samsung SM-A366W
Geekbench AI Score
541
Single Precision Score
944
Half Precision Score
754
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 28 2026 11:49 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
409
76.1 IPS |
|
|
Image Classification (HP)
|
100% |
703
130.8 IPS |
|
|
Image Classification (Q)
|
100% |
658
122.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
599
9.72 IPS |
|
|
Image Segmentation (HP)
|
100% |
1030
16.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
972
15.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1974
2.30 IPS |
|
|
Pose Estimation (HP)
|
99% |
3780
4.42 IPS |
|
|
Pose Estimation (Q)
|
96% |
3772
4.42 IPS |
|
|
Object Detection (SP)
|
100% |
361
28.6 IPS |
|
|
Object Detection (HP)
|
99% |
608
48.2 IPS |
|
|
Object Detection (Q)
|
87% |
569
45.7 IPS |
|
|
Face Detection (SP)
|
100% |
1042
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2023
24.0 IPS |
|
|
Face Detection (Q)
|
97% |
1800
21.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
1184
9.12 IPS |
|
|
Depth Estimation (HP)
|
98% |
2310
17.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
1718
16.9 IPS |
|
|
Style Transfer (SP)
|
100% |
2099
2.70 IPS |
|
|
Style Transfer (HP)
|
100% |
4559
5.86 IPS |
|
|
Style Transfer (Q)
|
98% |
4551
5.87 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
550
20.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1052
38.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1016
37.7 IPS |
|
|
Text Classification (SP)
|
35% |
23
220.4 IPS |
|
|
Text Classification (HP)
|
35% |
35
322.7 IPS |
|
|
Text Classification (Q)
|
33% |
26
317.8 IPS |
|
|
Machine Translation (SP)
|
100% |
378
6.51 IPS |
|
|
Machine Translation (HP)
|
97% |
434
7.50 IPS |
|
|
Machine Translation (Q)
|
43% |
117
6.65 IPS |
