samsung SM-A366W
Geekbench AI Score
931
Single Precision Score
1670
Half Precision Score
2096
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 22 2026 08:20 AM |
| Views | 4 |
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% |
459
85.4 IPS |
|
|
Image Classification (HP)
|
100% |
945
175.7 IPS |
|
|
Image Classification (Q)
|
99% |
1444
269.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
530
8.60 IPS |
|
|
Image Segmentation (HP)
|
100% |
1054
17.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1690
27.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2023
2.36 IPS |
|
|
Pose Estimation (HP)
|
92% |
4322
5.08 IPS |
|
|
Pose Estimation (Q)
|
96% |
3820
4.48 IPS |
|
|
Object Detection (SP)
|
100% |
463
36.7 IPS |
|
|
Object Detection (HP)
|
97% |
922
73.4 IPS |
|
|
Object Detection (Q)
|
85% |
1404
113.1 IPS |
|
|
Face Detection (SP)
|
100% |
1154
13.7 IPS |
|
|
Face Detection (HP)
|
100% |
2181
25.9 IPS |
|
|
Face Detection (Q)
|
97% |
3461
41.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1597
12.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
3241
25.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
3439
31.7 IPS |
|
|
Style Transfer (SP)
|
89% |
3717
4.82 IPS |
|
|
Style Transfer (HP)
|
88% |
4544
5.90 IPS |
|
|
Style Transfer (Q)
|
98% |
8295
10.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
865
31.9 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1775
66.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2089
77.4 IPS |
|
|
Text Classification (SP)
|
100% |
495
661.1 IPS |
|
|
Text Classification (HP)
|
100% |
813
1.09 KIPS |
|
|
Text Classification (Q)
|
93% |
943
1.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
737
12.7 IPS |
|
|
Machine Translation (HP)
|
96% |
919
15.9 IPS |
|
|
Machine Translation (Q)
|
55% |
644
17.3 IPS |
