samsung SM-A366W
Geekbench AI Score
603
Single Precision Score
821
Half Precision Score
1458
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 21 2025 02:05 AM |
| Views | 2 |
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% |
189
35.1 IPS |
|
|
Image Classification (HP)
|
100% |
446
83.0 IPS |
|
|
Image Classification (Q)
|
100% |
1444
268.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
504
8.17 IPS |
|
|
Image Segmentation (HP)
|
100% |
511
8.28 IPS |
|
|
Image Segmentation (Q)
|
98% |
1656
26.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2024
2.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
1857
2.17 IPS |
|
|
Pose Estimation (Q)
|
84% |
3422
4.06 IPS |
|
|
Object Detection (SP)
|
100% |
419
33.2 IPS |
|
|
Object Detection (HP)
|
100% |
449
35.6 IPS |
|
|
Object Detection (Q)
|
83% |
1366
110.4 IPS |
|
|
Face Detection (SP)
|
100% |
1073
12.7 IPS |
|
|
Face Detection (HP)
|
100% |
1081
12.8 IPS |
|
|
Face Detection (Q)
|
95% |
3361
40.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
766
5.90 IPS |
|
|
Depth Estimation (HP)
|
99% |
776
5.98 IPS |
|
|
Depth Estimation (Q)
|
64% |
3423
31.4 IPS |
|
|
Style Transfer (SP)
|
89% |
3639
4.72 IPS |
|
|
Style Transfer (HP)
|
89% |
3627
4.71 IPS |
|
|
Style Transfer (Q)
|
98% |
7353
9.48 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
797
29.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
815
30.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1826
67.6 IPS |
|
|
Text Classification (SP)
|
100% |
46
61.2 IPS |
|
|
Text Classification (HP)
|
100% |
418
557.7 IPS |
|
|
Text Classification (Q)
|
88% |
791
1.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
720
12.4 IPS |
|
|
Machine Translation (HP)
|
100% |
708
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
32
1.13 IPS |
