samsung SM-A366W
Geekbench AI Score
763
Single Precision Score
834
Half Precision Score
1436
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 02 2025 02:43 AM |
| Views | 5 |
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% |
187
34.9 IPS |
|
|
Image Classification (HP)
|
100% |
442
82.2 IPS |
|
|
Image Classification (Q)
|
100% |
1395
259.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
518
8.40 IPS |
|
|
Image Segmentation (HP)
|
100% |
522
8.47 IPS |
|
|
Image Segmentation (Q)
|
98% |
1423
23.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1998
2.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
1883
2.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
3226
3.83 IPS |
|
|
Object Detection (SP)
|
100% |
424
33.6 IPS |
|
|
Object Detection (HP)
|
100% |
452
35.9 IPS |
|
|
Object Detection (Q)
|
83% |
1388
112.1 IPS |
|
|
Face Detection (SP)
|
100% |
1093
13.0 IPS |
|
|
Face Detection (HP)
|
100% |
1087
12.9 IPS |
|
|
Face Detection (Q)
|
95% |
3379
40.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
767
5.91 IPS |
|
|
Depth Estimation (HP)
|
99% |
783
6.03 IPS |
|
|
Depth Estimation (Q)
|
64% |
3411
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3645
4.73 IPS |
|
|
Style Transfer (HP)
|
89% |
3668
4.76 IPS |
|
|
Style Transfer (Q)
|
98% |
7372
9.51 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
814
30.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
853
31.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1958
72.6 IPS |
|
|
Text Classification (SP)
|
100% |
484
645.6 IPS |
|
|
Text Classification (HP)
|
100% |
465
620.8 IPS |
|
|
Text Classification (Q)
|
88% |
817
1.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
685
11.8 IPS |
|
|
Machine Translation (HP)
|
100% |
672
11.6 IPS |
|
|
Machine Translation (Q)
|
50% |
31
1.09 IPS |
