samsung SM-A366W
Geekbench AI Score
873
Single Precision Score
849
Half Precision Score
1809
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | October 01 2025 05:45 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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 | 5.25 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
445
82.8 IPS |
|
|
Image Classification (HP)
|
100% |
455
84.6 IPS |
|
|
Image Classification (Q)
|
100% |
1442
268.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
526
8.52 IPS |
|
|
Image Segmentation (HP)
|
100% |
528
8.56 IPS |
|
|
Image Segmentation (Q)
|
98% |
1604
26.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1908
2.23 IPS |
|
|
Pose Estimation (HP)
|
100% |
1882
2.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
3760
4.46 IPS |
|
|
Object Detection (SP)
|
100% |
458
36.3 IPS |
|
|
Object Detection (HP)
|
100% |
395
31.3 IPS |
|
|
Object Detection (Q)
|
83% |
1207
97.5 IPS |
|
|
Face Detection (SP)
|
100% |
1054
12.5 IPS |
|
|
Face Detection (HP)
|
100% |
1062
12.6 IPS |
|
|
Face Detection (Q)
|
95% |
2933
35.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
1495
11.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
1448
11.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
2917
26.7 IPS |
|
|
Style Transfer (SP)
|
89% |
3288
4.27 IPS |
|
|
Style Transfer (HP)
|
89% |
3287
4.27 IPS |
|
|
Style Transfer (Q)
|
98% |
7463
9.62 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
776
28.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
767
28.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1742
64.5 IPS |
|
|
Text Classification (SP)
|
100% |
436
581.6 IPS |
|
|
Text Classification (HP)
|
100% |
431
575.0 IPS |
|
|
Text Classification (Q)
|
88% |
819
1.11 KIPS |
|
|
Machine Translation (SP)
|
100% |
723
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
654
11.3 IPS |
|
|
Machine Translation (Q)
|
50% |
393
14.0 IPS |
