samsung SM-A366W
Geekbench AI Score
934
Single Precision Score
1660
Half Precision Score
2091
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 12 2026 09:03 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% |
456
84.7 IPS |
|
|
Image Classification (HP)
|
100% |
950
176.6 IPS |
|
|
Image Classification (Q)
|
99% |
1439
268.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
542
8.79 IPS |
|
|
Image Segmentation (HP)
|
100% |
1052
17.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1672
27.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2042
2.38 IPS |
|
|
Pose Estimation (HP)
|
92% |
4268
5.01 IPS |
|
|
Pose Estimation (Q)
|
96% |
3817
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
458
36.3 IPS |
|
|
Object Detection (HP)
|
97% |
849
67.6 IPS |
|
|
Object Detection (Q)
|
85% |
1298
104.6 IPS |
|
|
Face Detection (SP)
|
100% |
1148
13.6 IPS |
|
|
Face Detection (HP)
|
100% |
2180
25.9 IPS |
|
|
Face Detection (Q)
|
97% |
3456
41.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1628
12.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
3254
25.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
3311
30.6 IPS |
|
|
Style Transfer (SP)
|
89% |
3718
4.83 IPS |
|
|
Style Transfer (HP)
|
88% |
4607
5.98 IPS |
|
|
Style Transfer (Q)
|
98% |
8539
11.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
851
31.4 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1741
64.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2090
77.5 IPS |
|
|
Text Classification (SP)
|
100% |
497
663.2 IPS |
|
|
Text Classification (HP)
|
100% |
817
1.09 KIPS |
|
|
Text Classification (Q)
|
93% |
956
1.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
744
12.8 IPS |
|
|
Machine Translation (HP)
|
96% |
944
16.3 IPS |
|
|
Machine Translation (Q)
|
55% |
687
18.5 IPS |
