samsung SM-A366W
Geekbench AI Score
538
Single Precision Score
946
Half Precision Score
752
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 06 2025 12:06 AM |
| Views | 2 |
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% |
404
75.2 IPS |
|
|
Image Classification (HP)
|
100% |
688
127.9 IPS |
|
|
Image Classification (Q)
|
100% |
645
120.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
590
9.57 IPS |
|
|
Image Segmentation (HP)
|
100% |
1069
17.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
963
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1990
2.32 IPS |
|
|
Pose Estimation (HP)
|
99% |
3815
4.46 IPS |
|
|
Pose Estimation (Q)
|
96% |
3789
4.44 IPS |
|
|
Object Detection (SP)
|
100% |
361
28.6 IPS |
|
|
Object Detection (HP)
|
99% |
608
48.2 IPS |
|
|
Object Detection (Q)
|
87% |
565
45.3 IPS |
|
|
Face Detection (SP)
|
100% |
1041
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2067
24.6 IPS |
|
|
Face Detection (Q)
|
97% |
1781
21.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1183
9.11 IPS |
|
|
Depth Estimation (HP)
|
98% |
2321
17.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
1738
17.1 IPS |
|
|
Style Transfer (SP)
|
100% |
2168
2.79 IPS |
|
|
Style Transfer (HP)
|
100% |
4554
5.85 IPS |
|
|
Style Transfer (Q)
|
98% |
4545
5.86 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
541
20.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1033
38.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1067
39.6 IPS |
|
|
Text Classification (SP)
|
35% |
22
217.2 IPS |
|
|
Text Classification (HP)
|
35% |
35
313.9 IPS |
|
|
Text Classification (Q)
|
33% |
26
313.2 IPS |
|
|
Machine Translation (SP)
|
100% |
378
6.51 IPS |
|
|
Machine Translation (HP)
|
97% |
430
7.43 IPS |
|
|
Machine Translation (Q)
|
43% |
112
6.36 IPS |
