HONOR ELN-W09
Geekbench AI Score
407
Single Precision Score
406
Half Precision Score
489
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | kot-ubitsa |
| Upload Date | October 28 2025 07:35 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% |
199
37.1 IPS |
|
|
Image Classification (HP)
|
100% |
198
36.8 IPS |
|
|
Image Classification (Q)
|
100% |
343
63.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
233
3.77 IPS |
|
|
Image Segmentation (HP)
|
100% |
235
3.80 IPS |
|
|
Image Segmentation (Q)
|
98% |
450
7.32 IPS |
|
|
Pose Estimation (SP)
|
100% |
787
0.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
807
0.94 IPS |
|
|
Pose Estimation (Q)
|
84% |
473
0.56 IPS |
|
|
Object Detection (SP)
|
100% |
172
13.7 IPS |
|
|
Object Detection (HP)
|
100% |
180
14.3 IPS |
|
|
Object Detection (Q)
|
83% |
340
27.4 IPS |
|
|
Face Detection (SP)
|
100% |
523
6.22 IPS |
|
|
Face Detection (HP)
|
100% |
526
6.25 IPS |
|
|
Face Detection (Q)
|
95% |
806
9.62 IPS |
|
|
Depth Estimation (SP)
|
100% |
769
5.93 IPS |
|
|
Depth Estimation (HP)
|
99% |
765
5.90 IPS |
|
|
Depth Estimation (Q)
|
64% |
711
6.51 IPS |
|
|
Style Transfer (SP)
|
89% |
1541
2.00 IPS |
|
|
Style Transfer (HP)
|
89% |
1550
2.01 IPS |
|
|
Style Transfer (Q)
|
98% |
1759
2.27 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
399
14.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
394
14.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
452
16.8 IPS |
|
|
Text Classification (SP)
|
100% |
231
308.4 IPS |
|
|
Text Classification (HP)
|
100% |
225
300.9 IPS |
|
|
Text Classification (Q)
|
88% |
350
472.1 IPS |
|
|
Machine Translation (SP)
|
100% |
355
6.12 IPS |
|
|
Machine Translation (HP)
|
100% |
333
5.73 IPS |
|
|
Machine Translation (Q)
|
50% |
198
7.02 IPS |
