samsung SM-A366W
Geekbench AI Score
928
Single Precision Score
904
Half Precision Score
1954
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 08 2025 02:41 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% |
460
85.6 IPS |
|
|
Image Classification (HP)
|
100% |
458
85.3 IPS |
|
|
Image Classification (Q)
|
100% |
1446
269.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
541
8.77 IPS |
|
|
Image Segmentation (HP)
|
100% |
542
8.79 IPS |
|
|
Image Segmentation (Q)
|
98% |
1664
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2014
2.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
2013
2.35 IPS |
|
|
Pose Estimation (Q)
|
84% |
3769
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
454
36.0 IPS |
|
|
Object Detection (HP)
|
100% |
394
31.2 IPS |
|
|
Object Detection (Q)
|
83% |
1176
95.0 IPS |
|
|
Face Detection (SP)
|
100% |
1134
13.5 IPS |
|
|
Face Detection (HP)
|
100% |
1143
13.6 IPS |
|
|
Face Detection (Q)
|
95% |
3382
40.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1601
12.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
1563
12.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
3291
30.1 IPS |
|
|
Style Transfer (SP)
|
89% |
3697
4.80 IPS |
|
|
Style Transfer (HP)
|
89% |
3638
4.72 IPS |
|
|
Style Transfer (Q)
|
98% |
8288
10.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
864
31.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
879
32.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2037
75.5 IPS |
|
|
Text Classification (SP)
|
100% |
495
661.1 IPS |
|
|
Text Classification (HP)
|
100% |
491
655.3 IPS |
|
|
Text Classification (Q)
|
88% |
927
1.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
732
12.6 IPS |
|
|
Machine Translation (HP)
|
100% |
660
11.4 IPS |
|
|
Machine Translation (Q)
|
50% |
438
15.5 IPS |
