samsung SM-A366W
Geekbench AI Score
536
Single Precision Score
935
Half Precision Score
745
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 18 2025 01:53 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 5.16 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
404
75.1 IPS |
|
|
Image Classification (HP)
|
100% |
687
127.7 IPS |
|
|
Image Classification (Q)
|
100% |
652
121.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
582
9.43 IPS |
|
|
Image Segmentation (HP)
|
100% |
1035
16.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
986
16.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1972
2.30 IPS |
|
|
Pose Estimation (HP)
|
99% |
3792
4.44 IPS |
|
|
Pose Estimation (Q)
|
96% |
3757
4.40 IPS |
|
|
Object Detection (SP)
|
100% |
358
28.4 IPS |
|
|
Object Detection (HP)
|
99% |
600
47.6 IPS |
|
|
Object Detection (Q)
|
87% |
563
45.2 IPS |
|
|
Face Detection (SP)
|
100% |
1018
12.1 IPS |
|
|
Face Detection (HP)
|
100% |
2022
24.0 IPS |
|
|
Face Detection (Q)
|
97% |
1734
20.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
1170
9.02 IPS |
|
|
Depth Estimation (HP)
|
98% |
2302
17.8 IPS |
|
|
Depth Estimation (Q)
|
61% |
1707
16.8 IPS |
|
|
Style Transfer (SP)
|
100% |
2162
2.78 IPS |
|
|
Style Transfer (HP)
|
100% |
4539
5.84 IPS |
|
|
Style Transfer (Q)
|
98% |
4515
5.82 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
534
19.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1013
37.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
980
36.3 IPS |
|
|
Text Classification (SP)
|
35% |
22
213.8 IPS |
|
|
Text Classification (HP)
|
35% |
34
312.9 IPS |
|
|
Text Classification (Q)
|
33% |
26
315.5 IPS |
|
|
Machine Translation (SP)
|
100% |
390
6.72 IPS |
|
|
Machine Translation (HP)
|
97% |
437
7.56 IPS |
|
|
Machine Translation (Q)
|
43% |
114
6.46 IPS |
