samsung SM-A366W
Geekbench AI Score
927
Single Precision Score
925
Half Precision Score
1974
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 10 2026 11:55 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% |
448
83.4 IPS |
|
|
Image Classification (HP)
|
100% |
455
84.6 IPS |
|
|
Image Classification (Q)
|
100% |
1440
267.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
535
8.67 IPS |
|
|
Image Segmentation (HP)
|
100% |
539
8.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
1670
27.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2024
2.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
2044
2.38 IPS |
|
|
Pose Estimation (Q)
|
84% |
3765
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
457
36.2 IPS |
|
|
Object Detection (HP)
|
100% |
453
36.0 IPS |
|
|
Object Detection (Q)
|
83% |
1336
107.9 IPS |
|
|
Face Detection (SP)
|
100% |
1132
13.4 IPS |
|
|
Face Detection (HP)
|
100% |
1124
13.4 IPS |
|
|
Face Detection (Q)
|
95% |
3387
40.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1607
12.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
1608
12.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
3412
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3700
4.80 IPS |
|
|
Style Transfer (HP)
|
89% |
3722
4.83 IPS |
|
|
Style Transfer (Q)
|
98% |
8535
11.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
862
31.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
866
32.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2044
75.7 IPS |
|
|
Text Classification (SP)
|
100% |
498
664.5 IPS |
|
|
Text Classification (HP)
|
100% |
488
652.0 IPS |
|
|
Text Classification (Q)
|
88% |
916
1.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
735
12.7 IPS |
|
|
Machine Translation (HP)
|
100% |
713
12.3 IPS |
|
|
Machine Translation (Q)
|
50% |
403
14.3 IPS |
