (HP)
|
100% |
246
3.99 IPS |
|
|
Image Segmentation (Q)
|
98% |
460
7.48 IPS |
|
|
Pose Estimation (SP)
|
100% |
863
1.01 IPS |
|
|
Pose Estimation (HP)
|
100% |
879
1.03 IPS |
|
|
Pose Estimation (Q)
|
84% |
568
0.67 IPS |
|
|
Object Detection (SP)
|
100% |
184
14.6 IPS |
|
|
Object Detection (HP)
|
100% |
187
14.8 IPS |
|
|
Object Detection (Q)
|
83% |
348
28.1 IPS |
|
|
Face Detection (SP)
|
100% |
538
6.40 IPS |
|
|
Face Detection (HP)
|
100% |
535
6.35 IPS |
|
|
Face Detection (Q)
|
95% |
838
10.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
772
5.95 IPS |
|
|
Depth Estimation (HP)
|
99% |
766
5.90 IPS |
|
|
Depth Estimation (Q)
|
64% |
780
7.15 IPS |
|
|
Style Transfer (SP)
|
89% |
1562
2.03 IPS |
|
|
Style Transfer (HP)
|
89% |
1399
1.82 IPS |
|
|
Style Transfer (Q)
|
98% |
1859
2.40 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
407
15.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
399
14.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
467
17.3 IPS |
|
|
Text Classification (SP)
|
100% |
233
310.7 IPS |
|
|
Text Classification (HP)
|
100% |
226
301.3 IPS |
|
|
Text Classification (Q)
|
88% |
352
474.2 IPS |
|
|
Machine Translation (SP)
|
100% |
351
6.05 IPS |
|
|
Machine Translation (HP)
|
100% |
343
5.90 IPS |
|
|
Machine Translation (Q)
|
50% |
201
7.15 IPS |
