samsung SM-A366W
Geekbench AI Score
787
Single Precision Score
841
Half Precision Score
1474
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 21 2025 06:25 PM |
| Views | 4 |
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% |
194
36.1 IPS |
|
|
Image Classification (HP)
|
100% |
455
84.5 IPS |
|
|
Image Classification (Q)
|
100% |
1447
269.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
531
8.61 IPS |
|
|
Image Segmentation (HP)
|
100% |
528
8.57 IPS |
|
|
Image Segmentation (Q)
|
98% |
1658
27.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2021
2.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
1970
2.30 IPS |
|
|
Pose Estimation (Q)
|
84% |
3622
4.30 IPS |
|
|
Object Detection (SP)
|
100% |
448
35.5 IPS |
|
|
Object Detection (HP)
|
100% |
442
35.1 IPS |
|
|
Object Detection (Q)
|
83% |
1390
112.3 IPS |
|
|
Face Detection (SP)
|
100% |
1086
12.9 IPS |
|
|
Face Detection (HP)
|
100% |
1094
13.0 IPS |
|
|
Face Detection (Q)
|
95% |
3383
40.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
820
6.32 IPS |
|
|
Depth Estimation (HP)
|
99% |
785
6.05 IPS |
|
|
Depth Estimation (Q)
|
64% |
3428
31.4 IPS |
|
|
Style Transfer (SP)
|
89% |
3644
4.73 IPS |
|
|
Style Transfer (HP)
|
89% |
3339
4.33 IPS |
|
|
Style Transfer (Q)
|
98% |
7364
9.50 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
845
31.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
846
31.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1958
72.6 IPS |
|
|
Text Classification (SP)
|
100% |
484
646.6 IPS |
|
|
Text Classification (HP)
|
100% |
483
644.9 IPS |
|
|
Text Classification (Q)
|
88% |
928
1.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
739
12.7 IPS |
|
|
Machine Translation (HP)
|
100% |
723
12.5 IPS |
|
|
Machine Translation (Q)
|
50% |
26
0.92 IPS |
