samsung SM-A366W
Geekbench AI Score
909
Single Precision Score
895
Half Precision Score
1861
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 11 2025 03:14 AM |
| Views | 3 |
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% |
455
84.6 IPS |
|
|
Image Classification (HP)
|
100% |
455
84.7 IPS |
|
|
Image Classification (Q)
|
100% |
1443
268.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
532
8.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
544
8.82 IPS |
|
|
Image Segmentation (Q)
|
98% |
1665
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2059
2.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
1974
2.30 IPS |
|
|
Pose Estimation (Q)
|
84% |
3767
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
457
36.2 IPS |
|
|
Object Detection (HP)
|
100% |
445
35.3 IPS |
|
|
Object Detection (Q)
|
83% |
1188
95.9 IPS |
|
|
Face Detection (SP)
|
100% |
1068
12.7 IPS |
|
|
Face Detection (HP)
|
100% |
1073
12.7 IPS |
|
|
Face Detection (Q)
|
95% |
3052
36.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1596
12.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
1505
11.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
2971
27.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3469
4.50 IPS |
|
|
Style Transfer (HP)
|
89% |
3492
4.53 IPS |
|
|
Style Transfer (Q)
|
98% |
7967
10.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
840
31.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
836
30.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1889
70.0 IPS |
|
|
Text Classification (SP)
|
100% |
462
617.2 IPS |
|
|
Text Classification (HP)
|
100% |
455
606.7 IPS |
|
|
Text Classification (Q)
|
88% |
854
1.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
738
12.7 IPS |
|
|
Machine Translation (HP)
|
100% |
708
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
398
14.1 IPS |
