samsung SM-A366W
Geekbench AI Score
531
Single Precision Score
920
Half Precision Score
733
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 07 2025 11:37 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 5.16 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
405
75.3 IPS |
|
|
Image Classification (HP)
|
100% |
683
127.0 IPS |
|
|
Image Classification (Q)
|
100% |
638
118.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
586
9.50 IPS |
|
|
Image Segmentation (HP)
|
100% |
1026
16.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
971
15.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1969
2.30 IPS |
|
|
Pose Estimation (HP)
|
99% |
3767
4.41 IPS |
|
|
Pose Estimation (Q)
|
96% |
3745
4.39 IPS |
|
|
Object Detection (SP)
|
100% |
357
28.3 IPS |
|
|
Object Detection (HP)
|
99% |
587
46.6 IPS |
|
|
Object Detection (Q)
|
87% |
551
44.2 IPS |
|
|
Face Detection (SP)
|
100% |
1022
12.1 IPS |
|
|
Face Detection (HP)
|
100% |
1997
23.7 IPS |
|
|
Face Detection (Q)
|
97% |
1758
21.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
1156
8.91 IPS |
|
|
Depth Estimation (HP)
|
98% |
2296
17.7 IPS |
|
|
Depth Estimation (Q)
|
61% |
1702
16.8 IPS |
|
|
Style Transfer (SP)
|
100% |
2029
2.61 IPS |
|
|
Style Transfer (HP)
|
100% |
4339
5.58 IPS |
|
|
Style Transfer (Q)
|
98% |
4313
5.56 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
538
19.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
995
36.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
975
36.1 IPS |
|
|
Text Classification (SP)
|
35% |
22
213.4 IPS |
|
|
Text Classification (HP)
|
35% |
34
309.7 IPS |
|
|
Text Classification (Q)
|
33% |
26
306.9 IPS |
|
|
Machine Translation (SP)
|
100% |
383
6.59 IPS |
|
|
Machine Translation (HP)
|
97% |
419
7.24 IPS |
|
|
Machine Translation (Q)
|
43% |
108
6.13 IPS |
