WingTech WTATTRW2
Geekbench AI Score
179
Single Precision Score
172
Half Precision Score
187
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | kvnsalters |
| Upload Date | December 15 2025 01:00 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
80
14.9 IPS |
|
|
Image Classification (HP)
|
100% |
84
15.6 IPS |
|
|
Image Classification (Q)
|
100% |
128
23.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
113
1.84 IPS |
|
|
Image Segmentation (HP)
|
100% |
113
1.83 IPS |
|
|
Image Segmentation (Q)
|
98% |
174
2.83 IPS |
|
|
Pose Estimation (SP)
|
100% |
397
0.46 IPS |
|
|
Pose Estimation (HP)
|
100% |
250
0.29 IPS |
|
|
Pose Estimation (Q)
|
84% |
176
0.21 IPS |
|
|
Object Detection (SP)
|
100% |
86
6.83 IPS |
|
|
Object Detection (HP)
|
100% |
90
7.17 IPS |
|
|
Object Detection (Q)
|
83% |
133
10.7 IPS |
|
|
Face Detection (SP)
|
100% |
220
2.61 IPS |
|
|
Face Detection (HP)
|
100% |
226
2.69 IPS |
|
|
Face Detection (Q)
|
95% |
351
4.19 IPS |
|
|
Depth Estimation (SP)
|
100% |
295
2.28 IPS |
|
|
Depth Estimation (HP)
|
99% |
285
2.20 IPS |
|
|
Depth Estimation (Q)
|
64% |
297
2.72 IPS |
|
|
Style Transfer (SP)
|
89% |
771
1.00 IPS |
|
|
Style Transfer (HP)
|
89% |
771
1.00 IPS |
|
|
Style Transfer (Q)
|
98% |
722
0.93 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
154
5.69 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
151
5.57 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
169
6.26 IPS |
|
|
Text Classification (SP)
|
100% |
95
126.9 IPS |
|
|
Text Classification (HP)
|
100% |
93
123.5 IPS |
|
|
Text Classification (Q)
|
88% |
113
152.3 IPS |
|
|
Machine Translation (SP)
|
100% |
150
2.58 IPS |
|
|
Machine Translation (HP)
|
100% |
154
2.65 IPS |
|
|
Machine Translation (Q)
|
50% |
73
2.58 IPS |
