samsung SM-A366W
Geekbench AI Score
537
Single Precision Score
937
Half Precision Score
744
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 25 2025 06:08 PM |
| Views | 7 |
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% |
410
76.3 IPS |
|
|
Image Classification (HP)
|
100% |
692
128.8 IPS |
|
|
Image Classification (Q)
|
100% |
643
119.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
592
9.59 IPS |
|
|
Image Segmentation (HP)
|
100% |
1039
16.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
976
15.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1983
2.31 IPS |
|
|
Pose Estimation (HP)
|
99% |
3800
4.45 IPS |
|
|
Pose Estimation (Q)
|
96% |
3762
4.41 IPS |
|
|
Object Detection (SP)
|
100% |
360
28.5 IPS |
|
|
Object Detection (HP)
|
99% |
598
47.4 IPS |
|
|
Object Detection (Q)
|
87% |
563
45.2 IPS |
|
|
Face Detection (SP)
|
100% |
1018
12.1 IPS |
|
|
Face Detection (HP)
|
100% |
1999
23.8 IPS |
|
|
Face Detection (Q)
|
97% |
1745
20.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1171
9.02 IPS |
|
|
Depth Estimation (HP)
|
98% |
2304
17.8 IPS |
|
|
Depth Estimation (Q)
|
61% |
1707
16.8 IPS |
|
|
Style Transfer (SP)
|
100% |
2164
2.78 IPS |
|
|
Style Transfer (HP)
|
100% |
4541
5.84 IPS |
|
|
Style Transfer (Q)
|
98% |
4503
5.81 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
537
19.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1034
38.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
999
37.0 IPS |
|
|
Text Classification (SP)
|
35% |
22
214.4 IPS |
|
|
Text Classification (HP)
|
35% |
34
312.1 IPS |
|
|
Text Classification (Q)
|
33% |
26
309.6 IPS |
|
|
Machine Translation (SP)
|
100% |
380
6.54 IPS |
|
|
Machine Translation (HP)
|
97% |
435
7.52 IPS |
|
|
Machine Translation (Q)
|
43% |
113
6.42 IPS |
