HONOR WOD-LX3
Geekbench AI Score
175
Single Precision Score
173
Half Precision Score
190
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 06 2024 01:35 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765V/XBA |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR WOD-LX3 |
| Model ID | HONOR WOD-LX3 |
| Motherboard | WDYL |
| CPU Information | |
|---|---|
| Name | ARM MT6765V/XBA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores @ 1.60 GHz |
| Cluster 2 | 4 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 3.71 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
54
10.1 IPS |
|
|
Image Classification (HP)
|
100% |
46
8.57 IPS |
|
|
Image Classification (Q)
|
100% |
67
12.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
78
1.27 IPS |
|
|
Image Segmentation (HP)
|
100% |
87
1.42 IPS |
|
|
Image Segmentation (Q)
|
98% |
121
1.97 IPS |
|
|
Pose Estimation (SP)
|
100% |
538
0.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
500
0.58 IPS |
|
|
Pose Estimation (Q)
|
84% |
390
0.46 IPS |
|
|
Object Detection (SP)
|
100% |
101
7.99 IPS |
|
|
Object Detection (HP)
|
100% |
109
8.65 IPS |
|
|
Object Detection (Q)
|
83% |
145
11.7 IPS |
|
|
Face Detection (SP)
|
100% |
249
2.96 IPS |
|
|
Face Detection (HP)
|
100% |
237
2.81 IPS |
|
|
Face Detection (Q)
|
95% |
397
4.74 IPS |
|
|
Depth Estimation (SP)
|
100% |
337
2.59 IPS |
|
|
Depth Estimation (HP)
|
99% |
326
2.51 IPS |
|
|
Depth Estimation (Q)
|
64% |
371
3.39 IPS |
|
|
Style Transfer (SP)
|
89% |
916
1.19 IPS |
|
|
Style Transfer (HP)
|
89% |
870
1.13 IPS |
|
|
Style Transfer (Q)
|
98% |
900
1.16 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
140
5.16 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
149
5.49 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
188
6.97 IPS |
|
|
Text Classification (SP)
|
100% |
82
109.1 IPS |
|
|
Text Classification (HP)
|
100% |
80
107.2 IPS |
|
|
Text Classification (Q)
|
88% |
91
123.1 IPS |
|
|
Machine Translation (SP)
|
100% |
140
2.42 IPS |
|
|
Machine Translation (HP)
|
100% |
141
2.43 IPS |
|
|
Machine Translation (Q)
|
50% |
59
2.09 IPS |
