samsung SM-A366W
Geekbench AI Score
535
Single Precision Score
939
Half Precision Score
745
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 03 2026 02:47 PM |
| Views | 6 |
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% |
407
75.6 IPS |
|
|
Image Classification (HP)
|
100% |
685
127.4 IPS |
|
|
Image Classification (Q)
|
100% |
640
118.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
581
9.41 IPS |
|
|
Image Segmentation (HP)
|
100% |
1016
16.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
965
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1985
2.32 IPS |
|
|
Pose Estimation (HP)
|
99% |
3800
4.45 IPS |
|
|
Pose Estimation (Q)
|
96% |
3766
4.41 IPS |
|
|
Object Detection (SP)
|
100% |
359
28.5 IPS |
|
|
Object Detection (HP)
|
99% |
601
47.6 IPS |
|
|
Object Detection (Q)
|
87% |
574
46.1 IPS |
|
|
Face Detection (SP)
|
100% |
1038
12.3 IPS |
|
|
Face Detection (HP)
|
100% |
2031
24.1 IPS |
|
|
Face Detection (Q)
|
97% |
1771
21.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1174
9.04 IPS |
|
|
Depth Estimation (HP)
|
98% |
2305
17.8 IPS |
|
|
Depth Estimation (Q)
|
61% |
1724
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2151
2.77 IPS |
|
|
Style Transfer (HP)
|
100% |
4543
5.84 IPS |
|
|
Style Transfer (Q)
|
98% |
4529
5.84 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
528
19.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1032
38.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
991
36.7 IPS |
|
|
Text Classification (SP)
|
35% |
22
218.1 IPS |
|
|
Text Classification (HP)
|
35% |
34
312.6 IPS |
|
|
Text Classification (Q)
|
33% |
26
314.4 IPS |
|
|
Machine Translation (SP)
|
100% |
376
6.48 IPS |
|
|
Machine Translation (HP)
|
97% |
453
7.83 IPS |
|
|
Machine Translation (Q)
|
43% |
112
6.38 IPS |
