Wingtech TMRV07P5G
Geekbench AI Score
355
Single Precision Score
611
Half Precision Score
555
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | Kovboy |
| Upload Date | January 28 2026 09:57 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Wingtech TMRV07P5G |
| Model ID | Wingtech TMRV07P5G |
| Motherboard | S88823AA1 |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| 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 | 7.29 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
278
51.7 IPS |
|
|
Image Classification (HP)
|
100% |
441
82.1 IPS |
|
|
Image Classification (Q)
|
99% |
393
73.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
413
6.70 IPS |
|
|
Image Segmentation (HP)
|
100% |
751
12.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
645
10.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1461
1.70 IPS |
|
|
Pose Estimation (HP)
|
99% |
2774
3.24 IPS |
|
|
Pose Estimation (Q)
|
97% |
2730
3.20 IPS |
|
|
Object Detection (SP)
|
100% |
226
17.9 IPS |
|
|
Object Detection (HP)
|
99% |
348
27.6 IPS |
|
|
Object Detection (Q)
|
85% |
330
26.6 IPS |
|
|
Face Detection (SP)
|
100% |
743
8.83 IPS |
|
|
Face Detection (HP)
|
100% |
1260
15.0 IPS |
|
|
Face Detection (Q)
|
97% |
1113
13.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
831
6.40 IPS |
|
|
Depth Estimation (HP)
|
98% |
1673
12.9 IPS |
|
|
Depth Estimation (Q)
|
65% |
1389
12.5 IPS |
|
|
Style Transfer (SP)
|
100% |
1675
2.15 IPS |
|
|
Style Transfer (HP)
|
100% |
3737
4.80 IPS |
|
|
Style Transfer (Q)
|
98% |
3650
4.71 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
373
13.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
653
24.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
623
23.1 IPS |
|
|
Text Classification (SP)
|
35% |
13
130.0 IPS |
|
|
Text Classification (HP)
|
35% |
23
213.6 IPS |
|
|
Text Classification (Q)
|
35% |
23
208.8 IPS |
|
|
Machine Translation (SP)
|
100% |
170
2.92 IPS |
|
|
Machine Translation (HP)
|
97% |
192
3.33 IPS |
|
|
Machine Translation (Q)
|
64% |
151
3.09 IPS |
