samsung SM-A366W
Geekbench AI Score
739
Single Precision Score
773
Half Precision Score
1395
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 12 2025 01:57 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% |
200
37.3 IPS |
|
|
Image Classification (HP)
|
100% |
196
36.5 IPS |
|
|
Image Classification (Q)
|
100% |
1223
227.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
494
8.01 IPS |
|
|
Image Segmentation (HP)
|
100% |
460
7.46 IPS |
|
|
Image Segmentation (Q)
|
98% |
1178
19.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2050
2.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
2040
2.38 IPS |
|
|
Pose Estimation (Q)
|
84% |
3761
4.46 IPS |
|
|
Object Detection (SP)
|
100% |
451
35.8 IPS |
|
|
Object Detection (HP)
|
100% |
457
36.3 IPS |
|
|
Object Detection (Q)
|
83% |
1258
101.6 IPS |
|
|
Face Detection (SP)
|
100% |
667
7.92 IPS |
|
|
Face Detection (HP)
|
100% |
1132
13.5 IPS |
|
|
Face Detection (Q)
|
95% |
3256
38.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
797
6.14 IPS |
|
|
Depth Estimation (HP)
|
99% |
790
6.08 IPS |
|
|
Depth Estimation (Q)
|
64% |
3410
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3661
4.75 IPS |
|
|
Style Transfer (HP)
|
89% |
3678
4.77 IPS |
|
|
Style Transfer (Q)
|
98% |
7358
9.49 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
824
30.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
865
32.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2032
75.3 IPS |
|
|
Text Classification (SP)
|
100% |
460
613.5 IPS |
|
|
Text Classification (HP)
|
100% |
452
603.9 IPS |
|
|
Text Classification (Q)
|
88% |
852
1.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
726
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
711
12.3 IPS |
|
|
Machine Translation (Q)
|
50% |
29
1.04 IPS |
