samsung SM-A366W
Geekbench AI Score
830
Single Precision Score
783
Half Precision Score
1412
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 28 2025 02:14 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 5.16 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
459
85.4 IPS |
|
|
Image Classification (HP)
|
100% |
427
79.4 IPS |
|
|
Image Classification (Q)
|
100% |
1322
245.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
508
8.23 IPS |
|
|
Image Segmentation (HP)
|
100% |
469
7.60 IPS |
|
|
Image Segmentation (Q)
|
98% |
1452
23.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1888
2.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
1876
2.19 IPS |
|
|
Pose Estimation (Q)
|
84% |
3619
4.29 IPS |
|
|
Object Detection (SP)
|
100% |
441
35.0 IPS |
|
|
Object Detection (HP)
|
100% |
382
30.3 IPS |
|
|
Object Detection (Q)
|
83% |
1362
110.0 IPS |
|
|
Face Detection (SP)
|
100% |
1130
13.4 IPS |
|
|
Face Detection (HP)
|
100% |
1094
13.0 IPS |
|
|
Face Detection (Q)
|
95% |
3133
37.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
764
5.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
760
5.85 IPS |
|
|
Depth Estimation (Q)
|
64% |
3411
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3611
4.69 IPS |
|
|
Style Transfer (HP)
|
89% |
3306
4.29 IPS |
|
|
Style Transfer (Q)
|
98% |
7356
9.49 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
841
31.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
840
31.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1743
64.6 IPS |
|
|
Text Classification (SP)
|
100% |
422
563.6 IPS |
|
|
Text Classification (HP)
|
100% |
410
546.6 IPS |
|
|
Text Classification (Q)
|
88% |
843
1.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
723
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
645
11.1 IPS |
|
|
Machine Translation (Q)
|
50% |
29
1.04 IPS |
