samsung SM-A366W
Geekbench AI Score
922
Single Precision Score
916
Half Precision Score
1997
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 13 2026 02:19 PM |
| Views | 11 |
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
84.8 IPS |
|
|
Image Classification (HP)
|
100% |
450
83.7 IPS |
|
|
Image Classification (Q)
|
100% |
1438
267.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
531
8.60 IPS |
|
|
Image Segmentation (HP)
|
100% |
532
8.63 IPS |
|
|
Image Segmentation (Q)
|
98% |
1658
27.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2023
2.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
1977
2.31 IPS |
|
|
Pose Estimation (Q)
|
84% |
3766
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
453
35.9 IPS |
|
|
Object Detection (HP)
|
100% |
454
36.0 IPS |
|
|
Object Detection (Q)
|
83% |
1380
111.4 IPS |
|
|
Face Detection (SP)
|
100% |
1123
13.3 IPS |
|
|
Face Detection (HP)
|
100% |
1131
13.4 IPS |
|
|
Face Detection (Q)
|
95% |
3376
40.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1536
11.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
1551
12.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
3408
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3696
4.80 IPS |
|
|
Style Transfer (HP)
|
89% |
3710
4.82 IPS |
|
|
Style Transfer (Q)
|
98% |
8505
11.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
872
32.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
864
31.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2025
75.0 IPS |
|
|
Text Classification (SP)
|
100% |
494
659.2 IPS |
|
|
Text Classification (HP)
|
100% |
485
647.8 IPS |
|
|
Text Classification (Q)
|
88% |
928
1.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
733
12.6 IPS |
|
|
Machine Translation (HP)
|
100% |
712
12.3 IPS |
|
|
Machine Translation (Q)
|
50% |
443
15.7 IPS |
