HONOR HEY2-W09
Geekbench AI Score
509
Single Precision Score
489
Half Precision Score
1059
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | 46fy45 |
| Upload Date | January 21 2026 05:11 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
188
35.0 IPS |
|
|
Image Classification (HP)
|
100% |
359
66.7 IPS |
|
|
Image Classification (Q)
|
100% |
1330
247.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
472
7.65 IPS |
|
|
Image Segmentation (HP)
|
100% |
483
7.83 IPS |
|
|
Image Segmentation (Q)
|
98% |
1544
25.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1810
2.11 IPS |
|
|
Pose Estimation (HP)
|
100% |
1730
2.02 IPS |
|
|
Pose Estimation (Q)
|
84% |
3365
3.99 IPS |
|
|
Object Detection (SP)
|
100% |
392
31.1 IPS |
|
|
Object Detection (HP)
|
100% |
397
31.5 IPS |
|
|
Object Detection (Q)
|
83% |
1278
103.2 IPS |
|
|
Face Detection (SP)
|
100% |
1040
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
1046
12.4 IPS |
|
|
Face Detection (Q)
|
95% |
2811
33.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1375
10.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
488
3.76 IPS |
|
|
Depth Estimation (Q)
|
64% |
1014
9.29 IPS |
|
|
Style Transfer (SP)
|
89% |
1145
1.49 IPS |
|
|
Style Transfer (HP)
|
89% |
1144
1.49 IPS |
|
|
Style Transfer (Q)
|
98% |
2484
3.20 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
271
10.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
275
10.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
625
23.2 IPS |
|
|
Text Classification (SP)
|
100% |
159
211.9 IPS |
|
|
Text Classification (HP)
|
100% |
158
210.3 IPS |
|
|
Text Classification (Q)
|
88% |
260
351.3 IPS |
|
|
Machine Translation (SP)
|
100% |
263
4.53 IPS |
|
|
Machine Translation (HP)
|
100% |
260
4.48 IPS |
|
|
Machine Translation (Q)
|
50% |
175
6.20 IPS |
