samsung SM-A366W
Geekbench AI Score
907
Single Precision Score
899
Half Precision Score
1918
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 13 2026 07:10 PM |
| 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% |
444
82.6 IPS |
|
|
Image Classification (HP)
|
100% |
457
85.0 IPS |
|
|
Image Classification (Q)
|
100% |
1446
268.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
528
8.56 IPS |
|
|
Image Segmentation (HP)
|
100% |
543
8.80 IPS |
|
|
Image Segmentation (Q)
|
98% |
1655
26.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2021
2.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
1999
2.33 IPS |
|
|
Pose Estimation (Q)
|
84% |
3710
4.40 IPS |
|
|
Object Detection (SP)
|
100% |
456
36.2 IPS |
|
|
Object Detection (HP)
|
100% |
457
36.3 IPS |
|
|
Object Detection (Q)
|
83% |
1394
112.6 IPS |
|
|
Face Detection (SP)
|
100% |
1113
13.2 IPS |
|
|
Face Detection (HP)
|
100% |
1118
13.3 IPS |
|
|
Face Detection (Q)
|
95% |
3213
38.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1552
12.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
1546
11.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
3298
30.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3718
4.83 IPS |
|
|
Style Transfer (HP)
|
89% |
3611
4.69 IPS |
|
|
Style Transfer (Q)
|
98% |
7473
9.64 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
812
30.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
811
29.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1877
69.6 IPS |
|
|
Text Classification (SP)
|
100% |
465
620.3 IPS |
|
|
Text Classification (HP)
|
100% |
459
613.1 IPS |
|
|
Text Classification (Q)
|
88% |
852
1.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
724
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
658
11.3 IPS |
|
|
Machine Translation (Q)
|
50% |
432
15.3 IPS |
