samsung SM-A366W
Geekbench AI Score
755
Single Precision Score
782
Half Precision Score
1357
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 19 2025 11:56 PM |
| Views | 14 |
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% |
193
35.8 IPS |
|
|
Image Classification (HP)
|
100% |
232
43.2 IPS |
|
|
Image Classification (Q)
|
100% |
1447
269.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
488
7.91 IPS |
|
|
Image Segmentation (HP)
|
100% |
518
8.40 IPS |
|
|
Image Segmentation (Q)
|
98% |
1659
27.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1998
2.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
1978
2.31 IPS |
|
|
Pose Estimation (Q)
|
84% |
3702
4.39 IPS |
|
|
Object Detection (SP)
|
100% |
378
30.0 IPS |
|
|
Object Detection (HP)
|
100% |
456
36.2 IPS |
|
|
Object Detection (Q)
|
83% |
1366
110.3 IPS |
|
|
Face Detection (SP)
|
100% |
1074
12.8 IPS |
|
|
Face Detection (HP)
|
100% |
1074
12.8 IPS |
|
|
Face Detection (Q)
|
95% |
3364
40.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
793
6.11 IPS |
|
|
Depth Estimation (HP)
|
99% |
796
6.13 IPS |
|
|
Depth Estimation (Q)
|
64% |
1425
13.0 IPS |
|
|
Style Transfer (SP)
|
89% |
3597
4.67 IPS |
|
|
Style Transfer (HP)
|
89% |
3581
4.65 IPS |
|
|
Style Transfer (Q)
|
98% |
8520
11.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
822
30.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
801
29.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1735
64.3 IPS |
|
|
Text Classification (SP)
|
100% |
466
621.7 IPS |
|
|
Text Classification (HP)
|
100% |
460
613.7 IPS |
|
|
Text Classification (Q)
|
88% |
855
1.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
725
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
708
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
29
1.04 IPS |
