samsung SM-A366W
Geekbench AI Score
534
Single Precision Score
937
Half Precision Score
745
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 22 2025 02:15 AM |
| Views | 4 |
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
75.2 IPS |
|
|
Image Classification (HP)
|
100% |
696
129.4 IPS |
|
|
Image Classification (Q)
|
100% |
654
121.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
582
9.44 IPS |
|
|
Image Segmentation (HP)
|
100% |
1041
16.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
961
15.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1965
2.29 IPS |
|
|
Pose Estimation (HP)
|
99% |
3767
4.41 IPS |
|
|
Pose Estimation (Q)
|
96% |
3739
4.38 IPS |
|
|
Object Detection (SP)
|
100% |
360
28.6 IPS |
|
|
Object Detection (HP)
|
99% |
603
47.8 IPS |
|
|
Object Detection (Q)
|
87% |
561
45.1 IPS |
|
|
Face Detection (SP)
|
100% |
1013
12.0 IPS |
|
|
Face Detection (HP)
|
100% |
2000
23.8 IPS |
|
|
Face Detection (Q)
|
97% |
1741
20.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1170
9.02 IPS |
|
|
Depth Estimation (HP)
|
98% |
2305
17.8 IPS |
|
|
Depth Estimation (Q)
|
61% |
1707
16.8 IPS |
|
|
Style Transfer (SP)
|
100% |
2155
2.77 IPS |
|
|
Style Transfer (HP)
|
100% |
4511
5.80 IPS |
|
|
Style Transfer (Q)
|
98% |
4484
5.78 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
535
19.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1024
37.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
999
37.0 IPS |
|
|
Text Classification (SP)
|
35% |
22
213.6 IPS |
|
|
Text Classification (HP)
|
35% |
34
312.1 IPS |
|
|
Text Classification (Q)
|
33% |
26
309.8 IPS |
|
|
Machine Translation (SP)
|
100% |
384
6.62 IPS |
|
|
Machine Translation (HP)
|
97% |
441
7.62 IPS |
|
|
Machine Translation (Q)
|
43% |
116
6.59 IPS |
