samsung SM-A366W
Geekbench AI Score
928
Single Precision Score
929
Half Precision Score
1979
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 27 2026 12:24 PM |
| Views | 7 |
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% |
461
85.7 IPS |
|
|
Image Classification (HP)
|
100% |
457
85.0 IPS |
|
|
Image Classification (Q)
|
100% |
1445
268.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
535
8.67 IPS |
|
|
Image Segmentation (HP)
|
100% |
539
8.74 IPS |
|
|
Image Segmentation (Q)
|
98% |
1665
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2034
2.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
2039
2.38 IPS |
|
|
Pose Estimation (Q)
|
84% |
3769
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
456
36.1 IPS |
|
|
Object Detection (HP)
|
100% |
457
36.3 IPS |
|
|
Object Detection (Q)
|
83% |
1387
112.1 IPS |
|
|
Face Detection (SP)
|
100% |
1143
13.6 IPS |
|
|
Face Detection (HP)
|
100% |
1147
13.6 IPS |
|
|
Face Detection (Q)
|
95% |
3403
40.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1553
12.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
1556
12.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
3424
31.4 IPS |
|
|
Style Transfer (SP)
|
89% |
3713
4.82 IPS |
|
|
Style Transfer (HP)
|
89% |
3757
4.88 IPS |
|
|
Style Transfer (Q)
|
98% |
8515
11.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
883
32.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
884
32.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1957
72.5 IPS |
|
|
Text Classification (SP)
|
100% |
483
644.5 IPS |
|
|
Text Classification (HP)
|
100% |
490
653.6 IPS |
|
|
Text Classification (Q)
|
88% |
932
1.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
742
12.8 IPS |
|
|
Machine Translation (HP)
|
100% |
721
12.4 IPS |
|
|
Machine Translation (Q)
|
50% |
406
14.4 IPS |
