samsung SM-A366W
Geekbench AI Score
922
Single Precision Score
920
Half Precision Score
1947
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | October 16 2025 02:21 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
454
84.4 IPS |
|
|
Image Classification (HP)
|
100% |
459
85.3 IPS |
|
|
Image Classification (Q)
|
100% |
1447
269.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
542
8.78 IPS |
|
|
Image Segmentation (HP)
|
100% |
537
8.71 IPS |
|
|
Image Segmentation (Q)
|
98% |
1669
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2030
2.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
2009
2.34 IPS |
|
|
Pose Estimation (Q)
|
84% |
3770
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
457
36.2 IPS |
|
|
Object Detection (HP)
|
100% |
455
36.1 IPS |
|
|
Object Detection (Q)
|
83% |
1338
108.1 IPS |
|
|
Face Detection (SP)
|
100% |
1136
13.5 IPS |
|
|
Face Detection (HP)
|
100% |
1144
13.6 IPS |
|
|
Face Detection (Q)
|
95% |
3389
40.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
1572
12.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1551
11.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
3285
30.1 IPS |
|
|
Style Transfer (SP)
|
89% |
3719
4.83 IPS |
|
|
Style Transfer (HP)
|
89% |
3662
4.75 IPS |
|
|
Style Transfer (Q)
|
98% |
8260
10.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
867
32.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
866
32.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1887
69.9 IPS |
|
|
Text Classification (SP)
|
100% |
462
616.4 IPS |
|
|
Text Classification (HP)
|
100% |
489
652.8 IPS |
|
|
Text Classification (Q)
|
88% |
920
1.24 KIPS |
|
|
Machine Translation (SP)
|
100% |
736
12.7 IPS |
|
|
Machine Translation (HP)
|
100% |
706
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
403
14.3 IPS |
