samsung SM-A047F
Geekbench AI Score
61
Single Precision Score
78
Half Precision Score
72
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | October 08 2024 04:40 PM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM Samsung |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A047F |
| Model ID | samsung SM-A047F |
| Motherboard | exynos850 |
| Governor | energy_step |
| CPU Information | |
|---|---|
| Name | ARM Samsung |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3333 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 8 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 2.64 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
48
8.90 IPS |
|
|
Image Classification (HP)
|
100% |
66
12.3 IPS |
|
|
Image Classification (Q)
|
99% |
65
12.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
65
1.05 IPS |
|
|
Image Segmentation (HP)
|
100% |
88
1.42 IPS |
|
|
Image Segmentation (Q)
|
98% |
88
1.43 IPS |
|
|
Pose Estimation (SP)
|
100% |
31
0.04 IPS |
|
|
Pose Estimation (HP)
|
100% |
42
0.05 IPS |
|
|
Pose Estimation (Q)
|
96% |
42
0.05 IPS |
|
|
Object Detection (SP)
|
100% |
37
2.96 IPS |
|
|
Object Detection (HP)
|
100% |
53
4.20 IPS |
|
|
Object Detection (Q)
|
83% |
53
4.27 IPS |
|
|
Face Detection (SP)
|
100% |
148
1.75 IPS |
|
|
Face Detection (HP)
|
100% |
205
2.43 IPS |
|
|
Face Detection (Q)
|
97% |
196
2.33 IPS |
|
|
Depth Estimation (SP)
|
100% |
70
0.54 IPS |
|
|
Depth Estimation (HP)
|
99% |
91
0.70 IPS |
|
|
Depth Estimation (Q)
|
62% |
74
0.70 IPS |
|
|
Style Transfer (SP)
|
100% |
143
0.18 IPS |
|
|
Style Transfer (HP)
|
100% |
193
0.25 IPS |
|
|
Style Transfer (Q)
|
98% |
192
0.25 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
38
1.39 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
53
1.97 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
53
1.96 IPS |
|
|
Text Classification (SP)
|
100% |
45
59.7 IPS |
|
|
Text Classification (HP)
|
100% |
44
59.4 IPS |
|
|
Text Classification (Q)
|
91% |
46
61.5 IPS |
|
|
Machine Translation (SP)
|
100% |
81
1.39 IPS |
|
|
Machine Translation (HP)
|
100% |
82
1.41 IPS |
|
|
Machine Translation (Q)
|
57% |
49
1.19 IPS |
