samsung SM-A366W
Geekbench AI Score
812
Single Precision Score
845
Half Precision Score
1532
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 02 2025 12:28 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 5.16 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
450
83.6 IPS |
|
|
Image Classification (HP)
|
100% |
446
82.9 IPS |
|
|
Image Classification (Q)
|
100% |
1438
267.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
520
8.43 IPS |
|
|
Image Segmentation (HP)
|
100% |
522
8.46 IPS |
|
|
Image Segmentation (Q)
|
98% |
1657
26.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2011
2.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
1975
2.30 IPS |
|
|
Pose Estimation (Q)
|
84% |
3766
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
423
33.6 IPS |
|
|
Object Detection (HP)
|
100% |
452
35.9 IPS |
|
|
Object Detection (Q)
|
83% |
1382
111.6 IPS |
|
|
Face Detection (SP)
|
100% |
758
9.00 IPS |
|
|
Face Detection (HP)
|
100% |
1109
13.2 IPS |
|
|
Face Detection (Q)
|
95% |
3367
40.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
780
6.01 IPS |
|
|
Depth Estimation (HP)
|
99% |
794
6.12 IPS |
|
|
Depth Estimation (Q)
|
64% |
3413
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3629
4.71 IPS |
|
|
Style Transfer (HP)
|
89% |
3602
4.68 IPS |
|
|
Style Transfer (Q)
|
98% |
7899
10.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
816
30.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
812
30.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2030
75.2 IPS |
|
|
Text Classification (SP)
|
100% |
499
666.3 IPS |
|
|
Text Classification (HP)
|
100% |
491
654.7 IPS |
|
|
Text Classification (Q)
|
88% |
922
1.24 KIPS |
|
|
Machine Translation (SP)
|
100% |
720
12.4 IPS |
|
|
Machine Translation (HP)
|
100% |
708
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
34
1.19 IPS |
