samsung SM-A366W
Geekbench AI Score
835
Single Precision Score
830
Half Precision Score
1453
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 22 2025 02:10 AM |
| 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% |
447
83.1 IPS |
|
|
Image Classification (HP)
|
100% |
444
82.5 IPS |
|
|
Image Classification (Q)
|
100% |
1279
237.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
437
7.09 IPS |
|
|
Image Segmentation (HP)
|
100% |
514
8.32 IPS |
|
|
Image Segmentation (Q)
|
98% |
1647
26.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
2001
2.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
1866
2.18 IPS |
|
|
Pose Estimation (Q)
|
84% |
3467
4.11 IPS |
|
|
Object Detection (SP)
|
100% |
451
35.8 IPS |
|
|
Object Detection (HP)
|
100% |
449
35.6 IPS |
|
|
Object Detection (Q)
|
83% |
1384
111.8 IPS |
|
|
Face Detection (SP)
|
100% |
1091
13.0 IPS |
|
|
Face Detection (HP)
|
100% |
1040
12.4 IPS |
|
|
Face Detection (Q)
|
95% |
3388
40.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
836
6.44 IPS |
|
|
Depth Estimation (HP)
|
99% |
819
6.31 IPS |
|
|
Depth Estimation (Q)
|
64% |
3431
31.4 IPS |
|
|
Style Transfer (SP)
|
89% |
3626
4.71 IPS |
|
|
Style Transfer (HP)
|
89% |
3531
4.58 IPS |
|
|
Style Transfer (Q)
|
98% |
7322
9.44 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
802
29.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
803
29.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1961
72.7 IPS |
|
|
Text Classification (SP)
|
100% |
485
646.7 IPS |
|
|
Text Classification (HP)
|
100% |
478
638.0 IPS |
|
|
Text Classification (Q)
|
88% |
892
1.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
731
12.6 IPS |
|
|
Machine Translation (HP)
|
100% |
705
12.1 IPS |
|
|
Machine Translation (Q)
|
50% |
28
0.98 IPS |
