samsung SM-A366W
Geekbench AI Score
925
Single Precision Score
1662
Half Precision Score
2105
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 05 2026 12:00 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
84.9 IPS |
|
|
Image Classification (HP)
|
100% |
937
174.2 IPS |
|
|
Image Classification (Q)
|
99% |
1442
269.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
530
8.59 IPS |
|
|
Image Segmentation (HP)
|
100% |
1040
16.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1667
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2018
2.35 IPS |
|
|
Pose Estimation (HP)
|
92% |
4322
5.08 IPS |
|
|
Pose Estimation (Q)
|
96% |
3816
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
457
36.3 IPS |
|
|
Object Detection (HP)
|
97% |
909
72.3 IPS |
|
|
Object Detection (Q)
|
85% |
1392
112.2 IPS |
|
|
Face Detection (SP)
|
100% |
1147
13.6 IPS |
|
|
Face Detection (HP)
|
100% |
2141
25.4 IPS |
|
|
Face Detection (Q)
|
97% |
3445
41.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1596
12.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
3215
24.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
3420
31.6 IPS |
|
|
Style Transfer (SP)
|
89% |
3710
4.82 IPS |
|
|
Style Transfer (HP)
|
88% |
4839
6.28 IPS |
|
|
Style Transfer (Q)
|
98% |
8563
11.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
848
31.3 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1718
63.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2079
77.0 IPS |
|
|
Text Classification (SP)
|
100% |
493
657.4 IPS |
|
|
Text Classification (HP)
|
100% |
808
1.08 KIPS |
|
|
Text Classification (Q)
|
93% |
928
1.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
729
12.6 IPS |
|
|
Machine Translation (HP)
|
96% |
909
15.7 IPS |
|
|
Machine Translation (Q)
|
55% |
690
18.5 IPS |
