HONOR HEY2-W09
Geekbench AI Score
356
Single Precision Score
610
Half Precision Score
554
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | 46fy45 |
| Upload Date | January 21 2026 05:21 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM SM6450 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | HONOR HEY2-W09 |
| Model ID | HONOR HEY2-W09 |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM SM6450 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
263
48.9 IPS |
|
|
Image Classification (HP)
|
100% |
458
85.1 IPS |
|
|
Image Classification (Q)
|
99% |
410
76.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
421
6.82 IPS |
|
|
Image Segmentation (HP)
|
100% |
750
12.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
667
10.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1471
1.72 IPS |
|
|
Pose Estimation (HP)
|
99% |
2790
3.26 IPS |
|
|
Pose Estimation (Q)
|
97% |
2745
3.21 IPS |
|
|
Object Detection (SP)
|
100% |
223
17.7 IPS |
|
|
Object Detection (HP)
|
99% |
335
26.6 IPS |
|
|
Object Detection (Q)
|
85% |
314
25.3 IPS |
|
|
Face Detection (SP)
|
100% |
695
8.25 IPS |
|
|
Face Detection (HP)
|
100% |
1221
14.5 IPS |
|
|
Face Detection (Q)
|
97% |
1043
12.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
832
6.41 IPS |
|
|
Depth Estimation (HP)
|
98% |
1670
12.9 IPS |
|
|
Depth Estimation (Q)
|
65% |
1370
12.3 IPS |
|
|
Style Transfer (SP)
|
100% |
1654
2.13 IPS |
|
|
Style Transfer (HP)
|
100% |
3655
4.70 IPS |
|
|
Style Transfer (Q)
|
98% |
3632
4.68 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
384
14.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
679
25.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
630
23.4 IPS |
|
|
Text Classification (SP)
|
35% |
15
147.3 IPS |
|
|
Text Classification (HP)
|
35% |
24
214.8 IPS |
|
|
Text Classification (Q)
|
35% |
23
209.8 IPS |
|
|
Machine Translation (SP)
|
100% |
165
2.84 IPS |
|
|
Machine Translation (HP)
|
97% |
184
3.17 IPS |
|
|
Machine Translation (Q)
|
64% |
154
3.17 IPS |
