samsung SM-A366W
Geekbench AI Score
536
Single Precision Score
947
Half Precision Score
748
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | October 01 2025 05:51 PM |
| Views | 6 |
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% |
676
125.7 IPS |
|
|
Image Classification (Q)
|
100% |
650
120.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
594
9.63 IPS |
|
|
Image Segmentation (HP)
|
100% |
1078
17.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
966
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1984
2.31 IPS |
|
|
Pose Estimation (HP)
|
99% |
3804
4.45 IPS |
|
|
Pose Estimation (Q)
|
96% |
3750
4.39 IPS |
|
|
Object Detection (SP)
|
100% |
353
28.0 IPS |
|
|
Object Detection (HP)
|
99% |
607
48.1 IPS |
|
|
Object Detection (Q)
|
87% |
571
45.9 IPS |
|
|
Face Detection (SP)
|
100% |
1039
12.3 IPS |
|
|
Face Detection (HP)
|
100% |
2020
24.0 IPS |
|
|
Face Detection (Q)
|
97% |
1769
21.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1181
9.10 IPS |
|
|
Depth Estimation (HP)
|
98% |
2316
17.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
1737
17.1 IPS |
|
|
Style Transfer (SP)
|
100% |
2171
2.79 IPS |
|
|
Style Transfer (HP)
|
100% |
4539
5.84 IPS |
|
|
Style Transfer (Q)
|
98% |
4535
5.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
515
19.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1058
39.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1003
37.2 IPS |
|
|
Text Classification (SP)
|
35% |
22
218.1 IPS |
|
|
Text Classification (HP)
|
35% |
35
320.2 IPS |
|
|
Text Classification (Q)
|
33% |
26
314.6 IPS |
|
|
Machine Translation (SP)
|
100% |
382
6.57 IPS |
|
|
Machine Translation (HP)
|
97% |
443
7.65 IPS |
|
|
Machine Translation (Q)
|
43% |
113
6.42 IPS |
