samsung SM-A366E
Geekbench AI Score
536
Single Precision Score
954
Half Precision Score
745
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | epicgeek |
| Upload Date | March 10 2026 11:14 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-A366E |
| Model ID | samsung SM-A366E |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.21 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
415
77.1 IPS |
|
|
Image Classification (HP)
|
100% |
703
130.8 IPS |
|
|
Image Classification (Q)
|
100% |
651
121.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
582
9.44 IPS |
|
|
Image Segmentation (HP)
|
100% |
1034
16.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
979
15.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2001
2.34 IPS |
|
|
Pose Estimation (HP)
|
99% |
3820
4.47 IPS |
|
|
Pose Estimation (Q)
|
96% |
3781
4.43 IPS |
|
|
Object Detection (SP)
|
100% |
357
28.3 IPS |
|
|
Object Detection (HP)
|
99% |
606
48.1 IPS |
|
|
Object Detection (Q)
|
87% |
576
46.2 IPS |
|
|
Face Detection (SP)
|
100% |
1032
12.3 IPS |
|
|
Face Detection (HP)
|
100% |
2036
24.2 IPS |
|
|
Face Detection (Q)
|
97% |
1783
21.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1180
9.09 IPS |
|
|
Depth Estimation (HP)
|
98% |
2335
18.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
1719
16.9 IPS |
|
|
Style Transfer (SP)
|
100% |
2159
2.77 IPS |
|
|
Style Transfer (HP)
|
100% |
4391
5.64 IPS |
|
|
Style Transfer (Q)
|
98% |
4341
5.60 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
526
19.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1049
38.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1008
37.4 IPS |
|
|
Text Classification (SP)
|
35% |
22
218.1 IPS |
|
|
Text Classification (HP)
|
35% |
35
316.2 IPS |
|
|
Text Classification (Q)
|
33% |
26
313.8 IPS |
|
|
Machine Translation (SP)
|
100% |
374
6.44 IPS |
|
|
Machine Translation (HP)
|
97% |
488
8.44 IPS |
|
|
Machine Translation (Q)
|
43% |
110
6.26 IPS |
