samsung SM-A366W
Geekbench AI Score
535
Single Precision Score
946
Half Precision Score
752
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 13 2026 02:24 PM |
| Views | 3 |
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% |
406
75.6 IPS |
|
|
Image Classification (HP)
|
100% |
706
131.4 IPS |
|
|
Image Classification (Q)
|
100% |
659
122.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
591
9.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
1023
16.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
972
15.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1995
2.33 IPS |
|
|
Pose Estimation (HP)
|
99% |
3814
4.46 IPS |
|
|
Pose Estimation (Q)
|
96% |
3778
4.43 IPS |
|
|
Object Detection (SP)
|
100% |
357
28.3 IPS |
|
|
Object Detection (HP)
|
99% |
609
48.3 IPS |
|
|
Object Detection (Q)
|
87% |
572
46.0 IPS |
|
|
Face Detection (SP)
|
100% |
1037
12.3 IPS |
|
|
Face Detection (HP)
|
100% |
2029
24.1 IPS |
|
|
Face Detection (Q)
|
97% |
1777
21.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1183
9.11 IPS |
|
|
Depth Estimation (HP)
|
98% |
2338
18.1 IPS |
|
|
Depth Estimation (Q)
|
61% |
1732
17.1 IPS |
|
|
Style Transfer (SP)
|
100% |
2174
2.79 IPS |
|
|
Style Transfer (HP)
|
100% |
4557
5.86 IPS |
|
|
Style Transfer (Q)
|
98% |
4535
5.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
512
18.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1040
38.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1010
37.4 IPS |
|
|
Text Classification (SP)
|
35% |
22
216.0 IPS |
|
|
Text Classification (HP)
|
35% |
35
316.8 IPS |
|
|
Text Classification (Q)
|
33% |
27
324.8 IPS |
|
|
Machine Translation (SP)
|
100% |
379
6.53 IPS |
|
|
Machine Translation (HP)
|
97% |
438
7.58 IPS |
|
|
Machine Translation (Q)
|
43% |
110
6.26 IPS |
