samsung SM-A366W
Geekbench AI Score
852
Single Precision Score
851
Half Precision Score
1529
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 10 2025 12:35 PM |
| 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% |
453
84.2 IPS |
|
|
Image Classification (HP)
|
100% |
444
82.5 IPS |
|
|
Image Classification (Q)
|
100% |
1433
266.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
511
8.28 IPS |
|
|
Image Segmentation (HP)
|
100% |
530
8.59 IPS |
|
|
Image Segmentation (Q)
|
98% |
1662
27.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2037
2.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
1986
2.32 IPS |
|
|
Pose Estimation (Q)
|
84% |
3766
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
440
34.9 IPS |
|
|
Object Detection (HP)
|
100% |
453
35.9 IPS |
|
|
Object Detection (Q)
|
83% |
1372
110.8 IPS |
|
|
Face Detection (SP)
|
100% |
1106
13.1 IPS |
|
|
Face Detection (HP)
|
100% |
1108
13.2 IPS |
|
|
Face Detection (Q)
|
95% |
3381
40.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
789
6.08 IPS |
|
|
Depth Estimation (HP)
|
99% |
786
6.06 IPS |
|
|
Depth Estimation (Q)
|
64% |
3408
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3671
4.77 IPS |
|
|
Style Transfer (HP)
|
89% |
3680
4.78 IPS |
|
|
Style Transfer (Q)
|
98% |
8626
11.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
862
31.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
861
31.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2034
75.4 IPS |
|
|
Text Classification (SP)
|
100% |
492
656.7 IPS |
|
|
Text Classification (HP)
|
100% |
488
651.5 IPS |
|
|
Text Classification (Q)
|
88% |
907
1.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
719
12.4 IPS |
|
|
Machine Translation (HP)
|
100% |
703
12.1 IPS |
|
|
Machine Translation (Q)
|
50% |
31
1.11 IPS |
