HONOR HEY2-W09
Geekbench AI Score
159
Single Precision Score
223
Half Precision Score
227
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | Nipoc |
| Upload Date | October 13 2024 08:34 AM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR HEY2-W09 |
| Model ID | HONOR HEY2-W09 |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
125
23.2 IPS |
|
|
Image Classification (HP)
|
100% |
217
40.4 IPS |
|
|
Image Classification (Q)
|
97% |
204
38.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
181
2.94 IPS |
|
|
Image Segmentation (HP)
|
100% |
230
3.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
223
3.63 IPS |
|
|
Pose Estimation (SP)
|
100% |
179
0.21 IPS |
|
|
Pose Estimation (HP)
|
100% |
288
0.34 IPS |
|
|
Pose Estimation (Q)
|
95% |
287
0.34 IPS |
|
|
Object Detection (SP)
|
100% |
97
7.73 IPS |
|
|
Object Detection (HP)
|
100% |
141
11.2 IPS |
|
|
Object Detection (Q)
|
89% |
141
11.3 IPS |
|
|
Face Detection (SP)
|
100% |
372
4.43 IPS |
|
|
Face Detection (HP)
|
100% |
506
6.01 IPS |
|
|
Face Detection (Q)
|
97% |
475
5.66 IPS |
|
|
Depth Estimation (SP)
|
100% |
276
2.13 IPS |
|
|
Depth Estimation (HP)
|
99% |
459
3.55 IPS |
|
|
Depth Estimation (Q)
|
63% |
371
3.49 IPS |
|
|
Style Transfer (SP)
|
100% |
604
0.78 IPS |
|
|
Style Transfer (HP)
|
100% |
1211
1.56 IPS |
|
|
Style Transfer (Q)
|
98% |
1232
1.59 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
109
4.03 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
137
5.07 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
134
4.98 IPS |
|
|
Text Classification (SP)
|
100% |
48
63.9 IPS |
|
|
Text Classification (HP)
|
100% |
48
63.7 IPS |
|
|
Text Classification (Q)
|
91% |
91
122.4 IPS |
|
|
Machine Translation (SP)
|
100% |
84
1.44 IPS |
|
|
Machine Translation (HP)
|
100% |
83
1.44 IPS |
|
|
Machine Translation (Q)
|
57% |
75
1.83 IPS |
