samsung SM-A366W
Geekbench AI Score
536
Single Precision Score
945
Half Precision Score
751
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | October 14 2025 02:12 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
411
76.4 IPS |
|
|
Image Classification (HP)
|
100% |
700
130.2 IPS |
|
|
Image Classification (Q)
|
100% |
666
123.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
584
9.46 IPS |
|
|
Image Segmentation (HP)
|
100% |
1046
17.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
994
16.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1968
2.30 IPS |
|
|
Pose Estimation (HP)
|
99% |
3797
4.44 IPS |
|
|
Pose Estimation (Q)
|
96% |
3749
4.39 IPS |
|
|
Object Detection (SP)
|
100% |
361
28.7 IPS |
|
|
Object Detection (HP)
|
99% |
608
48.2 IPS |
|
|
Object Detection (Q)
|
87% |
573
46.0 IPS |
|
|
Face Detection (SP)
|
100% |
1036
12.3 IPS |
|
|
Face Detection (HP)
|
100% |
2026
24.1 IPS |
|
|
Face Detection (Q)
|
97% |
1773
21.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1185
9.13 IPS |
|
|
Depth Estimation (HP)
|
98% |
2328
18.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
1732
17.1 IPS |
|
|
Style Transfer (SP)
|
100% |
2175
2.80 IPS |
|
|
Style Transfer (HP)
|
100% |
4550
5.85 IPS |
|
|
Style Transfer (Q)
|
98% |
4525
5.83 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
523
19.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1035
38.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1014
37.6 IPS |
|
|
Text Classification (SP)
|
35% |
22
214.9 IPS |
|
|
Text Classification (HP)
|
35% |
34
313.7 IPS |
|
|
Text Classification (Q)
|
33% |
26
315.6 IPS |
|
|
Machine Translation (SP)
|
100% |
380
6.54 IPS |
|
|
Machine Translation (HP)
|
97% |
448
7.74 IPS |
|
|
Machine Translation (Q)
|
43% |
111
6.31 IPS |
