samsung SM-A366W
Geekbench AI Score
532
Single Precision Score
935
Half Precision Score
742
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 04 2025 08:15 PM |
| Views | 6 |
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% |
404
75.0 IPS |
|
|
Image Classification (HP)
|
100% |
686
127.6 IPS |
|
|
Image Classification (Q)
|
100% |
634
117.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
589
9.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
1044
16.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
972
15.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1978
2.31 IPS |
|
|
Pose Estimation (HP)
|
99% |
3790
4.43 IPS |
|
|
Pose Estimation (Q)
|
96% |
3760
4.41 IPS |
|
|
Object Detection (SP)
|
100% |
353
28.0 IPS |
|
|
Object Detection (HP)
|
99% |
599
47.5 IPS |
|
|
Object Detection (Q)
|
87% |
564
45.3 IPS |
|
|
Face Detection (SP)
|
100% |
1020
12.1 IPS |
|
|
Face Detection (HP)
|
100% |
2017
24.0 IPS |
|
|
Face Detection (Q)
|
97% |
1743
20.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1167
8.99 IPS |
|
|
Depth Estimation (HP)
|
98% |
2298
17.8 IPS |
|
|
Depth Estimation (Q)
|
61% |
1700
16.7 IPS |
|
|
Style Transfer (SP)
|
100% |
2168
2.79 IPS |
|
|
Style Transfer (HP)
|
100% |
4537
5.83 IPS |
|
|
Style Transfer (Q)
|
98% |
4526
5.84 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
510
18.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1037
38.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1012
37.5 IPS |
|
|
Text Classification (SP)
|
35% |
22
213.4 IPS |
|
|
Text Classification (HP)
|
35% |
34
313.7 IPS |
|
|
Text Classification (Q)
|
33% |
26
309.6 IPS |
|
|
Machine Translation (SP)
|
100% |
381
6.57 IPS |
|
|
Machine Translation (HP)
|
97% |
424
7.34 IPS |
|
|
Machine Translation (Q)
|
43% |
110
6.27 IPS |
