samsung SM-A366W
Geekbench AI Score
536
Single Precision Score
944
Half Precision Score
750
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 08 2026 07:22 AM |
| Views | 8 |
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% |
693
129.0 IPS |
|
|
Image Classification (Q)
|
100% |
662
123.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
584
9.47 IPS |
|
|
Image Segmentation (HP)
|
100% |
1050
17.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
956
15.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1994
2.33 IPS |
|
|
Pose Estimation (HP)
|
99% |
3800
4.45 IPS |
|
|
Pose Estimation (Q)
|
96% |
3748
4.39 IPS |
|
|
Object Detection (SP)
|
100% |
360
28.5 IPS |
|
|
Object Detection (HP)
|
99% |
608
48.2 IPS |
|
|
Object Detection (Q)
|
87% |
567
45.5 IPS |
|
|
Face Detection (SP)
|
100% |
1041
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2042
24.3 IPS |
|
|
Face Detection (Q)
|
97% |
1795
21.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1180
9.09 IPS |
|
|
Depth Estimation (HP)
|
98% |
2313
17.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
1724
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2073
2.67 IPS |
|
|
Style Transfer (HP)
|
100% |
4557
5.86 IPS |
|
|
Style Transfer (Q)
|
98% |
4507
5.81 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
537
19.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1034
38.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1002
37.1 IPS |
|
|
Text Classification (SP)
|
35% |
22
214.7 IPS |
|
|
Text Classification (HP)
|
35% |
34
312.9 IPS |
|
|
Text Classification (Q)
|
33% |
26
312.7 IPS |
|
|
Machine Translation (SP)
|
100% |
381
6.56 IPS |
|
|
Machine Translation (HP)
|
97% |
445
7.69 IPS |
|
|
Machine Translation (Q)
|
43% |
116
6.59 IPS |
