HONOR ELN-W09
Geekbench AI Score
98
Single Precision Score
99
Half Precision Score
147
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | berkctezc |
| Upload Date | February 02 2025 08:36 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
56
10.4 IPS |
|
|
Image Classification (HP)
|
100% |
57
10.5 IPS |
|
|
Image Classification (Q)
|
99% |
91
17.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
76
1.23 IPS |
|
|
Image Segmentation (HP)
|
100% |
77
1.24 IPS |
|
|
Image Segmentation (Q)
|
98% |
107
1.73 IPS |
|
|
Pose Estimation (SP)
|
100% |
108
0.13 IPS |
|
|
Pose Estimation (HP)
|
100% |
108
0.13 IPS |
|
|
Pose Estimation (Q)
|
98% |
206
0.24 IPS |
|
|
Object Detection (SP)
|
100% |
57
4.50 IPS |
|
|
Object Detection (HP)
|
100% |
57
4.53 IPS |
|
|
Object Detection (Q)
|
87% |
95
7.62 IPS |
|
|
Face Detection (SP)
|
100% |
146
1.74 IPS |
|
|
Face Detection (HP)
|
100% |
149
1.77 IPS |
|
|
Face Detection (Q)
|
97% |
227
2.71 IPS |
|
|
Depth Estimation (SP)
|
100% |
130
1.00 IPS |
|
|
Depth Estimation (HP)
|
99% |
130
1.00 IPS |
|
|
Depth Estimation (Q)
|
64% |
188
1.70 IPS |
|
|
Style Transfer (SP)
|
100% |
240
0.31 IPS |
|
|
Style Transfer (HP)
|
100% |
242
0.31 IPS |
|
|
Style Transfer (Q)
|
98% |
457
0.59 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
64
2.36 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
64
2.36 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
119
4.42 IPS |
|
|
Text Classification (SP)
|
100% |
81
108.2 IPS |
|
|
Text Classification (HP)
|
100% |
81
108.1 IPS |
|
|
Text Classification (Q)
|
91% |
107
144.0 IPS |
|
|
Machine Translation (SP)
|
100% |
142
2.45 IPS |
|
|
Machine Translation (HP)
|
100% |
144
2.48 IPS |
|
|
Machine Translation (Q)
|
57% |
100
2.43 IPS |
