samsung SM-A366W
Geekbench AI Score
538
Single Precision Score
945
Half Precision Score
753
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | December 12 2025 03:17 AM |
| Views | 8 |
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% |
403
74.9 IPS |
|
|
Image Classification (HP)
|
100% |
686
127.6 IPS |
|
|
Image Classification (Q)
|
100% |
656
122.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
591
9.59 IPS |
|
|
Image Segmentation (HP)
|
100% |
1072
17.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
973
15.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1981
2.31 IPS |
|
|
Pose Estimation (HP)
|
99% |
3821
4.47 IPS |
|
|
Pose Estimation (Q)
|
96% |
3772
4.42 IPS |
|
|
Object Detection (SP)
|
100% |
360
28.5 IPS |
|
|
Object Detection (HP)
|
99% |
602
47.8 IPS |
|
|
Object Detection (Q)
|
87% |
568
45.6 IPS |
|
|
Face Detection (SP)
|
100% |
1044
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2055
24.4 IPS |
|
|
Face Detection (Q)
|
97% |
1798
21.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1189
9.16 IPS |
|
|
Depth Estimation (HP)
|
98% |
2324
18.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
1742
17.2 IPS |
|
|
Style Transfer (SP)
|
100% |
2125
2.73 IPS |
|
|
Style Transfer (HP)
|
100% |
4564
5.87 IPS |
|
|
Style Transfer (Q)
|
98% |
4550
5.87 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
551
20.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1051
38.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1021
37.8 IPS |
|
|
Text Classification (SP)
|
35% |
22
215.2 IPS |
|
|
Text Classification (HP)
|
35% |
34
313.5 IPS |
|
|
Text Classification (Q)
|
33% |
26
309.9 IPS |
|
|
Machine Translation (SP)
|
100% |
381
6.57 IPS |
|
|
Machine Translation (HP)
|
97% |
435
7.51 IPS |
|
|
Machine Translation (Q)
|
43% |
114
6.46 IPS |
