samsung SM-A366W
Geekbench AI Score
532
Single Precision Score
923
Half Precision Score
736
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 11 2025 02:34 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 5.16 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
402
74.8 IPS |
|
|
Image Classification (HP)
|
100% |
678
126.1 IPS |
|
|
Image Classification (Q)
|
100% |
643
119.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
589
9.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
1013
16.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
973
15.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1975
2.30 IPS |
|
|
Pose Estimation (HP)
|
99% |
3810
4.46 IPS |
|
|
Pose Estimation (Q)
|
96% |
3765
4.41 IPS |
|
|
Object Detection (SP)
|
100% |
346
27.4 IPS |
|
|
Object Detection (HP)
|
99% |
597
47.4 IPS |
|
|
Object Detection (Q)
|
87% |
562
45.2 IPS |
|
|
Face Detection (SP)
|
100% |
1027
12.2 IPS |
|
|
Face Detection (HP)
|
100% |
2031
24.1 IPS |
|
|
Face Detection (Q)
|
97% |
1758
21.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
1163
8.96 IPS |
|
|
Depth Estimation (HP)
|
98% |
2297
17.7 IPS |
|
|
Depth Estimation (Q)
|
61% |
1702
16.8 IPS |
|
|
Style Transfer (SP)
|
100% |
2094
2.69 IPS |
|
|
Style Transfer (HP)
|
100% |
4358
5.60 IPS |
|
|
Style Transfer (Q)
|
98% |
4334
5.59 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
541
20.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
998
36.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
982
36.4 IPS |
|
|
Text Classification (SP)
|
35% |
22
213.6 IPS |
|
|
Text Classification (HP)
|
35% |
34
309.5 IPS |
|
|
Text Classification (Q)
|
33% |
26
308.3 IPS |
|
|
Machine Translation (SP)
|
100% |
378
6.51 IPS |
|
|
Machine Translation (HP)
|
97% |
419
7.25 IPS |
|
|
Machine Translation (Q)
|
43% |
107
6.08 IPS |
