samsung SM-A366W
Geekbench AI Score
832
Single Precision Score
830
Half Precision Score
1483
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 18 2025 01:48 AM |
| Views | 2 |
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% |
451
83.8 IPS |
|
|
Image Classification (HP)
|
100% |
449
83.4 IPS |
|
|
Image Classification (Q)
|
100% |
1445
268.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
512
8.30 IPS |
|
|
Image Segmentation (HP)
|
100% |
518
8.39 IPS |
|
|
Image Segmentation (Q)
|
98% |
1665
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2002
2.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
1856
2.17 IPS |
|
|
Pose Estimation (Q)
|
84% |
3528
4.18 IPS |
|
|
Object Detection (SP)
|
100% |
418
33.2 IPS |
|
|
Object Detection (HP)
|
100% |
450
35.7 IPS |
|
|
Object Detection (Q)
|
83% |
1375
111.1 IPS |
|
|
Face Detection (SP)
|
100% |
1080
12.8 IPS |
|
|
Face Detection (HP)
|
100% |
1078
12.8 IPS |
|
|
Face Detection (Q)
|
95% |
3328
39.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
756
5.83 IPS |
|
|
Depth Estimation (HP)
|
99% |
771
5.94 IPS |
|
|
Depth Estimation (Q)
|
64% |
3413
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3610
4.69 IPS |
|
|
Style Transfer (HP)
|
89% |
3484
4.52 IPS |
|
|
Style Transfer (Q)
|
98% |
7369
9.50 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
789
29.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
825
30.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1951
72.3 IPS |
|
|
Text Classification (SP)
|
100% |
482
643.3 IPS |
|
|
Text Classification (HP)
|
100% |
479
639.8 IPS |
|
|
Text Classification (Q)
|
88% |
901
1.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
735
12.7 IPS |
|
|
Machine Translation (HP)
|
100% |
701
12.1 IPS |
|
|
Machine Translation (Q)
|
50% |
30
1.07 IPS |
