samsung SM-A366W
Geekbench AI Score
926
Single Precision Score
914
Half Precision Score
1993
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 28 2026 11:44 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
451
83.9 IPS |
|
|
Image Classification (HP)
|
100% |
456
84.9 IPS |
|
|
Image Classification (Q)
|
100% |
1440
267.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
543
8.81 IPS |
|
|
Image Segmentation (HP)
|
100% |
545
8.84 IPS |
|
|
Image Segmentation (Q)
|
98% |
1658
27.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2028
2.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
2019
2.36 IPS |
|
|
Pose Estimation (Q)
|
84% |
3762
4.46 IPS |
|
|
Object Detection (SP)
|
100% |
457
36.2 IPS |
|
|
Object Detection (HP)
|
100% |
454
36.1 IPS |
|
|
Object Detection (Q)
|
83% |
1391
112.3 IPS |
|
|
Face Detection (SP)
|
100% |
1144
13.6 IPS |
|
|
Face Detection (HP)
|
100% |
1144
13.6 IPS |
|
|
Face Detection (Q)
|
95% |
3382
40.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1567
12.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1537
11.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
3416
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3707
4.81 IPS |
|
|
Style Transfer (HP)
|
89% |
3658
4.75 IPS |
|
|
Style Transfer (Q)
|
98% |
8241
10.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
881
32.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
879
32.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1965
72.8 IPS |
|
|
Text Classification (SP)
|
100% |
479
638.7 IPS |
|
|
Text Classification (HP)
|
100% |
476
635.4 IPS |
|
|
Text Classification (Q)
|
88% |
888
1.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
734
12.6 IPS |
|
|
Machine Translation (HP)
|
100% |
664
11.4 IPS |
|
|
Machine Translation (Q)
|
50% |
478
17.0 IPS |
