samsung SM-A366W
Geekbench AI Score
537
Single Precision Score
944
Half Precision Score
748
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 07 2025 03:15 AM |
| Views | 2 |
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% |
718
133.6 IPS |
|
|
Image Classification (Q)
|
100% |
658
122.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
585
9.48 IPS |
|
|
Image Segmentation (HP)
|
100% |
1038
16.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
963
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1997
2.33 IPS |
|
|
Pose Estimation (HP)
|
99% |
3798
4.45 IPS |
|
|
Pose Estimation (Q)
|
96% |
3775
4.42 IPS |
|
|
Object Detection (SP)
|
100% |
359
28.5 IPS |
|
|
Object Detection (HP)
|
99% |
606
48.1 IPS |
|
|
Object Detection (Q)
|
87% |
567
45.6 IPS |
|
|
Face Detection (SP)
|
100% |
1046
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2036
24.2 IPS |
|
|
Face Detection (Q)
|
97% |
1779
21.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1183
9.11 IPS |
|
|
Depth Estimation (HP)
|
98% |
2303
17.8 IPS |
|
|
Depth Estimation (Q)
|
61% |
1727
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2156
2.77 IPS |
|
|
Style Transfer (HP)
|
100% |
4553
5.85 IPS |
|
|
Style Transfer (Q)
|
98% |
4539
5.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
520
19.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1028
38.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
987
36.6 IPS |
|
|
Text Classification (SP)
|
35% |
22
215.7 IPS |
|
|
Text Classification (HP)
|
35% |
35
314.4 IPS |
|
|
Text Classification (Q)
|
33% |
27
319.8 IPS |
|
|
Machine Translation (SP)
|
100% |
387
6.67 IPS |
|
|
Machine Translation (HP)
|
97% |
427
7.38 IPS |
|
|
Machine Translation (Q)
|
43% |
109
6.22 IPS |
