samsung SM-A366W
Geekbench AI Score
792
Single Precision Score
847
Half Precision Score
1483
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 25 2025 06:03 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% |
196
36.5 IPS |
|
|
Image Classification (HP)
|
100% |
454
84.4 IPS |
|
|
Image Classification (Q)
|
100% |
1446
269.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
530
8.60 IPS |
|
|
Image Segmentation (HP)
|
100% |
532
8.62 IPS |
|
|
Image Segmentation (Q)
|
98% |
1670
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2021
2.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
1948
2.27 IPS |
|
|
Pose Estimation (Q)
|
84% |
3754
4.45 IPS |
|
|
Object Detection (SP)
|
100% |
455
36.1 IPS |
|
|
Object Detection (HP)
|
100% |
456
36.2 IPS |
|
|
Object Detection (Q)
|
83% |
1377
111.3 IPS |
|
|
Face Detection (SP)
|
100% |
1119
13.3 IPS |
|
|
Face Detection (HP)
|
100% |
1111
13.2 IPS |
|
|
Face Detection (Q)
|
95% |
3409
40.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
816
6.29 IPS |
|
|
Depth Estimation (HP)
|
99% |
804
6.20 IPS |
|
|
Depth Estimation (Q)
|
64% |
3413
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3651
4.74 IPS |
|
|
Style Transfer (HP)
|
89% |
3393
4.40 IPS |
|
|
Style Transfer (Q)
|
98% |
7367
9.50 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
860
31.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
858
31.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1951
72.3 IPS |
|
|
Text Classification (SP)
|
100% |
484
646.5 IPS |
|
|
Text Classification (HP)
|
100% |
477
636.4 IPS |
|
|
Text Classification (Q)
|
88% |
918
1.24 KIPS |
|
|
Machine Translation (SP)
|
100% |
733
12.6 IPS |
|
|
Machine Translation (HP)
|
100% |
719
12.4 IPS |
|
|
Machine Translation (Q)
|
50% |
27
0.96 IPS |
