samsung SM-A366W
Geekbench AI Score
539
Single Precision Score
950
Half Precision Score
752
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | December 16 2025 03:50 PM |
| Views | 5 |
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% |
411
76.5 IPS |
|
|
Image Classification (HP)
|
100% |
714
132.8 IPS |
|
|
Image Classification (Q)
|
100% |
655
121.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
596
9.65 IPS |
|
|
Image Segmentation (HP)
|
100% |
1031
16.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
972
15.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1995
2.33 IPS |
|
|
Pose Estimation (HP)
|
99% |
3824
4.48 IPS |
|
|
Pose Estimation (Q)
|
96% |
3757
4.40 IPS |
|
|
Object Detection (SP)
|
100% |
359
28.5 IPS |
|
|
Object Detection (HP)
|
99% |
605
48.0 IPS |
|
|
Object Detection (Q)
|
87% |
572
46.0 IPS |
|
|
Face Detection (SP)
|
100% |
1039
12.3 IPS |
|
|
Face Detection (HP)
|
100% |
2032
24.1 IPS |
|
|
Face Detection (Q)
|
97% |
1777
21.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1180
9.09 IPS |
|
|
Depth Estimation (HP)
|
98% |
2331
18.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
1727
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2165
2.78 IPS |
|
|
Style Transfer (HP)
|
100% |
4567
5.87 IPS |
|
|
Style Transfer (Q)
|
98% |
4521
5.83 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
509
18.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1058
39.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1012
37.5 IPS |
|
|
Text Classification (SP)
|
35% |
23
222.3 IPS |
|
|
Text Classification (HP)
|
35% |
35
315.3 IPS |
|
|
Text Classification (Q)
|
33% |
27
324.8 IPS |
|
|
Machine Translation (SP)
|
100% |
380
6.55 IPS |
|
|
Machine Translation (HP)
|
97% |
440
7.61 IPS |
|
|
Machine Translation (Q)
|
43% |
112
6.39 IPS |
