samsung SM-A366B
Geekbench AI Score
139
Single Precision Score
139
Half Precision Score
392
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | nataljag2106 |
| Upload Date | December 21 2025 04:40 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-A366B |
| Model ID | samsung SM-A366B |
| 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% |
81
15.0 IPS |
|
|
Image Classification (HP)
|
100% |
81
15.0 IPS |
|
|
Image Classification (Q)
|
99% |
255
47.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
110
1.79 IPS |
|
|
Image Segmentation (HP)
|
100% |
111
1.80 IPS |
|
|
Image Segmentation (Q)
|
98% |
299
4.87 IPS |
|
|
Pose Estimation (SP)
|
100% |
139
0.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
139
0.16 IPS |
|
|
Pose Estimation (Q)
|
98% |
561
0.66 IPS |
|
|
Object Detection (SP)
|
100% |
79
6.27 IPS |
|
|
Object Detection (HP)
|
100% |
79
6.27 IPS |
|
|
Object Detection (Q)
|
87% |
267
21.4 IPS |
|
|
Face Detection (SP)
|
100% |
231
2.74 IPS |
|
|
Face Detection (HP)
|
100% |
232
2.76 IPS |
|
|
Face Detection (Q)
|
97% |
618
7.37 IPS |
|
|
Depth Estimation (SP)
|
100% |
184
1.42 IPS |
|
|
Depth Estimation (HP)
|
99% |
184
1.42 IPS |
|
|
Depth Estimation (Q)
|
64% |
518
4.70 IPS |
|
|
Style Transfer (SP)
|
100% |
334
0.43 IPS |
|
|
Style Transfer (HP)
|
100% |
335
0.43 IPS |
|
|
Style Transfer (Q)
|
98% |
1049
1.35 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
86
3.17 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
86
3.18 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
331
12.3 IPS |
|
|
Text Classification (SP)
|
100% |
117
156.3 IPS |
|
|
Text Classification (HP)
|
100% |
117
155.9 IPS |
|
|
Text Classification (Q)
|
91% |
278
373.0 IPS |
|
|
Machine Translation (SP)
|
100% |
202
3.47 IPS |
|
|
Machine Translation (HP)
|
100% |
201
3.46 IPS |
|
|
Machine Translation (Q)
|
57% |
246
6.02 IPS |
