samsung SM-A366W
Geekbench AI Score
844
Single Precision Score
831
Half Precision Score
1351
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 10 2025 02:36 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% |
453
84.3 IPS |
|
|
Image Classification (HP)
|
100% |
446
82.9 IPS |
|
|
Image Classification (Q)
|
100% |
1440
267.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
516
8.36 IPS |
|
|
Image Segmentation (HP)
|
100% |
518
8.39 IPS |
|
|
Image Segmentation (Q)
|
98% |
1657
26.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1989
2.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
1917
2.24 IPS |
|
|
Pose Estimation (Q)
|
84% |
3479
4.13 IPS |
|
|
Object Detection (SP)
|
100% |
453
35.9 IPS |
|
|
Object Detection (HP)
|
100% |
451
35.8 IPS |
|
|
Object Detection (Q)
|
83% |
1389
112.2 IPS |
|
|
Face Detection (SP)
|
100% |
1096
13.0 IPS |
|
|
Face Detection (HP)
|
100% |
1106
13.1 IPS |
|
|
Face Detection (Q)
|
95% |
1169
14.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
783
6.03 IPS |
|
|
Depth Estimation (HP)
|
99% |
797
6.14 IPS |
|
|
Depth Estimation (Q)
|
64% |
3392
31.1 IPS |
|
|
Style Transfer (SP)
|
89% |
3619
4.70 IPS |
|
|
Style Transfer (HP)
|
89% |
3326
4.32 IPS |
|
|
Style Transfer (Q)
|
98% |
7351
9.48 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
837
30.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
838
30.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1949
72.2 IPS |
|
|
Text Classification (SP)
|
100% |
478
637.7 IPS |
|
|
Text Classification (HP)
|
100% |
474
632.6 IPS |
|
|
Text Classification (Q)
|
88% |
913
1.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
703
12.1 IPS |
|
|
Machine Translation (HP)
|
100% |
678
11.7 IPS |
|
|
Machine Translation (Q)
|
50% |
34
1.22 IPS |
