WingTech WTATTRW2
Geekbench AI Score
50
Single Precision Score
53
Half Precision Score
35
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | kvnsalters |
| Upload Date | December 15 2025 03:28 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM MT6761V/WBB |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | WingTech WTATTRW2 |
| Model ID | WingTech WTATTRW2 |
| Motherboard | S98830AA1 |
| CPU Information | |
|---|---|
| Name | ARM MT6761V/WBB |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 2.74 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
30
5.57 IPS |
|
|
Image Classification (HP)
|
100% |
30
5.62 IPS |
|
|
Image Classification (Q)
|
97% |
27
4.98 IPS |
|
|
Image Segmentation (SP)
|
100% |
36
0.59 IPS |
|
|
Image Segmentation (HP)
|
100% |
37
0.59 IPS |
|
|
Image Segmentation (Q)
|
98% |
31
0.50 IPS |
|
|
Pose Estimation (SP)
|
100% |
165
0.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
160
0.19 IPS |
|
|
Pose Estimation (Q)
|
98% |
156
0.18 IPS |
|
|
Object Detection (SP)
|
100% |
29
2.33 IPS |
|
|
Object Detection (HP)
|
100% |
28
2.25 IPS |
|
|
Object Detection (Q)
|
83% |
26
2.08 IPS |
|
|
Face Detection (SP)
|
100% |
65
0.77 IPS |
|
|
Face Detection (HP)
|
100% |
98
1.16 IPS |
|
|
Face Detection (Q)
|
97% |
39
0.47 IPS |
|
|
Depth Estimation (SP)
|
100% |
74
0.57 IPS |
|
|
Depth Estimation (HP)
|
99% |
103
0.79 IPS |
|
|
Depth Estimation (Q)
|
63% |
56
0.51 IPS |
|
|
Style Transfer (SP)
|
100% |
272
0.35 IPS |
|
|
Style Transfer (HP)
|
100% |
249
0.32 IPS |
|
|
Style Transfer (Q)
|
98% |
258
0.33 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
69
2.53 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
70
2.57 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
62
2.31 IPS |
|
|
Text Classification (SP)
|
35% |
4
34.8 IPS |
|
|
Text Classification (HP)
|
35% |
4
36.5 IPS |
|
|
Text Classification (Q)
|
32% |
3
36.5 IPS |
|
|
Machine Translation (SP)
|
100% |
57
0.97 IPS |
|
|
Machine Translation (HP)
|
100% |
55
0.94 IPS |
|
|
Machine Translation (Q)
|
41% |
10
0.68 IPS |
