samsung SM-A366W
Geekbench AI Score
539
Single Precision Score
943
Half Precision Score
754
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 07 2026 08:03 AM |
| Views | 4 |
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% |
408
75.9 IPS |
|
|
Image Classification (HP)
|
100% |
704
131.0 IPS |
|
|
Image Classification (Q)
|
100% |
670
124.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
595
9.64 IPS |
|
|
Image Segmentation (HP)
|
100% |
1026
16.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
960
15.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1986
2.32 IPS |
|
|
Pose Estimation (HP)
|
99% |
3790
4.43 IPS |
|
|
Pose Estimation (Q)
|
96% |
3768
4.41 IPS |
|
|
Object Detection (SP)
|
100% |
361
28.6 IPS |
|
|
Object Detection (HP)
|
99% |
605
48.0 IPS |
|
|
Object Detection (Q)
|
87% |
571
45.9 IPS |
|
|
Face Detection (SP)
|
100% |
1040
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2018
24.0 IPS |
|
|
Face Detection (Q)
|
97% |
1769
21.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1182
9.11 IPS |
|
|
Depth Estimation (HP)
|
98% |
2331
18.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
1717
16.9 IPS |
|
|
Style Transfer (SP)
|
100% |
2176
2.80 IPS |
|
|
Style Transfer (HP)
|
100% |
4556
5.86 IPS |
|
|
Style Transfer (Q)
|
98% |
4534
5.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
540
20.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1041
38.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1013
37.5 IPS |
|
|
Text Classification (SP)
|
35% |
22
216.7 IPS |
|
|
Text Classification (HP)
|
35% |
35
315.4 IPS |
|
|
Text Classification (Q)
|
33% |
27
319.9 IPS |
|
|
Machine Translation (SP)
|
100% |
379
6.53 IPS |
|
|
Machine Translation (HP)
|
97% |
433
7.48 IPS |
|
|
Machine Translation (Q)
|
43% |
114
6.49 IPS |
