samsung SM-A366W
Geekbench AI Score
826
Single Precision Score
832
Half Precision Score
1511
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 04 2025 08:10 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
449
83.5 IPS |
|
|
Image Classification (HP)
|
100% |
447
83.2 IPS |
|
|
Image Classification (Q)
|
100% |
1437
267.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
486
7.88 IPS |
|
|
Image Segmentation (HP)
|
100% |
519
8.41 IPS |
|
|
Image Segmentation (Q)
|
98% |
1659
27.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2005
2.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
1854
2.16 IPS |
|
|
Pose Estimation (Q)
|
84% |
3457
4.10 IPS |
|
|
Object Detection (SP)
|
100% |
425
33.7 IPS |
|
|
Object Detection (HP)
|
100% |
451
35.8 IPS |
|
|
Object Detection (Q)
|
83% |
1380
111.5 IPS |
|
|
Face Detection (SP)
|
100% |
1091
13.0 IPS |
|
|
Face Detection (HP)
|
100% |
1100
13.1 IPS |
|
|
Face Detection (Q)
|
95% |
3321
39.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
767
5.91 IPS |
|
|
Depth Estimation (HP)
|
99% |
790
6.08 IPS |
|
|
Depth Estimation (Q)
|
64% |
3412
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3636
4.72 IPS |
|
|
Style Transfer (HP)
|
89% |
3634
4.72 IPS |
|
|
Style Transfer (Q)
|
98% |
7306
9.42 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
771
28.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
802
29.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1943
72.0 IPS |
|
|
Text Classification (SP)
|
100% |
481
641.4 IPS |
|
|
Text Classification (HP)
|
100% |
475
633.9 IPS |
|
|
Text Classification (Q)
|
88% |
917
1.24 KIPS |
|
|
Machine Translation (SP)
|
100% |
713
12.3 IPS |
|
|
Machine Translation (HP)
|
100% |
686
11.8 IPS |
|
|
Machine Translation (Q)
|
50% |
37
1.33 IPS |
