samsung SM-A366W
Geekbench AI Score
926
Single Precision Score
1628
Half Precision Score
2018
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 01 2026 09:46 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
465
86.5 IPS |
|
|
Image Classification (HP)
|
100% |
943
175.3 IPS |
|
|
Image Classification (Q)
|
99% |
1436
267.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
541
8.77 IPS |
|
|
Image Segmentation (HP)
|
100% |
1047
17.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
1666
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2017
2.35 IPS |
|
|
Pose Estimation (HP)
|
92% |
4224
4.96 IPS |
|
|
Pose Estimation (Q)
|
96% |
3808
4.46 IPS |
|
|
Object Detection (SP)
|
100% |
458
36.3 IPS |
|
|
Object Detection (HP)
|
97% |
909
72.4 IPS |
|
|
Object Detection (Q)
|
85% |
1390
112.0 IPS |
|
|
Face Detection (SP)
|
100% |
1136
13.5 IPS |
|
|
Face Detection (HP)
|
100% |
2166
25.7 IPS |
|
|
Face Detection (Q)
|
97% |
3447
41.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1589
12.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
3091
23.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
3159
29.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3710
4.82 IPS |
|
|
Style Transfer (HP)
|
88% |
4486
5.82 IPS |
|
|
Style Transfer (Q)
|
98% |
7544
9.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
850
31.4 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1736
64.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2028
75.1 IPS |
|
|
Text Classification (SP)
|
100% |
480
640.2 IPS |
|
|
Text Classification (HP)
|
100% |
780
1.04 KIPS |
|
|
Text Classification (Q)
|
93% |
912
1.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
735
12.7 IPS |
|
|
Machine Translation (HP)
|
96% |
853
14.7 IPS |
|
|
Machine Translation (Q)
|
55% |
584
15.7 IPS |
