samsung SM-A366W
Geekbench AI Score
542
Single Precision Score
957
Half Precision Score
753
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 27 2026 12:29 PM |
| Views | 10 |
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
75.8 IPS |
|
|
Image Classification (HP)
|
100% |
708
131.6 IPS |
|
|
Image Classification (Q)
|
100% |
661
122.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
590
9.57 IPS |
|
|
Image Segmentation (HP)
|
100% |
1027
16.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
986
16.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1997
2.33 IPS |
|
|
Pose Estimation (HP)
|
99% |
3789
4.43 IPS |
|
|
Pose Estimation (Q)
|
96% |
3776
4.42 IPS |
|
|
Object Detection (SP)
|
100% |
359
28.5 IPS |
|
|
Object Detection (HP)
|
99% |
610
48.4 IPS |
|
|
Object Detection (Q)
|
87% |
566
45.4 IPS |
|
|
Face Detection (SP)
|
100% |
1040
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2022
24.0 IPS |
|
|
Face Detection (Q)
|
97% |
1766
21.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1181
9.10 IPS |
|
|
Depth Estimation (HP)
|
98% |
2335
18.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
1739
17.1 IPS |
|
|
Style Transfer (SP)
|
100% |
2171
2.79 IPS |
|
|
Style Transfer (HP)
|
100% |
4554
5.85 IPS |
|
|
Style Transfer (Q)
|
98% |
4542
5.86 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
535
19.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1044
38.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1023
37.9 IPS |
|
|
Text Classification (SP)
|
35% |
22
217.7 IPS |
|
|
Text Classification (HP)
|
35% |
35
313.9 IPS |
|
|
Text Classification (Q)
|
33% |
26
312.2 IPS |
|
|
Machine Translation (SP)
|
100% |
406
6.99 IPS |
|
|
Machine Translation (HP)
|
97% |
492
8.51 IPS |
|
|
Machine Translation (Q)
|
43% |
114
6.50 IPS |
