samsung SM-S134DL
Geekbench AI Score
90
Single Precision Score
88
Half Precision Score
93
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 23 2024 04:53 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765V/CB |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | samsung SM-S134DL |
| Model ID | samsung SM-S134DL |
| Motherboard | a03su |
| CPU Information | |
|---|---|
| Name | ARM MT6765V/CB |
| 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 | 2.72 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
61
11.4 IPS |
|
|
Image Classification (HP)
|
100% |
55
10.3 IPS |
|
|
Image Classification (Q)
|
100% |
75
14.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
73
1.19 IPS |
|
|
Image Segmentation (HP)
|
100% |
67
1.09 IPS |
|
|
Image Segmentation (Q)
|
98% |
107
1.75 IPS |
|
|
Pose Estimation (SP)
|
100% |
261
0.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
243
0.28 IPS |
|
|
Pose Estimation (Q)
|
84% |
195
0.23 IPS |
|
|
Object Detection (SP)
|
100% |
45
3.56 IPS |
|
|
Object Detection (HP)
|
100% |
47
3.74 IPS |
|
|
Object Detection (Q)
|
83% |
58
4.70 IPS |
|
|
Face Detection (SP)
|
100% |
105
1.25 IPS |
|
|
Face Detection (HP)
|
100% |
106
1.26 IPS |
|
|
Face Detection (Q)
|
95% |
158
1.89 IPS |
|
|
Depth Estimation (SP)
|
100% |
155
1.19 IPS |
|
|
Depth Estimation (HP)
|
99% |
153
1.18 IPS |
|
|
Depth Estimation (Q)
|
64% |
167
1.53 IPS |
|
|
Style Transfer (SP)
|
89% |
489
0.64 IPS |
|
|
Style Transfer (HP)
|
89% |
543
0.71 IPS |
|
|
Style Transfer (Q)
|
98% |
511
0.66 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
65
2.40 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
65
2.40 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
89
3.31 IPS |
|
|
Text Classification (SP)
|
100% |
27
35.8 IPS |
|
|
Text Classification (HP)
|
100% |
28
37.4 IPS |
|
|
Text Classification (Q)
|
88% |
35
47.8 IPS |
|
|
Machine Translation (SP)
|
100% |
51
0.87 IPS |
|
|
Machine Translation (HP)
|
100% |
45
0.77 IPS |
|
|
Machine Translation (Q)
|
50% |
14
0.51 IPS |
