samsung SM-A366W
Geekbench AI Score
538
Single Precision Score
946
Half Precision Score
748
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 20 2025 02:41 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% |
412
76.6 IPS |
|
|
Image Classification (HP)
|
100% |
688
128.0 IPS |
|
|
Image Classification (Q)
|
100% |
642
119.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
588
9.53 IPS |
|
|
Image Segmentation (HP)
|
100% |
1077
17.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
966
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1990
2.32 IPS |
|
|
Pose Estimation (HP)
|
99% |
3795
4.44 IPS |
|
|
Pose Estimation (Q)
|
96% |
3764
4.41 IPS |
|
|
Object Detection (SP)
|
100% |
360
28.6 IPS |
|
|
Object Detection (HP)
|
99% |
603
47.8 IPS |
|
|
Object Detection (Q)
|
87% |
572
45.9 IPS |
|
|
Face Detection (SP)
|
100% |
1042
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2034
24.2 IPS |
|
|
Face Detection (Q)
|
97% |
1783
21.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1183
9.12 IPS |
|
|
Depth Estimation (HP)
|
98% |
2313
17.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
1726
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2178
2.80 IPS |
|
|
Style Transfer (HP)
|
100% |
4559
5.86 IPS |
|
|
Style Transfer (Q)
|
98% |
4535
5.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
524
19.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1037
38.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1005
37.2 IPS |
|
|
Text Classification (SP)
|
35% |
22
218.7 IPS |
|
|
Text Classification (HP)
|
35% |
35
315.5 IPS |
|
|
Text Classification (Q)
|
33% |
26
315.0 IPS |
|
|
Machine Translation (SP)
|
100% |
379
6.53 IPS |
|
|
Machine Translation (HP)
|
97% |
438
7.56 IPS |
|
|
Machine Translation (Q)
|
43% |
113
6.40 IPS |
