samsung SM-A366W
Geekbench AI Score
814
Single Precision Score
804
Half Precision Score
1383
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 16 2025 01:23 AM |
| Views | 6 |
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% |
449
83.5 IPS |
|
|
Image Classification (HP)
|
100% |
448
83.3 IPS |
|
|
Image Classification (Q)
|
100% |
1440
267.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
519
8.41 IPS |
|
|
Image Segmentation (HP)
|
100% |
508
8.23 IPS |
|
|
Image Segmentation (Q)
|
98% |
1603
26.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1917
2.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
1815
2.12 IPS |
|
|
Pose Estimation (Q)
|
84% |
3221
3.82 IPS |
|
|
Object Detection (SP)
|
100% |
408
32.4 IPS |
|
|
Object Detection (HP)
|
100% |
422
33.4 IPS |
|
|
Object Detection (Q)
|
83% |
1213
98.0 IPS |
|
|
Face Detection (SP)
|
100% |
1026
12.2 IPS |
|
|
Face Detection (HP)
|
100% |
1028
12.2 IPS |
|
|
Face Detection (Q)
|
95% |
2994
35.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
758
5.84 IPS |
|
|
Depth Estimation (HP)
|
99% |
759
5.85 IPS |
|
|
Depth Estimation (Q)
|
64% |
3291
30.1 IPS |
|
|
Style Transfer (SP)
|
89% |
3635
4.72 IPS |
|
|
Style Transfer (HP)
|
89% |
3676
4.77 IPS |
|
|
Style Transfer (Q)
|
98% |
7344
9.47 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
811
29.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
827
30.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1876
69.5 IPS |
|
|
Text Classification (SP)
|
100% |
464
619.0 IPS |
|
|
Text Classification (HP)
|
100% |
424
565.9 IPS |
|
|
Text Classification (Q)
|
88% |
808
1.09 KIPS |
|
|
Machine Translation (SP)
|
100% |
660
11.4 IPS |
|
|
Machine Translation (HP)
|
100% |
647
11.1 IPS |
|
|
Machine Translation (Q)
|
50% |
26
0.91 IPS |
