samsung SM-A366W
Geekbench AI Score
539
Single Precision Score
952
Half Precision Score
780
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | December 17 2025 02:43 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-A366W |
| Model ID | samsung SM-A366W |
| 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 | 5.25 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
410
76.2 IPS |
|
|
Image Classification (HP)
|
100% |
701
130.4 IPS |
|
|
Image Classification (Q)
|
100% |
658
122.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
585
9.49 IPS |
|
|
Image Segmentation (HP)
|
100% |
1039
16.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
977
15.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2000
2.33 IPS |
|
|
Pose Estimation (HP)
|
99% |
3818
4.47 IPS |
|
|
Pose Estimation (Q)
|
96% |
3750
4.39 IPS |
|
|
Object Detection (SP)
|
100% |
361
28.6 IPS |
|
|
Object Detection (HP)
|
99% |
608
48.2 IPS |
|
|
Object Detection (Q)
|
87% |
569
45.7 IPS |
|
|
Face Detection (SP)
|
100% |
1032
12.3 IPS |
|
|
Face Detection (HP)
|
100% |
2047
24.3 IPS |
|
|
Face Detection (Q)
|
97% |
1776
21.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1183
9.12 IPS |
|
|
Depth Estimation (HP)
|
98% |
2346
18.1 IPS |
|
|
Depth Estimation (Q)
|
61% |
1725
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2166
2.78 IPS |
|
|
Style Transfer (HP)
|
100% |
4548
5.85 IPS |
|
|
Style Transfer (Q)
|
98% |
4538
5.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
538
19.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1051
38.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1023
37.9 IPS |
|
|
Text Classification (SP)
|
35% |
22
216.5 IPS |
|
|
Text Classification (HP)
|
35% |
36
323.2 IPS |
|
|
Text Classification (Q)
|
33% |
27
322.7 IPS |
|
|
Machine Translation (SP)
|
100% |
383
6.60 IPS |
|
|
Machine Translation (HP)
|
97% |
439
7.59 IPS |
|
|
Machine Translation (Q)
|
43% |
159
9.02 IPS |
