samsung SM-A366W
Geekbench AI Score
533
Single Precision Score
942
Half Precision Score
747
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 22 2026 08:25 AM |
| 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% |
410
76.3 IPS |
|
|
Image Classification (HP)
|
100% |
700
130.2 IPS |
|
|
Image Classification (Q)
|
100% |
656
122.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
594
9.63 IPS |
|
|
Image Segmentation (HP)
|
100% |
1022
16.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
970
15.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1982
2.31 IPS |
|
|
Pose Estimation (HP)
|
99% |
3814
4.46 IPS |
|
|
Pose Estimation (Q)
|
96% |
3784
4.43 IPS |
|
|
Object Detection (SP)
|
100% |
352
27.9 IPS |
|
|
Object Detection (HP)
|
99% |
606
48.1 IPS |
|
|
Object Detection (Q)
|
87% |
568
45.6 IPS |
|
|
Face Detection (SP)
|
100% |
1038
12.3 IPS |
|
|
Face Detection (HP)
|
100% |
2033
24.2 IPS |
|
|
Face Detection (Q)
|
97% |
1781
21.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1166
8.98 IPS |
|
|
Depth Estimation (HP)
|
98% |
2323
18.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
1725
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2130
2.74 IPS |
|
|
Style Transfer (HP)
|
100% |
4454
5.73 IPS |
|
|
Style Transfer (Q)
|
98% |
4427
5.71 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
509
18.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1042
38.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1012
37.5 IPS |
|
|
Text Classification (SP)
|
35% |
22
216.6 IPS |
|
|
Text Classification (HP)
|
35% |
35
315.3 IPS |
|
|
Text Classification (Q)
|
33% |
26
315.5 IPS |
|
|
Machine Translation (SP)
|
100% |
380
6.54 IPS |
|
|
Machine Translation (HP)
|
97% |
436
7.54 IPS |
|
|
Machine Translation (Q)
|
43% |
112
6.37 IPS |
