samsung SM-A055F
Geekbench AI Score
99
Single Precision Score
116
Half Precision Score
68
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 06 2025 04:04 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM MT6769V/CZ |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A055F |
| Model ID | samsung SM-A055F |
| Motherboard | a05m |
| CPU Information | |
|---|---|
| Name | ARM MT6769V/CZ |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 5.55 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
96
17.8 IPS |
|
|
Image Classification (HP)
|
100% |
121
22.5 IPS |
|
|
Image Classification (Q)
|
99% |
23
4.35 IPS |
|
|
Image Segmentation (SP)
|
100% |
91
1.48 IPS |
|
|
Image Segmentation (HP)
|
100% |
49
0.80 IPS |
|
|
Image Segmentation (Q)
|
98% |
39
0.63 IPS |
|
|
Pose Estimation (SP)
|
100% |
408
0.48 IPS |
|
|
Pose Estimation (HP)
|
98% |
860
1.01 IPS |
|
|
Pose Estimation (Q)
|
57% |
354
0.58 IPS |
|
|
Object Detection (SP)
|
100% |
69
5.49 IPS |
|
|
Object Detection (HP)
|
100% |
36
2.85 IPS |
|
|
Object Detection (Q)
|
80% |
29
2.36 IPS |
|
|
Face Detection (SP)
|
28% |
16
2.90 IPS |
|
|
Face Detection (HP)
|
100% |
99
1.17 IPS |
|
|
Face Detection (Q)
|
97% |
61
0.73 IPS |
|
|
Depth Estimation (SP)
|
100% |
137
1.05 IPS |
|
|
Depth Estimation (HP)
|
99% |
80
0.61 IPS |
|
|
Depth Estimation (Q)
|
57% |
77
0.84 IPS |
|
|
Style Transfer (SP)
|
100% |
349
0.45 IPS |
|
|
Style Transfer (HP)
|
100% |
150
0.19 IPS |
|
|
Style Transfer (Q)
|
98% |
600
0.77 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
206
7.61 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
435
16.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
129
4.79 IPS |
|
|
Text Classification (SP)
|
100% |
26
35.1 IPS |
|
|
Text Classification (HP)
|
100% |
53
71.0 IPS |
|
|
Text Classification (Q)
|
93% |
9
11.4 IPS |
|
|
Machine Translation (SP)
|
100% |
91
1.57 IPS |
|
|
Machine Translation (HP)
|
100% |
91
1.57 IPS |
|
|
Machine Translation (Q)
|
57% |
80
1.94 IPS |
