TINNO U572AC
Geekbench AI Score
92
Single Precision Score
87
Half Precision Score
64
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | September 24 2025 06:05 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | TINNO U572AC |
| Model ID | TINNO U572AC |
| Motherboard | Cricket |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| 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 | 3.67 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
50
9.37 IPS |
|
|
Image Classification (HP)
|
100% |
47
8.72 IPS |
|
|
Image Classification (Q)
|
97% |
43
8.00 IPS |
|
|
Image Segmentation (SP)
|
100% |
75
1.21 IPS |
|
|
Image Segmentation (HP)
|
100% |
71
1.16 IPS |
|
|
Image Segmentation (Q)
|
98% |
65
1.06 IPS |
|
|
Pose Estimation (SP)
|
100% |
270
0.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
262
0.31 IPS |
|
|
Pose Estimation (Q)
|
98% |
255
0.30 IPS |
|
|
Object Detection (SP)
|
100% |
51
4.01 IPS |
|
|
Object Detection (HP)
|
100% |
49
3.91 IPS |
|
|
Object Detection (Q)
|
83% |
45
3.62 IPS |
|
|
Face Detection (SP)
|
100% |
139
1.65 IPS |
|
|
Face Detection (HP)
|
100% |
126
1.50 IPS |
|
|
Face Detection (Q)
|
97% |
81
0.96 IPS |
|
|
Depth Estimation (SP)
|
100% |
172
1.33 IPS |
|
|
Depth Estimation (HP)
|
99% |
201
1.55 IPS |
|
|
Depth Estimation (Q)
|
63% |
124
1.15 IPS |
|
|
Style Transfer (SP)
|
100% |
559
0.72 IPS |
|
|
Style Transfer (HP)
|
100% |
542
0.70 IPS |
|
|
Style Transfer (Q)
|
98% |
532
0.69 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
132
4.86 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
137
5.07 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
117
4.33 IPS |
|
|
Text Classification (SP)
|
35% |
6
53.9 IPS |
|
|
Text Classification (HP)
|
35% |
4
38.3 IPS |
|
|
Text Classification (Q)
|
32% |
4
56.3 IPS |
|
|
Machine Translation (SP)
|
100% |
83
1.42 IPS |
|
|
Machine Translation (HP)
|
100% |
83
1.42 IPS |
|
|
Machine Translation (Q)
|
41% |
15
1.00 IPS |
