samsung SM-A366W
Geekbench AI Score
536
Single Precision Score
948
Half Precision Score
745
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 27 2025 03:36 AM |
| Views | 5 |
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% |
407
75.7 IPS |
|
|
Image Classification (HP)
|
100% |
693
128.9 IPS |
|
|
Image Classification (Q)
|
100% |
638
118.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
583
9.46 IPS |
|
|
Image Segmentation (HP)
|
100% |
1061
17.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
965
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1994
2.33 IPS |
|
|
Pose Estimation (HP)
|
99% |
3788
4.43 IPS |
|
|
Pose Estimation (Q)
|
96% |
3761
4.41 IPS |
|
|
Object Detection (SP)
|
100% |
357
28.3 IPS |
|
|
Object Detection (HP)
|
99% |
603
47.8 IPS |
|
|
Object Detection (Q)
|
87% |
563
45.2 IPS |
|
|
Face Detection (SP)
|
100% |
1043
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2084
24.8 IPS |
|
|
Face Detection (Q)
|
97% |
1778
21.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1181
9.10 IPS |
|
|
Depth Estimation (HP)
|
98% |
2321
17.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
1723
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2177
2.80 IPS |
|
|
Style Transfer (HP)
|
100% |
4550
5.85 IPS |
|
|
Style Transfer (Q)
|
98% |
4529
5.84 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
522
19.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1026
37.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
996
36.9 IPS |
|
|
Text Classification (SP)
|
35% |
22
216.6 IPS |
|
|
Text Classification (HP)
|
35% |
36
324.4 IPS |
|
|
Text Classification (Q)
|
33% |
26
312.9 IPS |
|
|
Machine Translation (SP)
|
100% |
379
6.53 IPS |
|
|
Machine Translation (HP)
|
97% |
433
7.49 IPS |
|
|
Machine Translation (Q)
|
43% |
113
6.45 IPS |
