samsung SM-T227U
Geekbench AI Score
17
Single Precision Score
35
Half Precision Score
20
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | pawelknyc |
| Upload Date | January 20 2025 05:47 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM MT8768WT |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-T227U |
| Model ID | samsung SM-T227U |
| Motherboard | gta7lite |
| CPU Information | |
|---|---|
| Name | ARM MT8768WT |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.30 GHz |
| Memory Information | |
|---|---|
| Size | 2.67 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
24
4.47 IPS |
|
|
Image Classification (HP)
|
100% |
36
6.66 IPS |
|
|
Image Classification (Q)
|
99% |
34
6.42 IPS |
|
|
Image Segmentation (SP)
|
100% |
36
0.59 IPS |
|
|
Image Segmentation (HP)
|
100% |
45
0.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
45
0.73 IPS |
|
|
Pose Estimation (SP)
|
0
|
||
|
Pose Estimation (HP)
|
0
|
||
|
Pose Estimation (Q)
|
0
|
||
|
Object Detection (SP)
|
100% |
18
1.41 IPS |
|
|
Object Detection (HP)
|
100% |
26
2.05 IPS |
|
|
Object Detection (Q)
|
85% |
25
2.00 IPS |
|
|
Face Detection (SP)
|
100% |
72
0.86 IPS |
|
|
Face Detection (HP)
|
100% |
97
1.16 IPS |
|
|
Face Detection (Q)
|
97% |
91
1.09 IPS |
|
|
Depth Estimation (SP)
|
100% |
48
0.37 IPS |
|
|
Depth Estimation (HP)
|
99% |
75
0.58 IPS |
|
|
Depth Estimation (Q)
|
63% |
59
0.55 IPS |
|
|
Style Transfer (SP)
|
0
|
||
|
Style Transfer (HP)
|
100% |
162
0.21 IPS |
|
|
Style Transfer (Q)
|
0
|
||
|
Image Super-Resolution (SP)
|
100% |
21
0.77 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35
1.31 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
33
1.21 IPS |
|
|
Text Classification (SP)
|
100% |
34
45.8 IPS |
|
|
Text Classification (HP)
|
100% |
34
45.0 IPS |
|
|
Text Classification (Q)
|
91% |
50
67.6 IPS |
|
|
Machine Translation (SP)
|
100% |
57
0.98 IPS |
|
|
Machine Translation (HP)
|
100% |
57
0.99 IPS |
|
|
Machine Translation (Q)
|
57% |
49
1.21 IPS |
