HONOR HEY2-W09
Geekbench AI Score
196
Single Precision Score
196
Half Precision Score
7865
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | 46fy45 |
| Upload Date | January 21 2026 06:07 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| 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% |
115
21.3 IPS |
|
|
Image Classification (HP)
|
100% |
116
21.5 IPS |
|
|
Image Classification (Q)
|
97% |
7257
1.35 KIPS |
|
|
Image Segmentation (SP)
|
100% |
155
2.52 IPS |
|
|
Image Segmentation (HP)
|
100% |
156
2.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
5732
93.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
209
0.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
208
0.24 IPS |
|
|
Pose Estimation (Q)
|
98% |
21191
24.8 IPS |
|
|
Object Detection (SP)
|
100% |
114
9.03 IPS |
|
|
Object Detection (HP)
|
100% |
114
9.06 IPS |
|
|
Object Detection (Q)
|
86% |
3638
292.6 IPS |
|
|
Face Detection (SP)
|
100% |
296
3.51 IPS |
|
|
Face Detection (HP)
|
100% |
297
3.53 IPS |
|
|
Face Detection (Q)
|
97% |
21037
250.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
255
1.97 IPS |
|
|
Depth Estimation (HP)
|
99% |
257
1.98 IPS |
|
|
Depth Estimation (Q)
|
63% |
16309
152.7 IPS |
|
|
Style Transfer (SP)
|
100% |
436
0.56 IPS |
|
|
Style Transfer (HP)
|
100% |
434
0.56 IPS |
|
|
Style Transfer (Q)
|
98% |
44282
57.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
125
4.62 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
125
4.62 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
11124
412.2 IPS |
|
|
Text Classification (SP)
|
100% |
173
230.9 IPS |
|
|
Text Classification (HP)
|
100% |
173
231.2 IPS |
|
|
Text Classification (Q)
|
93% |
2650
3.56 KIPS |
|
|
Machine Translation (SP)
|
100% |
279
4.80 IPS |
|
|
Machine Translation (HP)
|
100% |
279
4.81 IPS |
|
|
Machine Translation (Q)
|
55% |
631
16.5 IPS |
