HONOR ELN-W09
Geekbench AI Score
153
Single Precision Score
234
Half Precision Score
212
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | kot-ubitsa |
| Upload Date | October 28 2025 07:50 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
111
20.7 IPS |
|
|
Image Classification (HP)
|
100% |
181
33.7 IPS |
|
|
Image Classification (Q)
|
99% |
169
31.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
162
2.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
259
4.19 IPS |
|
|
Image Segmentation (Q)
|
98% |
236
3.84 IPS |
|
|
Pose Estimation (SP)
|
100% |
553
0.65 IPS |
|
|
Pose Estimation (HP)
|
99% |
907
1.06 IPS |
|
|
Pose Estimation (Q)
|
97% |
899
1.05 IPS |
|
|
Object Detection (SP)
|
100% |
92
7.34 IPS |
|
|
Object Detection (HP)
|
99% |
147
11.7 IPS |
|
|
Object Detection (Q)
|
85% |
141
11.4 IPS |
|
|
Face Detection (SP)
|
100% |
343
4.07 IPS |
|
|
Face Detection (HP)
|
100% |
529
6.29 IPS |
|
|
Face Detection (Q)
|
97% |
476
5.68 IPS |
|
|
Depth Estimation (SP)
|
100% |
339
2.61 IPS |
|
|
Depth Estimation (HP)
|
98% |
528
4.08 IPS |
|
|
Depth Estimation (Q)
|
63% |
431
3.98 IPS |
|
|
Style Transfer (SP)
|
100% |
813
1.05 IPS |
|
|
Style Transfer (HP)
|
100% |
1229
1.58 IPS |
|
|
Style Transfer (Q)
|
98% |
1196
1.54 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
143
5.28 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
211
7.78 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
189
7.01 IPS |
|
|
Text Classification (SP)
|
35% |
6
59.0 IPS |
|
|
Text Classification (HP)
|
35% |
9
84.7 IPS |
|
|
Text Classification (Q)
|
35% |
9
83.2 IPS |
|
|
Machine Translation (SP)
|
100% |
101
1.74 IPS |
|
|
Machine Translation (HP)
|
97% |
124
2.14 IPS |
|
|
Machine Translation (Q)
|
64% |
89
1.83 IPS |
