samsung SM-A366W
Geekbench AI Score
922
Single Precision Score
1649
Half Precision Score
2101
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 05 2026 09:40 AM |
| Views | 3 |
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% |
456
84.8 IPS |
|
|
Image Classification (HP)
|
100% |
943
175.3 IPS |
|
|
Image Classification (Q)
|
99% |
1438
268.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
545
8.83 IPS |
|
|
Image Segmentation (HP)
|
100% |
1008
16.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
1668
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2014
2.35 IPS |
|
|
Pose Estimation (HP)
|
92% |
4295
5.04 IPS |
|
|
Pose Estimation (Q)
|
96% |
3820
4.48 IPS |
|
|
Object Detection (SP)
|
100% |
455
36.1 IPS |
|
|
Object Detection (HP)
|
97% |
906
72.1 IPS |
|
|
Object Detection (Q)
|
85% |
1399
112.7 IPS |
|
|
Face Detection (SP)
|
100% |
1132
13.5 IPS |
|
|
Face Detection (HP)
|
100% |
2112
25.1 IPS |
|
|
Face Detection (Q)
|
97% |
3396
40.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
1598
12.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
3238
25.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
3416
31.5 IPS |
|
|
Style Transfer (SP)
|
89% |
3665
4.76 IPS |
|
|
Style Transfer (HP)
|
88% |
4589
5.96 IPS |
|
|
Style Transfer (Q)
|
98% |
8550
11.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
824
30.4 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1758
65.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2075
76.9 IPS |
|
|
Text Classification (SP)
|
100% |
496
662.4 IPS |
|
|
Text Classification (HP)
|
100% |
808
1.08 KIPS |
|
|
Text Classification (Q)
|
93% |
950
1.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
724
12.5 IPS |
|
|
Machine Translation (HP)
|
96% |
904
15.6 IPS |
|
|
Machine Translation (Q)
|
55% |
671
18.0 IPS |
