samsung SM-A366W
Geekbench AI Score
783
Single Precision Score
855
Half Precision Score
1517
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 31 2025 07:52 PM |
| Views | 8 |
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% |
190
35.4 IPS |
|
|
Image Classification (HP)
|
100% |
446
82.9 IPS |
|
|
Image Classification (Q)
|
100% |
1430
266.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
515
8.35 IPS |
|
|
Image Segmentation (HP)
|
100% |
529
8.57 IPS |
|
|
Image Segmentation (Q)
|
98% |
1655
26.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2024
2.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
1994
2.33 IPS |
|
|
Pose Estimation (Q)
|
84% |
3669
4.35 IPS |
|
|
Object Detection (SP)
|
100% |
452
35.9 IPS |
|
|
Object Detection (HP)
|
100% |
453
35.9 IPS |
|
|
Object Detection (Q)
|
83% |
1370
110.7 IPS |
|
|
Face Detection (SP)
|
100% |
1107
13.1 IPS |
|
|
Face Detection (HP)
|
100% |
1109
13.2 IPS |
|
|
Face Detection (Q)
|
95% |
3356
40.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
778
5.99 IPS |
|
|
Depth Estimation (HP)
|
99% |
804
6.19 IPS |
|
|
Depth Estimation (Q)
|
64% |
3400
31.1 IPS |
|
|
Style Transfer (SP)
|
89% |
3673
4.77 IPS |
|
|
Style Transfer (HP)
|
89% |
3659
4.75 IPS |
|
|
Style Transfer (Q)
|
98% |
8614
11.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
859
31.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
865
31.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2030
75.2 IPS |
|
|
Text Classification (SP)
|
100% |
494
658.7 IPS |
|
|
Text Classification (HP)
|
100% |
490
654.3 IPS |
|
|
Text Classification (Q)
|
88% |
911
1.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
725
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
710
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
30
1.07 IPS |
