samsung SM-A366W
Geekbench AI Score
537
Single Precision Score
949
Half Precision Score
751
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 11 2025 03:21 AM |
| Views | 6 |
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% |
409
76.1 IPS |
|
|
Image Classification (HP)
|
100% |
711
132.2 IPS |
|
|
Image Classification (Q)
|
100% |
664
123.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
586
9.50 IPS |
|
|
Image Segmentation (HP)
|
100% |
1035
16.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
963
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1983
2.31 IPS |
|
|
Pose Estimation (HP)
|
99% |
3832
4.48 IPS |
|
|
Pose Estimation (Q)
|
96% |
3791
4.44 IPS |
|
|
Object Detection (SP)
|
100% |
356
28.2 IPS |
|
|
Object Detection (HP)
|
99% |
613
48.6 IPS |
|
|
Object Detection (Q)
|
87% |
565
45.3 IPS |
|
|
Face Detection (SP)
|
100% |
1047
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2038
24.2 IPS |
|
|
Face Detection (Q)
|
97% |
1811
21.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1179
9.08 IPS |
|
|
Depth Estimation (HP)
|
98% |
2324
18.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
1723
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2159
2.78 IPS |
|
|
Style Transfer (HP)
|
100% |
4562
5.86 IPS |
|
|
Style Transfer (Q)
|
98% |
4533
5.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
532
19.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1050
38.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1006
37.3 IPS |
|
|
Text Classification (SP)
|
35% |
22
215.3 IPS |
|
|
Text Classification (HP)
|
35% |
35
315.4 IPS |
|
|
Text Classification (Q)
|
33% |
26
318.4 IPS |
|
|
Machine Translation (SP)
|
100% |
381
6.57 IPS |
|
|
Machine Translation (HP)
|
97% |
434
7.50 IPS |
|
|
Machine Translation (Q)
|
43% |
114
6.49 IPS |
