HONOR ELN-W09
Geekbench AI Score
66
Single Precision Score
122
Half Precision Score
118
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | berkctezc |
| Upload Date | February 02 2025 09:26 AM |
| Views | 11 |
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% |
36
6.60 IPS |
|
|
Image Classification (HP)
|
100% |
72
13.3 IPS |
|
|
Image Classification (Q)
|
97% |
73
13.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
34
0.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
114
1.85 IPS |
|
|
Image Segmentation (Q)
|
98% |
114
1.85 IPS |
|
|
Pose Estimation (SP)
|
100% |
62
0.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
123
0.14 IPS |
|
|
Pose Estimation (Q)
|
95% |
123
0.14 IPS |
|
|
Object Detection (SP)
|
100% |
36
2.82 IPS |
|
|
Object Detection (HP)
|
100% |
60
4.73 IPS |
|
|
Object Detection (Q)
|
89% |
59
4.71 IPS |
|
|
Face Detection (SP)
|
100% |
88
1.04 IPS |
|
|
Face Detection (HP)
|
100% |
218
2.59 IPS |
|
|
Face Detection (Q)
|
97% |
225
2.69 IPS |
|
|
Depth Estimation (SP)
|
100% |
84
0.64 IPS |
|
|
Depth Estimation (HP)
|
99% |
172
1.33 IPS |
|
|
Depth Estimation (Q)
|
62% |
140
1.32 IPS |
|
|
Style Transfer (SP)
|
100% |
165
0.21 IPS |
|
|
Style Transfer (HP)
|
100% |
327
0.42 IPS |
|
|
Style Transfer (Q)
|
98% |
323
0.42 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
42
1.55 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
86
3.19 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
86
3.17 IPS |
|
|
Text Classification (SP)
|
100% |
82
109.6 IPS |
|
|
Text Classification (HP)
|
100% |
82
109.7 IPS |
|
|
Text Classification (Q)
|
91% |
107
143.9 IPS |
|
|
Machine Translation (SP)
|
100% |
144
2.49 IPS |
|
|
Machine Translation (HP)
|
100% |
145
2.50 IPS |
|
|
Machine Translation (Q)
|
57% |
100
2.44 IPS |
