samsung SM-A366W
Geekbench AI Score
838
Single Precision Score
832
Half Precision Score
1479
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 19 2025 06:33 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% |
453
84.3 IPS |
|
|
Image Classification (HP)
|
100% |
452
84.0 IPS |
|
|
Image Classification (Q)
|
100% |
1436
267.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
526
8.52 IPS |
|
|
Image Segmentation (HP)
|
100% |
492
7.97 IPS |
|
|
Image Segmentation (Q)
|
98% |
1670
27.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2020
2.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
1886
2.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
3615
4.29 IPS |
|
|
Object Detection (SP)
|
100% |
207
16.4 IPS |
|
|
Object Detection (HP)
|
100% |
450
35.7 IPS |
|
|
Object Detection (Q)
|
83% |
1384
111.8 IPS |
|
|
Face Detection (SP)
|
100% |
1066
12.7 IPS |
|
|
Face Detection (HP)
|
100% |
1076
12.8 IPS |
|
|
Face Detection (Q)
|
95% |
3289
39.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1543
11.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
784
6.04 IPS |
|
|
Depth Estimation (Q)
|
64% |
3420
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3644
4.73 IPS |
|
|
Style Transfer (HP)
|
89% |
3650
4.74 IPS |
|
|
Style Transfer (Q)
|
98% |
7324
9.44 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
815
30.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
806
29.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1952
72.3 IPS |
|
|
Text Classification (SP)
|
100% |
486
649.1 IPS |
|
|
Text Classification (HP)
|
100% |
480
640.5 IPS |
|
|
Text Classification (Q)
|
88% |
896
1.21 KIPS |
|
|
Machine Translation (SP)
|
100% |
728
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
708
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
29
1.04 IPS |
