samsung SM-A366W
Geekbench AI Score
532
Single Precision Score
933
Half Precision Score
741
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 24 2025 05:50 PM |
| Views | 2 |
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% |
404
75.1 IPS |
|
|
Image Classification (HP)
|
100% |
702
130.6 IPS |
|
|
Image Classification (Q)
|
100% |
648
120.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
593
9.61 IPS |
|
|
Image Segmentation (HP)
|
100% |
1057
17.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
986
16.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1968
2.30 IPS |
|
|
Pose Estimation (HP)
|
99% |
3822
4.47 IPS |
|
|
Pose Estimation (Q)
|
96% |
3777
4.43 IPS |
|
|
Object Detection (SP)
|
100% |
355
28.1 IPS |
|
|
Object Detection (HP)
|
99% |
598
47.4 IPS |
|
|
Object Detection (Q)
|
87% |
562
45.1 IPS |
|
|
Face Detection (SP)
|
100% |
1021
12.1 IPS |
|
|
Face Detection (HP)
|
100% |
2015
23.9 IPS |
|
|
Face Detection (Q)
|
97% |
1750
20.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
1154
8.89 IPS |
|
|
Depth Estimation (HP)
|
98% |
2279
17.6 IPS |
|
|
Depth Estimation (Q)
|
61% |
1708
16.8 IPS |
|
|
Style Transfer (SP)
|
100% |
2145
2.76 IPS |
|
|
Style Transfer (HP)
|
100% |
4452
5.72 IPS |
|
|
Style Transfer (Q)
|
98% |
4429
5.71 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
523
19.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
999
36.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
966
35.8 IPS |
|
|
Text Classification (SP)
|
35% |
22
218.4 IPS |
|
|
Text Classification (HP)
|
35% |
34
310.4 IPS |
|
|
Text Classification (Q)
|
33% |
26
310.2 IPS |
|
|
Machine Translation (SP)
|
100% |
376
6.47 IPS |
|
|
Machine Translation (HP)
|
97% |
425
7.34 IPS |
|
|
Machine Translation (Q)
|
43% |
112
6.36 IPS |
